CRUISE REPORT: P17E
(Updated JUN 2018)








Highlights


                        Cruise Summary Information


               Section Designation  P17E (MR16-09)
Expedition designation (ExpoCodes)  49NZ20170208
                  Chief Scientists  Hiroshi Uchida / JAMSTEC
                             Dates  2017 FEB 08 - 2017 MAR 05 
                              Ship  Mirai
                     Ports of call  Punta Arenas, Chile – Auckland, New Zealand

                                                  39° 46.31' S
             Geographic Boundaries  175° 19.69' W             72° 47.49' W
                                                  67° 0.23' S

                          Stations  35
      Floats and drifters deployed  3 Argo floats, 2 Deep Argo floats, 
                                    5 SOCOM floats, 7 CO2 buoys deployed
    Moorings deployed or recovered  0

                           Contact Information:
                              Hiroshi Uchida
                          huchida@jamstec.go.jp



















Mirai Cruise Report MR16−09





                      Trans South Pacific  Project


                   December 27, 2016 − March 28, 2017


      Japan Agency for Marine-Earth Science and Technology (JAMSTEC)



                                 Content

                          I.  Cruise Information
                 Murata, Harada, Abe and Uchida (JAMSTEC)


1.  Cruise ID
2.  Name of Vessel
3.  Title of Cruise
4.  Cruise Period
5.  Ports of Departure/call/arrival
6.  Research Area
7.  Research Map


                            II.  Researchers
                 Murata, Harada, Abe and Uchida (JAMSTEC)


1.  Chief Scientists
2.  Representative of the Science Party and the Proposed Science Plan
3.  List of Participants
4.  List of Principal Investigator and Person in Charge on the Ship


                            III.  Observation

1.  Cruise Narrative
    Murata, Harada, Abe and Uchida (JAMSTEC)


2.  Cruise Track and Log
    Murata, Harada, Abe and Uchida (JAMSTEC)


3.  Underway Observation
    3.1  Navigation
         Murata (JAMSTEC), Sueyoshi, Y. Murakami, Tokunaga, Inagaki, 
         Okumura (NME), K. Yoshida, Kimura, M. Murakami (Mirai Crew)
    3.2  Swath Bathymetry (MBES, Sub-bottom profiler)
         Abe (JAMSTEC), Matsumoto (Univ. of Ryukyu), Fujiwara (JAMSTEC), 
         Sueyoshi, Y. Murakami, Tokunaga, Inagaki, Okumura, K. Yoshida 
         (NME), Kimura, M. Murakami (Mirai Crew)
    3.3  Three Component and Total Force Magnetometry
         Abe (JAMSTEC), Matsumoto (Univ. of Ryukyu), Fujiwara (JAMSTEC), 
         Sueyoshi, Y. Murakami, Tokunaga, Inagaki, Okumura, K. Yoshida 
         (NME), Kimura, M. Murakami (NME)
    3.4  Sea Surface Gravity
         Abe (JAMSTEC), Matsumoto (Univ. of Ryukyu), Fujiwara (JAMSTEC),  
         Sueyoshi, Y. Murakami, Tokunaga, Inagaki, Okumura, K. Yoshida 
         (NME), Kimura, M. Murakami (Mirai Crew)
    3.5  Surface Meteorological Observations
         M. Katsumata (JAMSTEC), Sueyoshi, Y. Murakami, Tokunaga, 
         Inagaki, Okumura, K. Yoshida (NME), Kimura, M. Murakami (Mirai 
         Crew)
    3.6  Thermo-salinograph and Related Measurements
         Uchida, Shiozaki, Sasaoka (JAMSTEC), H. Sato, Tamada, Enoki, 
         Kuwahara, Orui (MWJ)
    3.7  pCO2
         Murata (JAMSTEC), Watai, A. Ono, Deguchi, Fujiki (MWJ)
    3.8  Satellite Image Acquisition
         M. Katsumata (JAMSTEC), Sueyoshi, Y. Murakami, Tokunaga, 
         Inagaki, Okumura, K. Yoshida (NME), Kimura, M. Murakami (Mirai 
         Crew)
    3.9  ADCP
         Kouketsu (JAMSTEC), Schneider (Univ. of Concepcion), Sueyoshi, 
         Y. Murakami, Tokunaga, Inagaki, Okumura, K. Yoshida (NME), 
         Kimura, M. Murakami (Mirai Crew)
   3.10  Ceilometer Observation
         M. Katsumata (JAMSTEC), Sueyoshi, Y. Murakami, Tokunaga, 
         Inagaki, Okumura, K. Yoshida (NME), Kimura, M. Murakami (Mirai 
         Crew)
   3.11  Marine Aerosols
         Noda (Rakuno Gakuen Univ.), Gutierrez (Univ. of Concepcion), O. 
         Yoshida (Rakuno Gakuen Univ.)
   3.12  Aerosol Optical Characteristics Measured by Ship-borne Sky  
         Radiometer
         Aoki (Toyama Univ.), Hayasaka (Tohoku Univ.)
   3.13  C-Band Polarimetric Doppler Weather Radar
         M. Katsumata, Geng (JAMSTEC), Sueyoshi, Y. Murakami, Tokunaga,    
         Inagaki, Okumura, K. Yoshida (NME), Kimura, M. Murakami (Mirai 
         Crew)
   3.14  Lidar Observation
         M. Katsumata, Taniguchi, Geng (JAMSTEC)
   3.15  Disdrometers
         M. Katsumata, Taniguchi, Geng (JAMSTEC)
   3.16  GNSS Precipitable Water
         M. Katsumata, Fujita, Taniguchi (JAMSTEC)
   3.17  Ship-borne Measurement of Aerosols
         Taketani, Kanaya, Miyagawa, Takashima (JAMSTEC), Todo (NIPR), 
         Komazaki (JAMSTEC), Matsui (Nagoya Univ.), Yoshizue (Tokyo Univ. 
         of Sci.)
   3.18  Underway CT
         Murata (JAMSTEC), Watai, A. Ono, Deguchi, Fujiki (MWJ)
   3.19  XCTD
         Uchida (JAMSTEC), Okumura, Inagaki, Kimura (NME), M. Murakami 
         (Mirai Crew)
   3.20  Radiosonde Observations
         M. Katsumata, Geng, Taniguchi (JAMSTEC), Sueyoshi, Y. Murakami 
        (NME)


4.  Station Observation
    4.1  Single Channel Seismic Survey
         Abe (JAMSTEC), Nasu, Kuno, Iijima, Hayashi (NME)
    4.2  Sediment Core
         Nagashima (JAMSTEC), Lany (AWI), Arz (IOW), Tokunaga, Inagaki, 
         Y. Murakami (NME), Y. Sato, Hatakeyama, Y. Katayama, Takahashi, 
         Miyajima, Yamaguchi (MWJ)
    4.3  Dredge
         Y. Sato, Hatakeyama, Y. Katayama (MWJ), Abe, Machida (JAMSTEC), 
         Anma (Univ. of Tsukuba), Orihashi (The Univ. of Tokyo)
    4.4  Biological Sample
         Castro (UdeC)
    4.5  Suspended Particles
         Gonzalez, Menshel (IDEAL)
    4.6  Physiological Characteristics of Phytoplankton Assemblages in 
         the Southern Patagonia Pacific Margin Waters Iriarte (IDEAL), 
         Shiozaki (JAMSTEC)
    4.7  CTDO2 Measurements
         Uchida (JAMSTEC), Ito, Tanihara, K. Katayama, Oshitani, 
         Kobayashi (MWJ), Sunamura (The Univ. of Tokyo)
    4.8  Bottle Salinity
         Uchida (JAMSTEC), Tanihara, Watanabe (MWJ)
    4.9  Oxygen
         Kumamoto (JAMSTEC), H. Sato, Tamada, Kuwahara, Orui, Htakeyama 
         (MWJ)
   4.10  Nutrients
         Aoyama (JAMSTEC), Sone, A. Ono, Yokogawa, Ishikawa, Y. Sato 
         (MWJ)
   4.11  Density
         Uchida, Shiozaki (JAMSTEC)
   4.12  Carbon Items
         Murata (JAMSTEC), Watai, A. Ono, Deguchi, Fujuki (MWJ)
   4.13  Geochemistry and Microbiology: Nitrogen and Carbon Cycles
         Yoshikawa (JAMSTEC), O. Yoshida, Chida, Iwamatsu, Koya (Rakuno 
         Gakuen Univ.), Makabe (JAMSTEC)
   4.14  Vertical Profiles of Microbial Abundance, Activity and Diversity
         Yokokawa (JAMSTEC), Sunamura (The Univ. of Tokyo), Nunoura 
         (JAMSTEC)
   4.15  Chlorophyll a
         Sasaoka, Shiozaki (JAMSTEC), H. Sato, Enoki, Kuwahara, Tamada, 
         Hatakeyama (MWJ)
   4.16  Nitrogen Fixation
         Shiozaki (JAMSTEC)
   4.17  Absorption Coefficients of Particulate Matter and Colored 
         Dissolved Organic Matter (CDOM)
         Sasaoka (JAMSTEC)
   4.18  Calcium
         E. Ono (JAMSTEC)
   4.19  Dissolved Organic Matter and the Associated Parameters
         Shigemitsu, Yokokawa, Wakita, Murata (JAMSTEC)
   4.20  Carbon Isotopes
         Kumamoto (JAMSTEC)
   4.21  Stable Isotopes of Water
         Uchida, K. Katsumata (JAMSTEC)
   4.22  Beryllium Isotopes
         Kumamoto (JAMSTEC)
   4.23  Lowered Acoustic Doppler Current Profiler
         Kouketsu, Uchida, K. Katsumata (JAMSTEC)
   4.24  Micro Rider
         Kouketsu, Uchida, K. Katsumata (JAMSTEC)
   4.25  Sound Velocity
         Uchida (JAMSTEC), Ito, Tanihara, K. Katayama, Oshitani, 
         Kobayashi (MWJ)
   4.26  pH, POC, and HPLC Sampling for SOCCOM Project
         K. Katsumata, Sasaoka (JAMSTEC), Boss (Univ. of Maine), Dickson, 
         Becker, Talley (SIO), Key (Princeton Univ.)
   4.27  Chlorofluorocarbons and Sulfur Hexafluoride
         Sasaki (JAMSTEC), H. Sato, Hoshino, Orui (MWJ)


5.  Floats, Drifters and Moorings
    5.1  Argo Floats
         Masuda, Hosoda, Sato, Hirano (JAMSTEC), Oshitani (MWJ)
    5.2  SOCCOM BGC Floats
         K. Katsumata (JAMSTEC), Riser, Swift (Univ. of Washington), 
         Johnson (MBARI), Boss (Univ. of Maine), Talley (SIO)
    5.3  CO2 buoys
         Murata, Sasaoka (JAMSTEC), Watai, A. Ono, Deguchi, Fujiki (MWJ)




















I.  Cruise Information

1.  Cruise ID
    MR16-09


2.  Name of vessel
    R/V Mirai


3.  Title of cruise
    Trans South Pacific Project


4.  Cruise period
    Leg 1: 27th December 2016 – 17th January 2017 
    Leg 2: 20th January – 5th February 2017
    Leg 3: 8th February – 5th March 2017
    Leg 4: 8th March – 28th March 2017

5.  Ports of departure/call/arrival
    Leg 1: Suva, Fuji – Puerto Montt, Chile
    Leg 2: Puerto Montt, Chile – Punta Arenas, Chile 
    Leg 3: Punta Arenas, Chile – Auckland, New Zealand 
    Leg 4: Auckland, New Zealand – Sekinehama, Japan

6.  Research area
    South Pacific, Chilean coast, Southern Ocean and western North 
    Pacific



7.  Research map


II.  Researchers

1.  Chief scientists
    Leg 1: Akihiko Murata (JAMSTEC) 
    Leg 2: Naomi Harada (JAMSTEC) 
    Leg 3: Hiroshi Uchida (JAMSTEC) 
    Leg 4: Akihiko Murata (JAMSTEC)

2.  Representative of the science party and the proposed science plan
    (1) Naomi Harada, Akihiko Murata and Natsue Abe: (JAMSTEC): Trans 
        Pacific Project: Ocean Acidification, Marine Biodiversity, 
        Pacific Meridional Overturning Circulation, Crustal Evolution;
    (2) Fumikazu Taketani (JAMSTEC): Ship-borne measurements of aerosols 
        in the marine atmosphere: Investigation of potential influence of 
        marine aerosol particles on the climate;
    (3) Shuhei Masuda (JAMSTEC): The monitoring of ocean climate change 
        from surface to deep layer in the Southern Ocean by using Argo-
        type floats;
    (4) Taichi Yokokawa (JAMSTEC): Geochemical and microbiological 
        processes throughout water column of the Southern Ocean in the 
        eastern Pacific sector;
    (5) Toshiya Fujiwara (JAMSTEC): Regional distribution of seafloor 
        displacement caused by the 2011 Tohoku-oki earthquake: What 
        happened in the northern Japan Trench?
    (6) Masaki Katsumata (JAMSTEC): Cumulus-scale air-sea interaction 
        study by shipboard in-situ observations;
    (7) Chisato Yoshikawa (JAMSTEC): Geochemical and microbiological 
        investigation for sea surface to sea bottom along Chile margin;
    (8) Kazuma Aoki (Toyama University): Aerosol optical characteristics 
        measured by Ship-borne Sky radiometer;
    (9) Takeshi Matsumoto (University of the Ryukyus): Cessation of 
        active spreading axes at trenches.



3.  List of participants

                                              Affili-
Name                 Charge on board          ation    Occupation
———————————————————  ———————————————————————  ———————  ————————————————
Leg 1: Suva – Puerto Montt

Akihiko Murata       Chief Scientist          JAMSTEC  Scientist
Masaki Katsumata     Meteorology              JAMSTEC  Scientist
Soichiro Sueyoshi    Chief Technician/ADCP/   NME      Technical Staff
                     Meteorology/Geophysics
Yutaro Murakami      Meteorology/ADCP/        NME      Technical Staff
                     Geophysics    
Tomonori Watai       Chief Technician         MWJ      Technical Staff
                     CO2-system Properties
Sinichiro Yokogawa   Nutrients                MWJ      Technical Staff
Hiroyasu Sato        DO/TSG                   MWJ      Technical Staff
Nagisa Fujiki        CO2-system Properties    MWJ      Technical Staff



Leg 2: Puerto Montt – Punta Arenas

Naomi Harada         Chief Scientist          JAMSTEC  Scientist
Natsue Abe           Dredge/Single-           JAMSTEC  Scientist
                     channel Seismology    
Kana Nagashima       Sediment                 JAMSTEC  Scientist
Takuhei Shiozaki     CTD/Water Sampling       JAMSTEC  Scientist
Miyako Sato          CTD/Water Sampling/      JAMSTEC  Technical Staff
                     Sediment    
Hidetaka Nomaki      Sediment                 JAMSTEC  Scientist
Chisato Yoshikawa    Water Sampling           JAMSTEC  Scientist
Shiki Machida        Dredge                   JAMSTEC  Scientist
Jun Noda             Aerosol/Water sampling   RGU      Assosiate Professor
Shinya Iwasaki       Sediment                 AIST     Researcher
Kanda Chida          Water Sampling           RGU      Graduate Student
Ryo Anma             Dredge/Sediment          Univ of  Lecturer
                                              Tsukuba  
Yuji Orihashi        Dredge                   UT       Assistant Professor
Frank Lamy           Sediment                 AWI      Professor
Helge Wolfgang Arz   Sediment                 IOW      Professor
Leonardo Román       Plankton Net             UdeC     Professor
Castro Cifuentes
Wolfgang Schneider   CTD                      UdeC     Professor
Humberto González    Water Sampling           IDEAL    Professor
Jose Luis Iriarte    FRRF                     IDEAL    Professor
Eduardo Menschel A.  Water Sampling           IDEAL    Technical Staff
Marcelo Gutiérrez    Aerosol/Water Sampling   UdeC     Researcher
Astete               
Alejandro Jose       Sediment                 UdeC     Technical Staff
 Avila Santis
Victor Acuña         Sediment/Plankton Net    UdeC     Technical Staff
Wataru Tokunaga      Chief Technician/ADCP/   NME      Technical Staff 
                     Meteorology/Bathymetry/
                     Geophysics
Satsuki Iijima       Meteorology/Bathymetry/  NME      Technical Staff
                     Geophysics/ADCP        
Koichi Inagaki       Meteorology/Bathymetry/  NME      Technical Staff
                     Geophysics/ADCP       
Yutaro Murakami      Meteorology/Bathymetry/  NME      Technical Staff
                     Geophysics/ADCP        
Toshimasa Nasu       Single-channel           NME      Technical Staff
                     Seismology
Hiroyuki Hayashi     Single-channel           NME      Technical Staff
                     Seismology 
Mitsuteru Kuno       Single-channel           NME      Technical Staff
                     Seismology    
Yusuke Sato          Chief Technician/        MWJ      Technical Staff
                     Sediment/Dredge        
Ei Hatakeyama        Sediment/Dredge          MWJ      Technical Staff
Yuki Miyajima        Sediment/Dredge          MWJ      Technical Staff
Mika Yamaguchi       Sediment/Dredge          MWJ      Technical Staff
Yohei Katayama       Sediment/Dredge          MWJ      Technical Staff
Kazuma Takahashi     Sediment/Dredge          MWJ      Technical Staff
Rei Ito              CTD                      MWJ      Technical Staff
Sonoka Tanihara      Water sampling/Salinity  MWJ      Technical Staff
Atsushi Ono          CO2-system Properties    MWJ      Technical Staff
Tomomi Sone          Water Sampling/          MWJ      Technical Staff
                     Nutrients
Haruka Tamada        TSG/Water Sampling/DO    MWJ      Technical Staff



Leg 3: Punta Arenas – Auckland

Hiroshi Uchida       Chief Scientist          JAMSTEC  Scientist
                     /Density/Isotope of 
                     Water/Sound Velocity
Yuichiro Kumamoto    DO/Water Sampling/       JAMSTEC  Scientist
                     Carbon Isotopes/
                     Beryllium Isotopes
Katsuro Katsumata    SOCCOM Project/          JAMSTEC  Scientist
                     LADCP/Micro Rider
Kosei Sasaoka        Chlorophyll-a/CDOM/      JAMSTEC  Scientist
                     Absorption Coefficient/
                     CO2 Buoy/SOCCOM Project
Etsuro Ono           Calcium/Water Sampling/  JAMSTEC  Scientist 
                     CO2 Buoy

Masahito Shigemitsu  DOM/Water Sampling       JAMSTEC  Scientist
Kenichi Sasaki       CFCs                     JAMSTEC  Scientist
Takuma Miyakawa      Aerosols                 JAMSTEC  Scientist
Taichi Yokokawa      Microbiology             JAMSTEC  Scientist
Michinari Sunamura   Microbiology             UT       Assistant 
                                                       Professor
Momoka Yoshizue      Aerosols                 TUS      Graduate Student
Noriko Iwamatsu      Geochemistry/            RGU      Student
                     Microbiology
Minami Koya          Geochemistry/            RGU      Student
                     Microbiology
Shinya Okumura       Chief technician/        NME      Technical Staff
                     Meteorology/Geophysics/  
                     ADCP/XCTD
Koichi Inagaki       Meteorology/Geophysics/  NME      Technical Staff
                     ADCP/XCTD    
Ryo Kimura           Meteorology/Geophysics/  NME      Technical Staff
                     ADCP/XCTD    
Satoshi Ozawa        Chief Technician/        MWJ      Technical Staff
                     Water Sampling    
Kenichi Katayama     CTD                      MWJ      Technical Staff
Akira Watanabe       Water Sampling/Salinity  MWJ      Technical Staff
Shungo Oshitani      CTD/Argo                 MWJ      Technical Staff
Rio Kobayashi        CTD                      MWJ      Technical Staff
Shinichiro Yokogawa  Nutrients                MWJ      Technical Staff
Tomonori Watai       Total Alkalinity/        MWJ      Technical Staff
                     Underway DIC    
Nagisa Fujiki        DIC/Underway DIC         MWJ      Technical Staff
Ei Hatakeyama        DO/TSG/Chlorophyll-a     MWJ      Technical Staff
Masanori Enoki       DO/TSG/Chlorophyll-a     MWJ      Technical Staff
Hironori Sato        CFCs                     MWJ      Technical Staff
Hiroshi Hoshino      CFCs                     MWJ      Technical Staff
Misato Kuwahara      DO/TSG/Chlorophyll-a     MWJ      Technical Staff
Koki Uda             Water Sampling           MWJ      Technical Staff
Yoshiaki Sato        Nutrients                MWJ      Technical Staff
Rei Ito              CTD/Argo                 MWJ      Technical Staff
Sonoka Tanihara      Salinity                 MWJ      Technical Staff
Atsushi Ono          DIC/Underway DIC         MWJ      Technical Staff
Tomomi Sone          Nutrients                MWJ      Technical Staff
Haruka Tamada        DO/TSG/Chlorophyll-a     MWJ      Technical Staff
Yoshiko Ishikawa     Nutrients                MWJ      Technical Staff
Emi Deguchi          Total Alkalinity         MWJ      Technical Staff
Masahiro Orui        CFCs                     MWJ      Technical Staff



Leg 4: Auckland – Sekinehama

Akihiko Murata       Chief Scientist          JAMSTEC  Scientist
Kazuho Yoshida       Chief Technician/ADCP/   NME      Technical Staff
                     Meteorology/Geophysics    
Ryo Kimura           Meteorology/ADCP/        NME      Technical Staff
                     Geophysics    
Yoshiko Ishikawa     Chief Technician         MWJ      Technical Staff
Masahiro Orui        DO/TSG/Chlorophyll-a     MWJ      Technical Staff
Emi Deguchi          CO2-system Properties    MWJ      Technical Staff
-------------------------------------------------------------------------
JAMSTEC  Japan Agency for Marine-Earth Science and Technology 
NME      Nippon Marine Enterprises, Ltd.
MWJ      Marine Works Japan, Ltd.
RGU      Rakuno Gakuen University
TUS      Tokyo University of Science
UdeC     University of Conception, Chile
IDEAL    Centro de Investigación Dinámica de Ecosystemas Marinos de Altas 
         Latitudes, Universidad Austral de Chile
SIO      Scripps Institution of Oceanography, USA
UW       University of Washington, USA
UT       The University of Tokyo
AIST     National Institute of Advanced Industrial Science and Technology 
AWI      Alfred Wegener Institute, Germany
IOW      Leibniz-Institute for Baltic Sea Research Warnemünde, Germany



4.  List of Principal Investigator and Person in Charge on the Ship
    The principal investigator (PI) and the person in charge responsible 
    for major parameters measured on the cruise are listed in Table 4.1.


Table 4.1. List of principal investigator and person in charge on the 
           ship.

=========================================================================

Item	Principal Investigator	Person in Charge on the Ship
-------------------------------------------------------------------------
Underway

Navigation       Akihiko Murata (JAMSTEC)       Souichiro Sueyoshi (NME) (leg 1)
                 murataa@jamstec.go.jp          Wataru Tokunaga (NME) (leg 2)
                                                Shinya Okumura (NME) (leg 3)
                                                Kazuho Yoshida (NME) (leg 4)
Bathymetry       Natsue Abe (JAMSTEC)           Souichiro Sueyoshi (NME) (leg 1)
                 abenatsu@jamstec.go.jp         Wataru Tokunaga (NME) (leg 2)
                                                Shinya Okumura (NME) (leg 3)
                                                Kazuho Yoshida (NME) (leg 4)
Magnetic Field   Natsue Abe (JAMSTEC)           Souichiro Sueyoshi (NME) (leg 1)
                 abenatsu@jamstec.go.jp         Wataru Tokunaga (NME) (leg 2)
                                                Shinya Okumura (NME) (leg 3)
                                                Kazuho Yoshida (NME) (leg 4)
Gravity          Natsue Abe (JAMSTEC)           Souichiro Sueyoshi (NME) (leg 1)
                 abenatsu@jamstec.go.jp         Wataru Tokunaga (NME) (leg 2)
                                                Shinya Okumura (NME) (leg 3)
                                                Kazuho Yoshida (NME) (leg 4)
Meteorology      Masaki Katsumata (JAMSTEC)     Souichiro Sueyoshi (NME) (leg 1)
                 katsu@jamstec.go.jp            Wataru Tokunaga (NME) (leg 2)
                                                Shinya Okumura (NME) (leg 3)
                                                Kazuho Yoshida (NME) (leg 4)
TSG              Hiroshi Uchida (JAMSTEC)       Hironori Sato (MWJ) (leg 1)
                 huchida@jamtec.go.jp           Haruka Tamada (MWJ) (leg 2)
                                                Masanori Enoki (MWJ) (leg 3)
                                                Masahiro Orui (MWJ) (leg 4)
pCO2             Akihiko Murata (JAMSTEC)
                 murataa@jamstec.go.jp          Tomonori Watai (MWJ) (leg 1) 
                                                Atsushi Ono (MWJ) (leg 2)
                                                Emi Deguchi (MWJ) (legs 3, 4)
Underway DIC     Akihiko Murata (JAMSTEC)       Nagisa Fujiki (MWJ)
                 murataa@jamstec.go.jp  
ADCP             Shinya Kouketsu (JAMSTEC)      Souichiro Sueyoshi (NME) (leg 1)
                 skouketsu@jamstec.go.jp        Wataru Tokunaga (NME) (leg 2)

                                                Shinya Okumura (NME) (leg 3)
                                                Kazuho Yoshida (NME) (leg 4)
Ceilometer       Masaki Katsumata (JAMSTEC)     Souichiro Sueyoshi (NME) (leg 1)
                 katsu@jamstec.go.jp            Wataru Tokunaga (NME) (leg 2)
                                                Shinya Okumura (NME) (leg 3)
                                                Kazuho Yoshida (NME) (leg 4)
Marine Aerosols  Jun Noda (RGU)                 Jun Noda (RGU) (leg 2)
                 jnoda@rakuno.ac.jp             Taichi Yokokawa (JAMSTEC) (leg 3)
Sky Radiometer   Kazuma Aoki (Univ. of Toyama)  none
                 kazuma@sci.u-toyama.ac.jp  
Doppler Radar    Masaki Katsumata (JAMSTEC)     Souichiro Sueyoshi (NME) (leg 1)
                 katsu@jamstec.go.jp            Wataru Tokunaga (NME) (leg 2)
                                                Shinya Okumura (NME) (leg 3)
                                                Kazuho Yoshida (NME) (leg 4)
Lidar            Masaki Katsumata (JAMSTEC)     Masaki Katsumata (JAMSTEC) (leg 1)
                 katsu@jamstec.go.jp
Disdrometer      Masaki Katsumata (JAMSTEC)     Masaki Katsumata (JAMSTEC) (leg 1)
                 katsu@jamstec.go.jp
GNSS Precipit-   Masaki Katsumata (JAMSTEC)     Masaki Katsumata (JAMSTEC) (leg 1)
able Water       katsu@jamstec.go.jp
XCTD             Hiroshi Uchida (JAMSTEC)       Shinya Okumura (NME)
                 huchida@jamstec.go.jp
Radiosonde       Masaki Katsumata (JAMSTEC)     Souichiro Sueyoshi (NME)
                 katsu@jamstec.go.jp
Satellite Image  Masaki Katsumata (JAMSTEC)     Souichiro Sueyoshi (NME) (leg 1)
                 katsu@jamstec.go.jp            Wataru Tokunaga (NME) (leg 2) 
                                                Shinya Okumura (NME) (leg 3) 
                                                Kazuho Yoshida (NME) (leg 4)
MAX-DOAS         Hisahiro Takashima (JAMSTEC)   Takuma Miyakawa (JAMSTEC) (leg 3)
                 hisahiro@jamstec.go.jp
Ozone and CO     Yugo Kanaya (JAMSTEC)          Takuma Miyakawa (JAMSTEC) (leg 3)
                 yugo@jamstec.go.jp
Black Carbon     Fumikazu Taketani (JAMSTEC)    Takuma Miyakawa (JAMSTEC) (leg 3)
Particles        taketani@jamstec.go.jp

Fluorescent      Fumikazu Taketani (JAMSTEC)    Takuma Miyakawa (JAMSTEC) (leg 3)
Aerosol          taketani@jamstec.go.jp
Particles
Aerosol          Takuma Miyakawa (JAMSTEC)      Takuma Miyakawa (JAMSTEC) (leg 3)
Particle Size    miyakawat@jamstec.go.jp
Distribution
Aerosol          Fumikazu Taketani (JAMSTEC)    Takuma Miyakawa (JAMSTEC) (leg 3)
Particle         taketani@jamstec.go.jp
Sampling for 
post-analyses

Station Observation
Single Channel   Natsue Abe (JAMSTEC)           Toshimasa Nasu (NME)
Seismometer      abenatsu@jamstec.go.jp
Sediment Core    Kana Nagashima (JAMSTEC)       Yusuke Sato (MWJ)
                 nagashimak@jamstec.go.jp
Dredge           Natsue Abe (JAMSTEC)           Yusuke Sato (MWJ)
                 abenatsu@jamstec.go.jp
Biological       Leonardo Román Castro
Sample           Cifuentes (UdeC)               Naomi Harada (JAMSTEC)
                 lecastro@oceanografia.udec.cl
Suspended        Humberto González (IDEAL)      Naomi Harada (JAMSTEC)
 Particles       hgonzale@uach.cl
FRRF             Jose Luis Iriarte (IDEAL)      Naomi Harada (JAMSTEC)
                 jiriarte@uach.cl

CTD/O2           Hiroshi Uchida (JAMSTEC)       Rei Ito (MWJ) (leg 2)
                 huchida@jamstec.go.jp          Kenichi Katayama (MWJ) (leg 3)
Salinity         Hiroshi Uchida (JAMSTEC)       Sonoka Tanihara (MWJ)
                 huchida@jamstec.go.jp  
Oxygen           Yuichiro Kumamoto (JAMSTEC)    Hironori Sato (MWJ) (leg 1)
                 kumamoto@jamstec.go.jp         Haruka Tamada (MWJ) (legs 2, 3)
                                                Masahiro Orui (MWJ) (leg 4)
Nutrients        Michio Aoyama (Fukushima U.)   Tomomi Sone (MWJ)
                 r706@ipc.fukushima-u.ac.jp  
Density          Hiroshi Uchida (JAMSTEC)       Takuhei Shiozaki (JAMSTEC) (leg 2)
                 huchida@jamstec.go.jp          Hiroshi Uchida (JAMSTEC) (leg 3)


CFCs/SF6/N2O     Ken’ichi Sasaki (JAMSTEC)      Ken’ichi Sasaki (JAMSTEC)
                 ksasaki@jamstec.go.jp
DIC              Akihiko Murata (JAMSTEC)       Atsushi Ono (MWJ)
                 murataa@jamstec.go.jp
Alkalinity       Akihiko Murata (JAMSTEC)       Atsushi Ono (MWJ) (leg 2)
                 murataa@jamstec.go.jp          Tomonori Watai (MWJ) (leg 3) 
Chlorophyll a    Kosei Sasaoka (JAMSTEC)        Hironori Sato (MWJ) (leg 1)
                 sasaoka@jamstec.go.jp          Takuhei Shiozaki (JAMSTEC) (leg 2) 
                                                Kosei Sasaoka (JAMSTEC) (leg 3) 
                                                Masahiro Orui (MWJ) (leg 4)
CDOM/Absorption  Kosei Sasaoka (JAMSTEC)        Kosei Sasaoka (JAMSTEC) 
 Coefficients    sasaoka@jamstec.go.jp
Calcium          Etsuro Ono (JAMSTEC)           Etsuro Ono (JAMSTEC)
                 onoet@jamstec.go.jp
DOM              Masahiro Shigemitsu (JAMSTEC)  Masahiro Shigemitsu (JAMSTEC)
                 ma-shige@jamstec.go.jp
D14C/d13C        Yuichiro Kumamoto (JAMSTEC)    Yuichiro Kumamoto (JAMSTEC)
                 kumamoto@jamstec.go.jp
Beryllium        Yuichiro Kumamoto (JAMSTEC)    Yuichiro Kumamoto (JAMSTEC)
 Isotopes        kumamoto@jamstec.go.jp
d18O/dD          Hiroshi Uchida (JAMSTEC)       Hiroshi Uchida (JAMSTEC)
                 huchida@jamstec.go.jp
N2O/CH4          Osamu Yoshida (RGU)            Kanta Chida (RGU) (leg 2)
                 yoshida@rakuno.ac.jp           Noriko Iwamatsu (RGU) (leg 3)
Cell Abundance   Michinari Sunamura (UT)        Hidetaka Nomaki (JAMSTEC) (leg 2)
                 sunamura@eps.s.u-tokyo.ac.jp   Michinari Sunamura (UT) (leg 3) 
Microbial        Taichi Yokokawa (JAMSTEC)      Hidetaka Nomaki (JSMTEC) (leg 2)
 Diversity       taichi.yokokawa@jamstec.go.jp  Taichi Yokokawa (JAMSTEC) (leg 3) 
Microbial        Taichi Yokokawa (JAMSTEC)      Taichi Yokokawa (JAMSTEC)(leg 3)
 Carbon Uptake   taichi.yokokawa@jamstec.go.jp
d13C/CH4         Akiko Makabe (JAMSTEC)         Chisato Yoshikawa (JAMSTEC) (leg 2)
                 makabea@jamstec.go.jp          Minami Koya (RGU) (leg 3)
d15N d18O/N2O    Akiko Makabe (JAMSTEC)         Chisato Yoshikawa (JAMSTEC) (leg 2)
                 makabea@jamstec.go.jp          Noriko Iwamatsu (RGU) (leg 3)
d15N d18O/NO3    Chisato Yoshikawa (JAMSTEC)    Chisato Yoshikawa (JAMSTEC) (leg 2)
                 yoshikawac@jamstec.go.jp       Minami Koya (RGU) (leg 3)
d15N/            Chisato Yoshikawa (JAMSTEC)    Chisato Yoshikawa (JAMSTEC) (leg 2)
chlorophyll      yoshikawac@jamstec.go.jp  
LADCP            Shinya Kouketsu (JAMSTEC)      Katsuro Katsumata (JAMSTEC)
                 skouketsu@jamstec.go.jp  
Micro-Rider      Shinya Kouketsu (JAMSTEC)      Katsuro Katsumata (JAMSTEC)
                 skouketsu@jamstec.go.jp  
Sound Velocity   Hiroshi Uchida (JAMSTEC)       Rei Ito (MWJ) (leg 2)
                 huchida@jamstec.go.jp          Hiroshi Uchida (JAMSTEC) (leg 3)
pH               Andrew Dickson (SIO)           Katsuro Katsumata (JAMSTEC)
                 adickson@ucsd.edu  
POC              Susan Becker (SIO)             Kosei Sasaoka (JAMSTEC)
                 sbecker@ucsd.edu
HPLC             Susan Becker (SIO)             Kosei Sasaoka (JAMSTEC)
                 sbecker@ucsd.edu

Floats, Drifters, Moorings
ARGO Float       Shuhei Masuda (JAMSTEC)        Shungo Oshitani (MWJ)
                 smasuda@jamstec.go.jp
SOCCOM BGC       Stephen Riser (UW)             Katsuro Katsumata (JAMSTEC) 
Float            riser@ocean.washington.edu
CO2 Buoy         Akihiko Murata (JAMSTEC)       Akihiko Murata (JAMSTEC) (leg 1)
                 murataa@jamstec.go.jp          Kosei Sasaoka (JAMSTEC) (leg 3)

    JAMSTEC  Japan Agency for Marine-Earth Science and Technology 
    NME       Nippon Marine Enterprises, Ltd.
    MWJ      Marine Works Japan, Ltd.
    RGU      Rakuno Gakuen University
    TUS      Tokyo University of Science
    UdeC     University of Conception, Chile
    IDEAL    Centro de Investigación Dinámica de Ecosystemas Marinos de Altas 
             Latitudes, Universidad Austral de Chile
    SIO      Scripps Institution of Oceanography, USA
    UW       University of Washington, USA
    UT       The University of Tokyo




                            III.  Observation


1.  CRUISE NARRATIVE

    We are now at a transient stage moving from Holocene, which is 
characterized by a stable climate, to a new era: Anthropocene. Impacts 
due to human activities upon surface environment of the earth are 
appearing as catastrophic climate changes and the related collapse of 
ecosystem. In addition, as demonstrated by a series of great earthquakes 
occurred off Chilean coast, off Sumatra and off East Japan, and volcanic 
activities linked to the earthquakes, it can be said that we are now in 
the era, when the interior of the earth or crust is in an active phase. 
Therefore, the present cruise was aimed at clarifying what happened, in 
this Anthropocene, era of great earth changes, in the fields on surface 
environment of the earth and those in the interior of it, focusing 
emergent and confronting issues: 1) Changes in heat and material 
transports by ocean circulation; 2) Detection of progressive ocean 
acidification and the response of marine biology, and relationship 
between biodiversity of marine organisms and changes in living 
environment; 3) Interaction among mantle, ocean ridge, and subduction 
system.

    In the cruise, 8 science plans (see II 2) adopted by the Mirai 
science committee were also conducted together with the main mission: 
Trans South Pacific Project.



2.  CRUISE TRACK AND LOG

Cruise tracks and positions at each day are shown in the following 
figures, separately for respective legs. (see .pdf version)


3.  UNDERWAY OBSERVATION


3.1  Navigation


(1) Personnel		

    Akihiko Murata      JAMSTEC: Principal investigator*1      - leg1,2,3,4 -
    Souichiro Sueyoshi  Nippon Marine Enterprises Ltd., (NME)  - leg1 -
    Yutaro Murakami     NME                                    - leg1,2 -
    Wataru Tokunaga     NME                                    - leg2 -
    Koichi Inagaki      NME                                    - leg2,3 -
    Shinya Okumura      NME                                    - leg3 -
    Kazuho Yoshida      NME                                    - leg4 -
    Ryo Kimura          MIRAI crew / NME                       - leg1,3,4 -
    Masanori Murakami   MIRAI crew                             - leg2,3,4 -
                                     *1 leg1,4: On-board, leg2,3: Not on-board


(2) System description

     Ship’s position and velocity were provided by Navigation System on 
R/V MIRAI. This system integrates GNSS position, Doppler sonar log speed, 
Gyro compass heading and other basic data for navigation. This system 
also distributed ship’s standard time synchronized to GPS time server  
via Network Time Protocol. These data were logged on the network server 
as “SOJ” data every 5 seconds. Sensors for navigation data are listed 
below;

i) GNSS system:

   R/V MIRAI has four GNSS systems, all GNSS positions were offset to 
radar-mast position, datum point. Anytime changeable manually switched as 
to GNSS receiving state.
    a) StarPack-D & Multi-Fix (version 6), Differential GNSS system. 
       Antenna:	Located on compass deck, starboard.
    b) StarPack-D & Multi-Fix (version 6), Differential GNSS system. 
       Antenna:	Located on compass deck, portside.
    c) Standalone GPS system. Receiver:	Trimble SPS751
       Antenna:	Located on navigation deck, starboard.
    d) Standalone GPS system. Receiver:	Trimble SPS751
       Antenna:	Located on navigation deck, portside.
    
ii) Doppler sonar log: 

FURUNO DS-30, which use three acoustic beam for current measurement 
under the hull.

iii) Gyro compass:

TOKYO KEIKI TG-6000, sperry type mechanical gyrocompass.

iv) GPS time server:

SEIKO Precision TS-2540 Time Server, synchronizing to GPS satellites 
every 1 second.


(3) Data period (Time in UTC)
    Leg1: 17:10, 26 Dec. 2016 to 11:00, 17 Jan. 2017
    Leg2: 12:00, 20 Jan. 2017 to 13:00, 05 Feb. 2017
    Leg3: 13:10, 08 Feb. 2017 to 21:00, 04 Mar. 2017
    Leg4: 21:20, 07 Mar. 2017 to 00:00, 28 Mar. 2017



3.2  Swath Bathymetry (MBES, Sub-bottom profiler)

(1) Personnel

    Natsue Abe          JAMSTEC: Principal investigator           - leg2 - 
    Takeshi Matsumoto   Univ. of the Ryukyus: Principal investigator 
                                                  (Not on board)  - leg1,2,3,4 -
    Toshiya Fujiwara    JAMSTEC: Principal investigator 
                                                  (Not on board)  - leg4 -
    Souichiro Sueyoshi  Nippon Marine Enterprises Ltd., (NME)     - leg1 -
    Yutaro Murakami     NME                                       - leg1,2 -
    Wataru Tokunaga     NME                                       - leg2 -
    Koichi Inagaki      NME                                       - leg2,3 -
    Shinya Okumura      NME                                       - leg3 -
    Kazuho Yoshida      NME                                       - leg4 -
    Ryo Kimura          MIRAI crew / NME                          - leg1,3,4 -
    Masanori Murakami   MIRAI crew                                - leg2,3,4 -


(2) Introduction

    R/V MIRAI is equipped with a Multi narrow Beam Echo Sounding system 
(MBES), SEABEAM 3012 (L3 Communications, ELAC Nautik). The objective of 
MBES is collecting continuous bathymetric data along ship’s track to make 
a contribution to geological and geophysical investigations and global 
datasets.

    Also, R/V MIRAI is equipped with a Sub-Bottom Profiler (SBP), 
Bathy2010 (SyQwest). The objective of SBP is collecting sub-bottom data 
along ship’s track.


(3) Data Acquisition

    The “SEABEAM 3012” on R/V MIRAI was used for bathymetry mapping in 
the MR16-09 Leg1 to Leg4 cruises.

    To get accurate sound velocity of water column for ray-path 
correction of acoustic multibeam, we used Surface Sound Velocimeter (SSV) 
data to get the sea surface sound velocity (at 6.62m), and the deeper 
depth sound velocity profiles were calculated by temperature and salinity 
profiles from CTD and XCTD data by the equation in Del Grosso (1974) 
during these cruises. Table 3.2-1 shows system configuration and 
performance of SEABEAM 3012.

    Bathy2010 on R/V MIRAI was used for sub-bottom mapping during the 
Leg2 cruise. Table 3.2-2 shows system configuration and performance of 
Bathy2010 system.
    

Table 3.2-1: SEABEAM 3012 system configuration and performance
----------------------------------------------------------------------
Frequency:             12 kHz
Transmit beam width:   2.0 degree
Transmit power:        4 kW
Transmit pulse length: 2 to 20 msec.
Receive beam width:    1.6 degree
Depth range:           50 to 11,000 m
Number of beams:       301 beams
Beam spacing:          Equi-angle
Swath width:           60 to 150 degrees
Depth accuracy:        < 1 % of water depth (average across the swath)


Table 3.2-2	Bathy2010 System configuration and performance
-------------------------------------------------------------------------
Frequency:             3.5 KHz (FM sweep)
Transmit beam width:   23 degree Transmit pulse length:	0.5 to 50 msec
Strata resolution:     Up to 8 cm with 300 m of bottom penetration 
                       according to bottom type
Depth resolution:      0.1 feet, 0.1 m
Depth accuracy:        ±10 cm to 100 m, ± 0.3% to 6,000 m
Sound velocity:        1,500 m/s (fix)


(4) Data processing of MBES (leg3)

i) Sound velocity correction

    Bathymetry data were corrected with sound velocity profiles 
calculated from the nearest CTD or XCTD data in the distance. The 
equation of Del Grosso (1974) was used for calculating sound velocity. 
The data correction was carried out using the HIPS software version 9.1.4 
(CARIS, Canada)

ii) Editing and Gridding

    Editing for the bathymetry data was carried out using the HIPS. 
Firstly, the bathymetry data during ship’s turning were basically 
deleted, and spike noise of swath data was removed. Then the bathymetry 
data were checked by “BASE surface (resolution: 50 m averaged grid)”.
Finally, all accepted data were exported as XYZ ASCII data (longitude 
[degree], latitude [degree], depth [m]), and converted to 150 m grid data 
using “nearneighbor” utility of GMT (Generic Mapping Tool) software.


Table 3.2-3: Parameters for gridding on “nearneighbor” in GMT
-------------------------------------------------------------
Gridding mesh size:                   150 m
Search radius size:                   150 m 
Minimum number of neighbors for grid: 1
-------------------------------------------------------------


(5) Data Archives

    These data obtained in this cruise will be submitted to the Data 
Management Group (DMG) in JAMSTEC, and will be opened to the public via 
“Data Research System for Whole Cruise Information in JAMSTEC (DARWIN)” 
in JAMSTEC web site.

<http://www.godac.jamstec.go.jp/darwin/e>.


(6)  Remarks (Time in UTC)
     i) The following periods, the MBES observations were carried out. 
        Leg1:  18:46, 28 Dec. 2016 to 06:00, 15 Jan. 2017
        Leg2:  12:11, 21 Jan. 2017 to 14:17, 21 Jan. 2017
               14:32, 21 Jan. 2017 to 00:23, 04 Feb. 2017
        Leg3:  21:00, 10 Feb. 2017 to 06:59, 03 Mar. 2017
        Leg4:  07:03, 09 Mar. 2017 to 09:59, 10 Mar. 2017
               10:00, 15 Mar. 2017 to 08:09, 16 Mar. 2017
               01:50, 18 Mar. 2017 to 03:43, 26 Mar. 2017

    ii) The following periods, the SBP observations were carried out. 
        Leg2:  12:11, 21 Jan. 2017 to 14:17, 21 Jan. 2017
               14:32, 21 Jan. 2017 to 00:23, 04 Feb. 2017

   iii) The following periods, data acquisition of MBES was suspended 
        due to system trouble. 
        Leg4:  07:38, 09 Mar. 2017 to 07:47, 09 Mar. 2017
               04:02, 25 Mar. 2017 to 04:11, 26 Mar. 2017



3.3  Three Component and Total Force Magnetometry

(1) Personnel

    Natsue Abe          JAMSTEC: Principal investigator        - leg2 - 
    Takeshi Matsumoto   Univ. of the Ryukyus: Principal investigator 
                                                (Not on board) - leg1, 2, 3, 4 -
    Toshiya Fujiwara    JAMSTEC: Principal investigator 
                                                (Not on board  - leg4 -
    Souichiro Sueyoshi  Nippon Marine Enterprise Ltd., (NME)   - leg1 -
    Yutaro Murakami     NME                                    - leg1, 2 -
    Wataru Tokunaga     NME                                    - leg2 -
    Koichi Inagaki      NME                                    - leg2, 3 -
    Shinya Okumura      NME                                    - leg3 -
    Kazuho Yoshida      NME                                    - leg4 -
    Ryo Kimura          MIRAI crew / NME                       - leg1, 3, 4 -
    Masanori Murakami   MIRAI crew                             - leg2, 3, 4 -
    

(2) Introduction

    Measurement of magnetic force on the sea surface is required for the 
geophysical investigations of marine magnetic anomaly caused by 
magnetization in the upper crust. We measured geomagnetic vector by using 
a three-component magnetometer and total magnetic force by using a cesium 
magnetometer.

(3) Instruments and Methods

A) Three-component magnetometer

    A shipboard three-component magnetometer system (Tierra Tecnica 
SFG1214) is equipped on-board R/V MIRAI. Three-axes flux-gate sensors 
with ring-cored coils are fixed on the fore mast. Outputs from the 
sensors are digitized by a 20-bit A/D converter (1 nT/LSB), and sampled 
at 8 times per second. Ship's heading, pitch, and roll are measured by 
the Inertial Navigation System (INS) for controlling attitude of a 
Doppler radar. Ship's position and speed data are taken from LAN every 
second.

    The relation between a magnetic-field vector observed on-board, Hob, 
(in the ship's fixed coordinate system) and the geomagnetic field vector, 
F, (in the Earth's fixed coordinate system) is expressed as:
   
    Hob =  A  R  P  Y  F + Hp    (a)

where R, P and Y  are the matrices of rotation due to roll, pitch and 
heading of a ship, respectively. A is a 3 x 3 matrix which represents 
magnetic susceptibility of the ship, and Hp is a magnetic field vector 
produced by a permanent magnetic moment of the ship's body. Rearrangement 
of Eq. (a) makes
  
    B Hob + Hbp =  R  P Y F      (b)

where	=  A-1, and   Hbp = -	Hp. The magnetic field, F, can be obtained 
by measuring  R,  P,  Y and Hob, if   and Hbp are known. Twelve constants 
in B and Hbp can be determined by measuring variation of Hob with R, P 
and  Y  at a place where the geomagnetic field, F, is known.

B) Cesium magnetometer

    We measured the total magnetic force by using a cesium marine 
magnetometer (G-882, Geometrics Inc.) and recorded by G-882 data logger 
(Ver.1.0.0, Clovertech Co.). The G-882 magnetometer uses an optically 
pumped Cesium-vapor atomic resonance system. The sensor fish towed from 
450m to 500 m behind the vessel to minimize the effects of the ship's 
magnetic field. Table 3.3-1 shows system configuration of MIRAI cesium 
magnetometer system.


Table 3.3-1: System configuration of MIRAI cesium magnetometer system
-------------------------------------------------------------------------
    Dynamic operating range: 20,000 to 100,000 nT 
    Absolute accuracy:       < ±2 nT throughout range 
    Setting:                 Cycle rate;     0.1 sec
                             Sensitivity;    0.001265 nT at a 0.1 second 
                                             cycle rate 
                             Sampling rate;  1 sec

(3) Data Archive

    These data obtained in this cruise will be submitted to the Data 
Management Group of JAMSTEC, and will be opened to the public via “Data 
Research System for Whole Cruise Information in JAMSTEC (DARWIN)” in 
JAMSTEC web site.
<http://www.godac.jamstec.go.jp/darwin/e>

(4)  Remarks (Time in UTC)

A) Three component magnetometer
   i) The following periods, observations were carried out. 
      Leg1: 18:45, 28 Dec. 2016 to 06:14, 15 Jan. 2017 
      Leg2: 12:11, 21 Jan. 2017 to 14:17, 21 Jan. 2017
            14:32, 21 Jan. 2017 to 00:23, 04 Feb. 2017
      Leg3: 21:00, 10 Feb. 2017 to 06:59, 03 Mar. 2017
      Leg4: 07:03, 09 Mar. 2017 to 09:59, 10 Mar. 2017
            10:00, 15 Mar. 2017 to 08:09, 16 Mar. 2017
            01:50, 18 Mar. 2017 to 00:00, 28 Mar. 2017

  ii) The following periods, we made a “figure-eight” turn (a pair of 
      clockwise and anti-clockwise rotation) for calibration of the 
      ship’s magnetic effect.
      Leg1: 01:47, 29 Dec. 2016 to 02:08, 29 Dec. 2016 around 26-18N, 174-01W
            22:00, 03 Jan. 2017 to 22:22, 03 Jan. 2017 around 43-08S, 145-11W
            18:00, 11 Jan. 2017 to 18:24. 11 Jan. 2017 around 48-13S, 95-01W
            10:10, 14 Jan. 2017 to 10:42, 14 Jan. 2017 around 45-01S, 80-02W
      Leg2: 20:29, 21 Jan. 2017 to 21:02, 21 Jan. 2017 around 44-21S, 75-33W
            05:35, 31 Jan. 2017 to 05:58, 31 Jan. 2017 around 50-43S, 79-12W
      Leg3: 21:07, 10 Feb. 2017 to 21:41, 10 Feb. 2017 around 59-10S, 73-18W
            00:57, 03 Mar. 2017 to 01:17, 03 Mar. 2017 around 39-46S, 175-20W
      Leg4: 03:00, 18 Mar. 2017 to 03:21, 18 Mar. 2017 around 11-27N, 155-42E
            00:41, 25 Mar. 2017 to 01:09, 25 Mar. 2017 around 38-58N, 144-51E
            20:08, 25 Mar. 2017 to 20:39, 25 Mar. 2017 around 39-52N, 143-10E

 iii) The following period, data were invalid due to trouble of the 
      deck box. 
      Leg3: 10:47, 18 Feb. 2017 to 13:39, 18 Feb. 2017
            20:49, 25 Feb. 2017 to 00:32, 26 Feb. 2017

  iv) The following period, time stamps were delayed 7 seconds.
      Leg3: 13:39, 18 Feb. 2017 to 22:04, 18 Feb. 2017

   v) The following period, data acquisition was suspended due to 
      maintenance. 
      Leg3: 22:04, 18 Feb. 2017 to 22:05, 18 Feb. 2017
            00:32, 26 Feb. 2017 to 00:34, 26 Feb. 2017


B) Cesium magnetometer
   i) The following periods, observations were carried out. 
      Leg1 (Towing distance from stern; 500m):
           01:40, 29 Dec. 2016 to 19:01, 04 Jan. 2017
           19:50, 04 Jan. 2017 to 15:30, 01 Jan. 2017
           16:54, 07 Jan. 2017 to 15:30, 08 Jan. 2017
           16:50, 08 Jan. 2017 to 12:30, 14 Jan. 2017
      Leg2 (Towing distance from stern; 450m):
           20:20, 21 Jan. 2017 to 07:27, 22 Jan. 2017
           13:40, 22 Jan. 2017 to 17:15, 22 Jan. 2017
           18:43, 22 Jan. 2017 to 23:33, 22 Jan. 2017
           02:50, 23 Jan. 2017 to 11:00, 23 Jan. 2017
           03:18, 24 Jan. 2017 to 09:35, 24 Jan. 2017
           02:09, 25 Jan. 2017 to 05:17, 25 Jan. 2017
           11:21, 25 Jan. 2017 to 08:32, 26 Jan. 2017
           20:15, 26 Jan. 2017 to 13:36, 27 Jan. 2017
           21:12, 27 Jan. 2017 to 06:32, 28 Jan. 2017
           21:14, 28 Jan. 2017 to 11:39, 29 Jan. 2017
           16:04, 29 Jan. 2017 to 13:33, 30 Jan. 2017
           20:18, 30 Jan. 2017 to 07:00, 31 Jan. 2017
           20:07, 31 Jan. 2017 to 06:58, 02 Feb. 2017
           13:30, 02 Feb. 2017 to 23:53, 02 Feb. 2017
           04:34, 03 Feb. 2017 to 18:17, 03 Feb. 2017
      Leg3 (Towing distance from stern; 490m)
           19:08, 10 Feb. 2017 to 22:55, 14 Feb. 2017
      Leg4 (Towing distance from stern; 490m)
           01:50, 18 Mar. 2017 to 06:58, 21 Mar. 2017
           07:19, 23 Mar. 2017 to 23:30, 25 Mar. 2017

  ii) The following period, total magnetic data were invalid due to low 
      signal strength. 
      Leg2: 23:29, 25 Jan. 2017
            19:16, 01 Feb. 2017
            19:21, 01 Feb. 2017
            20:02, 01 Feb. 2017


3.4  Sea Surface Gravity

(1) Personnel

    Natsue Abe          JAMSTEC: Principal investigator        - leg2 - 
    Takeshi Matsumoto   Univ. of the Ryukyus:                  - leg1, 2, 3, 4 -
                        Principal investigator (Not on board)
    Toshiya Fujiwara    JAMSTEC:                               - leg4 -
                        Principal investigator (Not on board)
    Souichiro Sueyoshi  Nippon Marine Enterprises Ltd., (NME)  - leg1 -
    Yutaro Murakami     NME                                    - leg1, 2 -
    Wataru Tokunaga     NME                                    - leg2 -
    Koichi Inagaki      NME                                    - leg2, 3 -
    Shinya Okumura      NME                                    - leg3 -
    Kazuho Yoshida      NME                                    - leg4 -
    Ryo Kimura          MIRAI crew / NME                       - leg1, 3, 4 -
    Masanori Murakami   MIRAI crew                             - leg2, 3, 4 -


(2)  Introduction

    The local gravity is an important parameter in geophysics and 
geodesy. We collected gravity data at the sea surface.

(3)  Parameters

    Relative Gravity [CU: Counter Unit] [mGal] = (coef1: 0.9946) * [CU]
QC Filter : 120sec. filtered

(4)  Data Acquisition

    We measured relative gravity using LaCoste and Romberg air-sea 
gravity meter S-116 (Micro-G LaCoste, LLC) in the MR16-09 Leg1 to Leg4 
cruises.

    To convert the relative gravity to absolute one, we measured gravity, 
using portable gravity meter (CG-5, Scintrex), at Shimizu, Punta Arenas 
and Sekinehama as the reference points.

(5)  Preliminary Results

    Absolute gravity table is shown in Table 3.4-1.


Table 3.4-1: Absolute gravity table of the MR16-09 cruise


                                   Absolute   Sea    Ship   Gravity at   S-116
No.    Date     UTC   Port          Gravity   Level  Draft   Sensor *   Gravity
     yy/mm/dd                       [mGal]    [cm]   [cm]     [mGal]     [mGal]
---  --------  -----  ----------  ----------  -----  -----  ----------  --------
#1   16/11/25  06:18  Shimizu     979729.626   128    645    979730.18  12014.81
#2   17/03/28  08:35  Sekinehama  980371.862   200    600    980372.63  12685.04

*: Gravity at Sensor = Absolute Gravity + Sea Level*0.3086/100 + 
   (Draft-530)/100*0.2222


(6)  Data Archive

    These data obtained in this cruise will be submitted to the Data 
Management Group (DMG) in JAMSTEC, and will be opened to the public via 
“Data Research System for Whole Cruise Information in JAMSTEC (DARWIN)” 
in JAMSTEC web site. <http://www.godac.jamstec.go.jp/darwin/e>.

(7)  Remarks (Time in UTC)
     i) The following periods, the observation were carried out. 
        Leg1: 18:46, 28 Dec. 2016 to 06:13, 15 Jan. 2017 
        Leg2: 12:11, 21 Jan. 2017 to 
              14:17, 21 Jan. 2017
              14:32, 21 Jan. 2017 to 00:23, 04 Feb. 2017
        Leg3: 21:00, 10 Feb. 2017 to 06:59, 03 Mar. 2017
        Leg4: 07:03, 09 Mar. 2017 to 09:59, 10 Mar. 2017
              10:00, 15 Mar. 2017 to 08:09, 16 Mar. 2017
              01:50, 18 Mar. 2017 to 00:00, 28 Mar. 2017


    ii) The following period, depth data was available 
        Leg1: 18:47, 28 Dec. 2016 to 05:39, 15 Jan. 2017 
        Leg2: 12:11, 21 Jan. 2017 to 14:17, 21 Jan. 2017
              14:32, 21 Jan. 2017 to 00:23, 04 Feb. 2017
        Leg3: 21:00, 10 Feb. 2017 to 06:59, 03 Mar. 2017
        Leg4: 07:05, 09 Mar. 2017 to 07:37, 09 Mar. 2017
              07:48, 09 Mar. 2017 to 09:59, 10 Mar. 2017
              10:00, 15 Mar. 2017 to 08:09, 16 Mar. 2017
              01:50, 18 Mar. 2017 to 04:01, 25 Mar. 2017
              04:12, 25 Mar. 2017 to 03:43, 26 Mar. 2017


3.5  Surface Meteorological Observations

(1)  Personnel    

     Masaki Katsumata    JAMSTEC: Principal investigator*1     - leg1,2,3,4 -
     Souichiro Sueyoshi  Nippon Marine Enterprise Ltd., (NME)  - leg1 -
     Yutaro Murakami     NME                                   - leg1,2 -
     Wataru Tokunaga     NME                                   - leg2 -
     Koichi Inagaki      NME                                   - leg2,3 -
     Shinya Okumura      NME                                   - leg3 -
     Kazuho Yoshida      NME                                   - leg4 -
     Ryo Kimura          MIRAI crew / NME                      - leg1,3,4 -
     Masanori Murakami   MIRAI crew                            - leg2,3,4 -
                                      *1 leg1:On-board, leg2,3,4:Not on-board


(2)  Objectives

    Surface meteorological parameters are observed as a basic dataset of 
the meteorology. These parameters provide the temporal variation of the 
meteorological condition surrounding the ship.

(3)  Methods

    Surface meteorological parameters were observed from the MR16-09 Leg1 
cruise to Leg4 cruise. In these cruises, we used two systems for the 
observation.

     i) MIRAI Surface Meteorological observation (SMet) system
          Instruments of SMet system are listed in Table  3.5-1 and 
        measured parameters are listed in Table 3.5-2. Data were 
        collected and processed by KOAC-7800 weather data processor made 
        by Koshin-Denki, Japan. The data set consists of 6-second 
        averaged data.

    ii) Shipboard Oceanographic and Atmospheric Radiation (SOAR) 
        measurement system
          SOAR system designed by BNL (Brookhaven National Laboratory, 
        USA) consists of major five parts.

        a) Portable Radiation Package (PRP) designed by BNL – short and 
           long wave downward radiation.
        b) Analog meteorological data sampling with CR1000 logger 
           manufactured by Campbell Inc. Canada – wind, pressure, and 
           rainfall (by a capacitive rain gauge) measurement.
        c) Digital meteorological data sampling from individual sensors - 
           air temperature, relative humidity and rainfall (by ORG 
           (optical rain gauge)) measurement.
        d) Photosynthetically Available Radiation (PAR) sensor 
           manufactured by Biospherical Instruments Inc. (USA) - PAR 
           measurement.
        e) Scientific Computer System (SCS) developed by NOAA (National 
           Oceanic and Atmospheric Administration, USA) – centralized 
           data acquisition and logging of all data sets.

    SCS recorded PRP, CR1000 data, air temperature and relative humidity 
data, ORG data. SCS composed Event data (JamMet) from these data and 
ship’s navigation data every 6 seconds. Instruments and their locations 
are listed in Table 3.5-3 and measured parameters are listed in Table 
3.5-4.

    For the quality control as post processing, we checked the following 
sensors, before and after the cruise.

     i. Young rain gauge (SMet and SOAR)
          Inspect of the linearity of output value from the rain gauge 
        sensor to change input value by adding fixed quantity of test 
        water.

    ii. Barometer (SMet and SOAR)
          Comparison with the portable barometer value, PTB220, VAISALA

   iii. Thermometer (air temperature and relative humidity) ( SMet and 
        SOAR ) Comparison with the portable thermometer value, HM70, 
        VAISALA

(4)  Preliminary results

     Fig. 3.5-1 to Fig. 3.5-3 show the time series of the following 
     parameters; 
       Wind (SOAR)
       Air temperature (SMet) 
       Relative humidity (SMet) 
       Precipitation (SOAR, ORG)
       Short/long wave radiation (SOAR) 
       Pressure (SMet)
       Sea surface temperature (SMet) 
       Significant wave height (SMet)

(5)  Data archives

    These data obtained in these cruises will be submitted to the Data 
Management Group of JAMSTEC, and will be opened to the public via “Data 
Research System for Whole Cruise Information in JAMSTEC (DARWIN)” in 
JAMSTEC web site.

<http://www.godac.jamstec.go.jp/darwin/e>.

(6)  Remarks (Times in UTC)

     i) The following periods, the observation were carried out. 
        Leg1: 18:45, 28 Dec. 2016 to 06:13, 15 Jan. 2017 
        Leg2: 12:11, 21 Jan. 2017 to 
              14:17, 21 Jan. 2017
              14:32, 21 Jan. 2017 to 00:23, 04 Feb. 2017
        Leg3: 21:00, 10 Feb. 2017 to 06:59, 03 Mar. 2017
        Leg4: 07:03, 09 Mar. 2017 to 09:59, 10 Mar. 2017
              10:00, 15 Mar. 2017 to 08:09, 16 Mar. 2017
              01:50, 18 Mar. 2017 to 00:00, 28 Mar. 2017

    ii) The following periods, sea surface temperature of SMet data was 
        available. 
        Leg1: 18:45, 28 Dec. 2016 to 06:13, 15 Jan. 2017
        Leg2: 12:11, 21 Jan. 2017 to 14:17, 21 Jan. 2017
              14:32, 21 Jan. 2017 to 00:23, 04 Feb. 2017
        Leg3: 21:00, 10 Feb. 2017 to 06:59, 03 Mar. 2017
        Leg4: 07:03, 09 Mar. 2017 to 09:59, 10 Mar. 2017
              10:00, 15 Mar. 2017 to 08:09, 16 Mar. 2017
              01:50, 18 Mar. 2017 to 05:30, 26 Mar. 2017

   iii) The following period, downwelling shortwave radiation amount of 
        SOAR was invalid due to a PSP sensor failure.
          about 13:00, 02 Jan. 2017 to 16:11, 07 Jan. 2017

    iv) PSP senor of PRP was replaced to a spare due to a sensor failure 
        at 06:11, 07 Jan. 2017.

     v) The following period, FRSR data acquisition was stopped due to a 
        trouble of heater in the  FRSR sensor.
          08:14, 27 Feb. 2017 to 07:00, 03 Mar. 2017

    vi) The following period, FRSR data acquisition was suspended to 
        prevent the shadow-band from freezing.
          21:25, 12 Feb. 2017 to 23:28, 22 Feb. 2017

   vii) The following periods, downwelling shortwave radiation amount 
        and longwave radiation amount data of SOAR were invalid due to 
        PRP system maintenance.
          21:15, 06 Jan. 2017 to 21:51, 06 Jan. 2017
          15:55, 07 Jan. 2017 to 16:15, 07 Jan. 2017

  viii) The following periods, downwelling shortwave radiation amount 
        and longwave radiation amount data of SOAR were not acquired due 
        to PRP system maintenance.
          21:23, 12 Feb. 2017 to 21:24, 12 Feb. 2017
          23:24, 22 Feb. 2017 to 23:28, 22 Feb. 2017
          07:56, 27 Feb. 2017 to 08:13, 27 Feb. 2017
          17:33, 27 Feb. 2017 to 17:50, 27 Feb. 2017
          23:22, 27 Feb. 2017 to 23:26, 27 Feb. 2017

    ix) The following time, increasing of SMet capacitive rain gauge data 
        were invalid due to transmitting for MF/HF or VHF radio.
          21:27, 06 Jan. 2017
          20:17, 03 Feb. 2017
          20:21, 03 Feb. 2017
          23:20, 18 Mar. 2017
          15:01, 23 Mar. 2017
          15:04, 23 Mar. 2017

     x) The following time, increasing of SMet optical rain gauge data 
        were invalid due to maintenance.
          02:50, 25 Feb. 2017
          20:29, 01 Mar. 2017
          20:30, 01 Mar. 2017
          06:21, 23 Mar. 2017


Table 3.5-1: Instruments and installation locations of MIRAI Surface 
             Meteorological observation system

Sensors                 Type       Manufacturer             Location 
                                                            (altitude from surface)
----------------------  ---------  -----------------------  -------------------------
Anemometer              KE-500     Koshin Denki, Japan      Foremast (24 m)
Tair/RH                 HMP155     Vaisala, Finland
with 43408 Gill aspirated radiation shield R.M. Young, USA  Compass deck (21 m)
                                                            starboard and portside
Thermometer: SST        RFN2-0     Koshin Denki, Japan      4th deck (-1m, inlet -5m)
Barometer               Model-370  Setra System, USA        Captain deck (13 m)
                                                            weather observation room
Capacitive rain gauge   50202      R. M. Young, USA         Compass deck (19 m)
Optical rain gauge      ORG-815DS  Osi, USA                 Compass deck (19 m)
Radiometer (short wave) MS-802     Eko Seiki, Japan         Radar mast (28 m)
Radiometer (long wave)  MS-202     Eko Seiki, Japan         Radar mast (28 m)
Wave height meter       WM-2       Tsurumi-seiki, Japan     Bow (10 m)
                                                            Stern (8m)


Table 3.5-2: Parameters of MIRAI Surface Meteorological observation 
             system


Parameter                                  Units   Remarks
-----------------------------------------  ------  ---------------------
 1  Latitude                               degree
 2  Longitude                              degree
 3  Ship’s speed                           knot    MIRAI log DS-30, Furuno
 4  Ship’s heading                         degree  MIRAI gyro, TG-6000,
                                                   TOKYO-KEIKI
 5  Relative wind speed                    m/s     6sec./10min. averaged
 6  Relative wind direction                degree  6sec./10min. averaged
 7  True wind speed                        m/s     6sec./10min. averaged
 8  True wind direction                    degree  6sec./10min. averaged
 9  Barometric pressure                    hPa     adjusted to sea 
                                                   surface level
                                                   6sec. averaged
10  Air temperature (starboard side)       degC    6sec. averaged
11  Air temperature (port side)            degC    6sec. averaged
12  Dewpoint temperature (starboard side)  degC    6sec. averaged
13  Dewpoint temperature (port side)       degC    6sec. averaged
14  Relative humidity (starboard side)     %       6sec. averaged
15  Relative humidity (port side)          %       6sec. averaged
16  Sea surface temperature                degC    6sec. averaged
17  Rain rate (optical rain gauge)         mm/hr   hourly accumulation
18  Rain rate (capacitive rain gauge)      mm/hr   hourly accumulation
19  Down welling shortwave radiation       W/m2    6sec. averaged
20  Down welling infra-red radiation       W/m2    6sec. averaged
21  Significant wave height (bow)          m       hourly
22  Significant wave height (aft)          m       hourly
23  Significant wave period (bow)          second  hourly
24  Significant wave period (aft)          second  hourly


Table 3.5-3: Instruments and installation locations of SOAR system

Sensors (Meteorological)  Type              Manufacturer     Location (altitude from surface)
------------------------  ----------------  ---------------  --------------------------------
Anemometer                05106             R.M. Young, USA  Foremast (25 m)
Barometer                 PTB210            Vaisala, Finland
with 61002 Gill pressure  port              R.M. Young, USA  Foremast (23 m)
Capacitive rain gauge     50202             R.M. Young, USA  Foremast (24 m)
Tair/RH                   HMP155            Vaisala, Finland
with 43408 Gill aspirated radiation shield  R.M. Young, USA  Foremast (23 m)
Optical rain gauge        ORG-815DR         Osi, USA         Foremast (24 m)

Sensors (PRP)             Type              Manufacturer     Location (altitude from surface)
------------------------  ----------------  ---------------  --------------------------------
Radiometer (short wave)   PSP               Epply Labs, USA  Foremast (25 m)
Radiometer (long wave)    PIR               Epply Labs, USA  Foremast (25 m)
Fast rotating shadowband  radiometer        Yankee, USA      Foremast (25 m)

Sensor (PAR)              Type              Manufacturer     Location (altitude from surface)
------------------------  ----------------  ---------------  --------------------------------
PAR sensor                PUV-510           Biospherical Instruments Inc., USA
                                                             Navigation deck (18m)




Table 3.5-4 Parameters of SOAR system (JamMet)

Parameter                                  Units           Remarks
-----------------------------------------  --------------  --------------
 1  Latitude                               degree
 2  Longitude                              degree
 3  SOG                                    knot
 4  COG                                    degree
 5  Relative wind speed                    m/s
 6  Relative wind direction                degree
 7  Barometric pressure                    hPa
 8  Air temperature                        degC
 9  Relative humidity                      %
10  Rain rate (optical rain gauge)         mm/hr
11  Precipitation (capacitive rain gauge)  mm              reset at 50 mm
12  Down welling shortwave radiation       W/m2
13  Down welling infra-red radiation       W/m2
14  Defuse irradiance                      W/m2
15  PAR                                    microE/cm2/sec


Fig. 3.5-1: Time series of surface meteorological parameters during the 
            MR16-09 Leg1 cruise

Fig. 3.5-2: Time series of surface meteorological parameters during the 
            MR16-09 Leg3 cruise

Fig. 3.5-3: Time series of surface meteorological parameters during the 
            MR16-09 Leg4 cruise



3.6  Thermo-Salinograph and Related Measurements
       May 17, 2017


(1) Personnel

    Hiroshi Uchida (JAMSTEC) 
    Takuhei Shiozaki (JAMSTEC) 
    Kosei Sasaoka (JAMSTEC) 
    Hironori Sato (MWJ)
    Haruka Tamada (MWJ) 
    Masanori Enoki (MWJ) 
    Misato Kuwahara (MWJ) 
    Masahiro Orui (MWJ)

(2) Objectives

    The objective is to collect sea surface salinity, temperature, 
dissolved oxygen, fluorescence and turbidity data continuously along the 
cruise track.

(3) Materials and methods

    The Continuous Sea Surface Water Monitoring System (Marine Works 
Japan Co, Ltd.) has seven sensors and automatically measures salinity, 
temperature, dissolved oxygen, fluorescence, and turbidity in sea surface 
water every one minute. This system is located in the sea surface 
monitoring laboratory and bottom of the ship and connected to shipboard 
LAN system. Measured data along with time and location of the ship were 
displayed on a monitor and stored in a desktop computer. The sea surface 
water was continuously pumped up to the laboratory from about 5 m water 
depth and flowed into the system through a vinyl-chloride pipe. One 
thermometer is located just before the sea water pump at bottom of the 
ship. The flow rate of the surface seawater was controlled to be about 
1.2 L/min. Periods of measurement, maintenance and problems are listed in 
Table 3.6.1.

Software and sensors used in this system are listed below.

i. Software
    Seamoni-kun Ver.1.50


ii. Sensors
    Temperature and conductivity sensor
       Model:                            SBE 45, Sea-Bird Electronics, Inc.
       Serial number:                    4557820-0319
       Pre-cruise calibration:           19 May 2016, Sea-Bird Electronics, Inc.
    Bottom of ship thermometer
       Model:                            SBE 38, Sea-Bird Electronics, Inc.
       Serial number:                    3852788-0457
       Pre-cruise calibration:           8 March 2016, Sea-Bird Electronics, Inc.
    Dissolved oxygen sensor  
       Model:                            RINKO-II, JFE Adantech Co. Ltd.
       Serial number:                    0013
       Pre-cruise calibration:           24 April 2016, JAMSTEC

       Model:                            OPTODE 3835, Aanderaa Data Instruments, AS.
       Serial number:                    1915
       Pre-cruise calibration:           13 May 2015, JAMSTEC
    Fluorometer and turbidity sensor  
       Model:                            C3, Turner Designs, Inc.
       Serial number:                    2300384


Table 3.6.1: Events of the Continuous Sea Surface Water Monitoring System 
             operation.


System Date  System Time                    Event
   [UTC]        [UTC]

                               Leg 1
————————————————————————————————————————————————————————————————————
2016/12/28     18:46     Logging start
2017/01/06  00:11~00:57  Logging stop for filter cleaning
2017/01/15     06:12     Logging stop

                               Leg 2
————————————————————————————————————————————————————————————————————
2017/01/21     12:11     Logging start
2017/01/21  14:18~14:31  All data unavailable
2017/01/28  11:01~11:43  Logging stop for filter cleaning
2017/01/28  12:02~12:03  C3 data unavailable
2017/01/28  19:14~19:15  All data unavailable
2017/01/28  19:15~19:18  C3 data unavailable
2017/01/28  20:15~21:21  Logging stop for entering into
                         Chilean territorial waters
2017/01/31  08:50~08:55  Flow rate for RINKO/Optode was
zero
2017/02/03     23:59     Logging stop

                               Leg 3
————————————————————————————————————————————————————————————————————
2017/02/10     21:15     Logging start
2017/02/16  03:17~04:10  Logging stop for filter cleaning
2017/02/16  08:16~15:46  Flow rate for RINKO/Optode might
                         be small
2017/02/16     20:55~    Flow rate for SBE 45 was unstable
2017/02/17     ~12:07  
2017/02/17  12:08~13:25  Logging stop for filter cleaning
2017/03/03     07:00     Logging stop

                               Leg 4
————————————————————————————————————————————————————————————————————
2017/03/09     07:03     Logging start
2017/03/10     10:00~    Logging stop for entering into foreign EEZs
2017/03/15     ~09:59  
2017/03/16     08:10~    Logging stop for entering into foreign EEZs
2017/03/18     ~01:49  
2017/03/25     23:00     Logging stop



(4) Pre-cruise calibration

   Pre-cruise sensor calibrations for the SBE 45 and SBE 38 were 
performed at Sea-Bird Electronics, Inc.

   Pre-cruise sensor calibrations for the oxygen sensors were performed 
at JAMSTEC. The oxygen sensors were immersed in fresh water in a 1-L 
semi-closed glass vessel, which was immersed in a temperature-controlled 
water bath. Temperature of the water bath was set to 1, 10, 20 and 29ºC. 
Temperature of the fresh water in the vessel was measured by a thermistor 
thermometer (expanded uncertainty of smaller than 0.01ºC, ARO-PR, JFE 
Advantech, Co., Ltd.). At each temperature, the fresh water in the vessel 
was bubbled with standard gases (4, 10, 17 and 25% oxygen consisted of 
the oxygen-nitrogen mixture, whose relative expanded uncertainty is 0.5%) 
for more than 30 minutes to insure saturation. Absolute pressure of the 
vessel headspace was measured by a reference quartz crystal barometer 
(expanded uncertainty of 0.01% of reading) and ranged from about 1040 to 
1070 hPa. The data were averaged over 5 minutes at each calibration point 
(a matrix of 24 points). As a reference, oxygen concentration of the 
fresh water in the calibration vessel was calculated from the oxygen 
concentration of the gases, temperature and absolute pressure at the 
water depth (about 8 cm) of the sensor’s sensing foil as follows:

   O2 (µmol/L) = {1000 × c(T) × (Ap – pH2O)} / 
                                   {0.20946 × 22.3916 × (1013.25 – pH2O)}

where c(T) is the oxygen solubility, Ap is absolute pressure [in hPa], 
and pH2O is the water vapor pressure [in hPa].

    The RINKO was calibrated by the modified Stern-Volmer equation 
slightly modified from a method by Uchida et al. (2010):
    

   O2 ((mol/L) = [(V0 / V)E – 1] / Ksv

where V is raw phase difference, V0 is raw phase difference in the 
absence of oxygen, Ksv is Stern-Volmer constant. The coefficient E 
corrects nonlinearity of the Stern-Volmer equation. The V0 and the Ksv 
are assumed to be functions of temperature as follows.
   
   Ksv = C0 + C1 × T + C2 × T2 
   V0 = 1 + C3 × T
   V = C4 + C5 × Vb

where T is CTD temperature (°C) and Vb is raw output. The oxygen 
concentration is calculated using accurate temperature data from the SBE 
45 instead of temperature data from the RINKO. The calibration 
coefficients were as follows:

   C0 = 5.123682697760924e–3 
   C1 = 2.216599487021134e–4 
   C2 = 4.123214071344090e–6 
   C3 = –6.672929550710492e–4 
   C4 = 2.395966849477748e–2 
   C5 = 0.1951644347447042
   E = 1.5


(5) Data processing and post-cruise calibration

    Data from the Continuous Sea Surface Water Monitoring System were 
obtained at 1 minute intervals. These data were processed as follows. 
Spikes in the temperature and salinity data were removed using a median 
filter with a window of 3 scans (3 minutes) when difference between the 
original data and the median filtered data was larger than 0.1ºC for 
temperature and 0.5 for salinity. Data gaps were linearly interpolated 
when the gap was ≤ 13 minutes. Fluoromete and turbidity data were low-
pass filtered using a median filter with a window of 3 scans (3 minutes) 
to remove spikes. Raw data from the RINKO oxygen sensor, fluorometer and 
turbidity data were low-pass filtered using a Hamming filter with a 
window of 15 scans (15 minutes).

    Salinity (S [PSU]), dissolved oxygen (O [Smol/kg]), and fluorescence 
(Fl [RFU]) data were corrected using the water sampled data. Details of 
the measurement methods are described in Sections 4.8,
4.9 and 4.15 for salinity, dissolved oxygen, and chlorophyll-a, 
respectively. Corrected salinity (Scor), dissolved oxygen (Ocor), and 
estimated chlorophyll a (Chl-a) were calculated from following equations

   Scor [PSU] = c0 + c1 S + c2 t
   Ocor [[mol/kg] = c0 + c1 O + c2 T + c3 t 
   Chl-a [tg/L] = c0 + c1 Fl

where S is practical salinity, t is days from a reference time 
(2016/12/28 18:46 [UTC]), T is temperature in ºC. The best fit sets of 
calibration coefficients (c0~c3) were determined by a least square 
technique to minimize the deviation from the water sampled data. The 
calibration coefficients were listed in Table 3.6.2. Comparisons between 
the Continuous Sea Surface Water Monitoring System data and water sampled 
data are shown in Figs. 3.6.1, 3.6.2 and 3.6.3. The calibration 
coefficients were basically determined for each leg.

    For leg 3, salinity data were shifted at routine maintenance 
(2017/02/16 03:17~04:10). Therefore, the coefficient c0 was changed 
before and after the maintenance.

    For fluorometer data, water sampled data obtained at night [PAR  
(Photosynthetically Available Radiation) < 50 <E/(m2 sec)] were used for 
the calibration, since sensitivity of the fluorometer to chlorophyll a is 
different at nighttime and daytime (Section 2.4 in Uchida et al., 2015). 
Sensitivity of the fluorometer to chlorophyll a may also have regional 
differences. Therefore, the calibration coefficients were change in leg 
2.

    For leg 2, chlorophyll a data obtained at 10 m depths of CTD/water 
sampling casts were also used to calibrate the fluorometer data.


(6) References

Uchida, H., G. C. Johnson, and K. E. McTaggart (2010): CTD oxygen sensor 
    calibration procedures, The GO-SHIP Repeat Hydrography Manual: A 
    collection of expert reports and guidelines, IOCCP Rep., No. 14, ICPO 
    Pub. Ser. No. 134.

Uchida, H., K. Katsumata, and T. Doi (2015): WHP P14S, S04I Revisit Data 
    Book, JASTEC, Yokosuka, 187 pp.




Table 3.6.2: Calibration coefficients for the salinity, dissolved oxygen, 
             and chlorophyll a.
-------------------------------------------------------------------------
             c0          c1             c2          c3
-------------------------------------------------------------------------
Salinity

Leg 1    4.130002e–2  0.9988262    3.781427e–4  
Leg 2   –7.173855e–3  0.9997166    4.655501e–4  
Leg 3   –5.867472e–5  0.9992261    4.396308e–4  (for ~ 2017/02/16 04:00)
        –5.160587e–3  0.9992261    4.396308e–4  (for 2017/02/16 04:00 ~)
Leg 4   –9.554012e–3  0.9994091    2.991207e–4  


Dissolved oxygen

Leg 1  –10.49821      0.9774294    0.4408163    7.269963e–2
Leg 2   –8.846670     0.9636318    0.4452296    0.1050298
Leg 3    3.415634     0.9044650   –5.714148e–3  0.2063646
Leg 4   53.65725      0.8189659   –0.3604695   –0.1434302


Chlorophyll a

Leg 1  0.0            2.615018e–2  (for Fl < 8)
      –0.1071907      3.954902e–2  (for Fl >= 8)
Leg 2 (for ~ 2017/01/25 19:50 or 2017/01/29 19:50 ~)
       0.0            6.722433e–2  (for Fl < 7)
      –0.3219685      0.1132198    (for Fl >= 7)
      (for 2017/01/25 19:50 ~ 2017/01/29 19:50)
       0.0            0.1164691    (for Fl < 8)
      –3.496350       0.5535129    (for Fl >= 8 and Fl < 12)
       2.689773       3.800260e–2  (for Fl >= 12)
Leg 3  0.0            5.766692e–2  (for Fl < 8)
      –0.1513446      7.658499e–2  (for Fl >= 8)
Leg 4  0.0  0.1164691  (for Fl < 8)
      –3.496350       0.5535129    (for Fl >= 8 and Fl < 12)
       2.689773       3.800260e–2  (for Fl >= 12)


Figure 3.6.1: Comparison between TSG salinity (red: before correction, 
              green: after correction) and sampled salinity.

Figure 3.6.2: Comparison between TSG oxygen (red: before correction, 
              green: after correction) and sampled oxygen.

Figure 3.6.3: Comparison between TSG fluorescence and sampled 
              chlorophyll-a. Open dots show that PAR data were greater       
              than 50 FE/(m2 sec). Calibration functions are also shown 
              as lines.



3.7  pCO2

(1) Personnel

    Akihiko Murata (JAMSTEC) 
    Tomonori Watai (MWJ) 
    Atsushi Ono (MWJ)
    Emi Deguchi (MWJ) 
    Nagisa Fujiki (MWJ)


(2) Objective

    Concentrations of CO2 in the atmosphere are now increasing at a rate 
of about 2.0 ppmv y–1 owing to human activities such as burning of fossil 
fuels, deforestation, and cement production. It is an urgent task to 
estimate as accurately as possible the absorption capacity of the oceans 
against the increased atmospheric CO2, and to clarify the mechanism of 
the CO2 absorption, because the magnitude of the anticipated global 
warming depends on the levels of CO2 in the atmosphere, and because the 
ocean currently absorbs 1/3 of the 6 Gt of carbon emitted into the 
atmosphere each year by human activities.

    In this cruise, we measured pCO2 (partial pressure of CO2) in the 
atmosphere and surface seawater continuously along cruise tracks in the 
South Pacific in order to quantify how much CO2 is absorbed in the 
region.


(3) Apparatus

    Concentrations of CO2 in the atmosphere and the sea surface were 
measured continuously during the cruise using an automated system with a 
non-dispersive infrared (NDIR) analyzer (Li-COR LI-7000). The automated 
system (Nippon ANS) was operated by about one and a half hour cycle. In 
one cycle, standard gasses, marine air and an air in a headspace of an 
equilibrator were analyzed subsequently. The nominal concentrations of 
the standard gas were 230, 290, 370 and 430 ppmv. The standard gases  
will  be calibrated after the cruise.

    The marine air taken from the bow was introduced into the NDIR by 
passing through a mass flow controller, which controlled the air flow 
rate at about 0.6 – 0.8 L/min, a cooling unit, a perma-pure dryer (GL 
Sciences Inc.) and a desiccant holder containing Mg(ClO4)2.

    A fixed volume of the marine air taken from the bow was equilibrated 
with a stream of seawater that flowed at a rate of 4.0 – 5.0 L/min in the 
equilibrator. The air in the equilibrator was circulated with a pump at 
0.7-0.8L/min in a closed loop passing through two cooling units, a perma-
pure dryer (GL   Science Inc.) and a desiccant holder containing 
Mg(ClO4)2.


(4) Results

    Concentrations of CO2 (xCO2) of marine air and surface seawater are 
shown in Fig. 3.7.1, together with SST.

Fig. 3.7.1: Preliminary results of concentrations of CO2 (xCO2) in 
            atmosphere (green) and  surface seawater (blue), and SST 
            (red) observed during (a) leg 1, (b) leg 3, and (c) leg 4 of 
            MR16-09.


3.8  Satellite Image Acquisition


(1) Personnel

    Masaki Katsumata    JAMSTEC: Principal investigator*1     - leg1,2,3,4 -
    Souichiro Sueyoshi  Nippon Marine Enterprise Ltd., (NME)  - leg1 -
    Yutaro Murakami     NME                                   - leg1,2 -
    Wataru Tokunaga     NME                                   - leg2 -
    Koichi Inagaki      NME                                   - leg2,3 -
    Shinya Okumura      NME                                   - leg3 -
    Kazuho Yoshida      NME                                   - leg4 -
    Ryo Kimura          MIRAI crew / NME                      - leg1,3,4 -
    Masanori Murakami   MIRAI crew                            - leg2,3,4 -
                                 *1 leg1: On-board, leg2,3,4: Not on-board


(2) Objectives

    The objectives are to collect cloud data in a high spatial resolution 
mode from the Advance Very High Resolution Radiometer (AVHRR) on the NOAA 
and MetOp polar orbiting satellites, and to verify the data from Doppler 
radar on board.


(3) Methods

    We received the down link High Resolution Picture Transmission (HRPT) 
signal from satellites, which passed over the area around the R/V MIRAI. 
We processed the HRPT signal with the in-flight calibration and computed 
the brightness temperature. A cloud image map around the R/V MIRAI was 
made from the data for each pass of satellites.

    We received and processed polar orbiting satellites data from the 
MR16-09 Leg1 cruise to Leg4 cruise.


(4) Data archives

    These data obtained in these cruises will be submitted to the Data 
Management Group of JAMSTEC, and will be opened to the public via “Data 
Research System for Whole Cruise Information in JAMSTEC (DARWIN)” in 
JAMSTEC web site.
<http://www.godac.jamstec.go.jp/darwin/e>.


3.9  ADCP


(1) Personnel

    Shinya Kouketsu     JAMSTEC:                               - leg1,2,3,4 -
                        Principal Investigator(Not on board)  
    Wolfgang Schneider  Univ. of Concepcion:                   - leg2 -
                        Principal Investigator 
    Souichiro Sueyoshi  Nippon Marine Enterprises Ltd., (NME)  - leg1 -
    Yutaro Murakami     NME                                    - leg1,2 -
    Wataru Tokunaga     NME                                    - leg2 -
    Koichi Inagaki      NME                                    - leg2,3 -
    Shinya Okumura      NME                                    - leg3 -
    Kazuho Yoshida      NME                                    - leg4 -
    Ryo Kimura          MIRAI crew / NME                       - leg1,3,4 -
    Masanori Murakami   MIRAI crew                             - leg2,3,4 -


(2) Objective
  
    To obtain continuous measurement of the current profile along the ship’s 
track.


(3) Methods

    Upper ocean current measurements were made in the MR16-09 Leg1 to 
Leg4 cruises, using the hull-mounted Acoustic Doppler Current Profiler 
(ADCP) system. For most of its operation the instrument was configured 
for water-tracking mode. Bottom-tracking mode, interleaved bottom-ping 
with water-ping, was made to get the calibration data for evaluating 
transducer misalignment angle in the shallow water. The system consists 
of following components;

1) R/V MIRAI has installed vessel-mount ADCP (acoustic frequency 76.8 
   kHz “Ocean Surveyor”, Teledyne RD Instruments). It has a phased-array 
   transducer with single ceramic assembly and creates 4 acoustic beams 
   electronically. We mounted the transducer head rotated to a ship-
   relative angle of 45 degrees azimuth from the keel.
2) For heading source, we use ship’s gyro compass (TOKYO KEIKI, 
   Japan), continuously providing heading to the ADCP system directory. 
   Also we have Inertial Navigation System (PHINS, IXBLUE) which provide 
   high-precision heading and attitude information are stored in “.N2R” 
   data files.
3) Differential GNSS system (Multi-Fix, Fugro, Netherlands) providing 
   precise ship’s position fixes.
4) We used VmDas version 1.46.5 (TRDI) for data acquisition.
5) To synchronize time stamp of pinging with GPS time, the clock of 
   the logging computer is adjusted to GPS time every 8 minutes.
6) The sound speed at the transducer does affect the vertical bin 
   mapping and vertical velocity measurement, is calculated from  
   temperature, salinity (constant value; 35.0 psu) and depth (6.5 m; 
   transducer depth) by equation in Medwin (1975).

    Data was configured for 8-m intervals starting 23-m below the 
surface. Every ping was recorded as raw ensemble data (.ENR). Major 
parameters for the measurement (Direct Command) are shown in Table 3.9-1.


(4) Preliminary results

    Fig.3.9-1 to 3.9-4 show surface current profile along the ship’s 
track, averaged four depth cells from 6th to 10th, about 55m to 103 m 
with 30 minutes average.


(5) Data archive

    These data obtained in these cruises will be submitted to the Data 
Management Group of JAMSTEC, and will be opened to the public via “Data 
Research System for Whole Cruise Information in JAMSTEC (DARWIN)” in 
JAMSTEC web site.
<http://www.godac.jamstec.go.jp/darwin/e>.


(6) Remarks (Time in UTC)

i) The following periods, the observations were carried out.

Leg1: 18:46, 28 Dec. 2016 to 06:00, 15 Jan. 2017
Leg2: 12:11, 21 Jan. 2017 to 14:174, 21 Feb. 2017
      14:32, 21 Jan. 2017 to 00:23, 04 Feb. 2017
Leg3: 21:00, 10 Feb. 2017 to 06:59, 03 Mar. 2017
Leg4: 07:03, 09 Mar. 2017 to 09:59, 10 Mar. 2017
      10:00, 15 Mar. 2017 to 08:09, 16 Mar. 2017
      01:50, 18 Mar. 2017 to 00:00, 28 Mar. 2017


ii) The following period, Temperature and Sound Velocity data were 
constant (0.0°C and 1449m/s) due to system trouble.

      02:55, 16 Feb. 2017 to 02:19, 19 Feb. 2017



Table 3.9-1: Major parameters

Bottom-Track Commands

BP = 001 Pings per Ensemble (almost less than 1300m depth) 

      Leg1: None
      Leg2: 22:19, 21 Jan. 2017 to 06:00, 22 Jan. 2017
            21:43, 26 Jan. 2017 to 23:19, 26 Jan. 2017
            23:02, 28 Jan. 2017 to 01:25, 29 Jan. 2017
            22:55, 03 Feb. 2017 to 23:56, 03 Feb. 2017
      Leg3: None
      Leg4: 07:58, 09 Mar. 2017 to 18:34, 09 Mar. 2017
            22:19, 25 Mar. 2017 to 00:00, 28 Mar. 2017

Environmental Sensor Commands

EA = +04500    Heading Alignment (1/100 deg) 
EB = +00000    Heading Bias (1/100 deg)
ED = 00065     Transducer Depth (0 - 65535 dm)
EF = +001      Pitch/Roll Divisor/Multiplier (pos/neg) [1/99 - 99] 
EH = 00000     Heading (1/100 deg)
ES = 35        Salinity (0-40 pp thousand)
EX = 00000     Coord Transform (Xform:Type; Tilts; 3Bm; Map) 
EZ = 10200010  Sensor Source (C; D; H; P; R; S; T; U)
        C (1): Sound velocity calculates using ED, ES, ET (temp.) 
        D (0): Manual ED
        H (2): External synchro
        P (0), R (0): Manual EP, ER (0 degree) 
        S (0): Manual ES
        T (1): Internal transducer sensor 
        U (0): Manual EU

Timing Commands

TE = 00:00:02.00  Time per Ensemble (hrs:min:sec.sec/100) 
TP = 00:02.00     Time per Ping (min:sec.sec/100)

Water-Track Commands

WA = 255          False Target Threshold (Max) (0-255 count)
WB = 1            Mode 1 Bandwidth Control (0=Wid, 1=Med, 2=Nar) 
WC = 120          Low Correlation Threshold (0-255)
WD = 111 100 000  Data Out (V; C; A; PG; St; Vsum; Vsum^2;#G;P0)
WE = 1000         Error Velocity Threshold (0-5000 mm/s) 
WF = 0800         Blank After Transmit (cm)
WG = 001          Percent Good Minimum (0-100%) 
WI = 0            Clip Data Past Bottom (0 = OFF, 1 = ON) 
WJ = 1            Rcvr Gain Select (0 = Low, 1 = High)
WM = 1            Profiling Mode (1-8)
WN = 100          Number of depth cells (1-128)
WP = 00001        Pings per Ensemble (0-16384) 
WS= 0800          Depth Cell Size (cm)
WT = 000          Transmit Length (cm) [0 = Bin Length]
WV = 0390         Mode 1 Ambiguity Velocity (cm/s radial)


Fig 3.9-1: Current profile along the ship’s track, about 55m to 103m 
           depth, averaged every 30 minutes (Leg1).

Fig 3.9-2: Current profile along the ship’s track, about 55m to 103m 
           depth, averaged every 30 minutes (Leg2).

Fig 3.9-3: Current profile along the ship’s track, about 55m to 103m 
           depth, averaged every 30 minutes (Leg3).

Fig 3.9-4: Current profile along the ship’s track, about 55m to 103m 
           depth, averaged every 30 minutes (Leg4).



3.10  Ceilometer observation


(1) Personnel	

    Masaki Katsumata    JAMSTEC: Principal investigator*1     - leg1,2,3,4 -
    Souichiro Sueyoshi  Nippon Marine Enterprise Ltd., (NME)  - leg1 -
    Yutaro Murakami     NME                                   - leg1,2 -
    Wataru Tokunaga     NME                                   - leg2 -
    Koichi Inagaki      NME                                   - leg2,3 -
    Shinya Okumura      NME                                   - leg3 -
    Kazuho Yoshida      NME                                   - leg4 -
    Ryo Kimura          MIRAI crew / NME                      - leg1,3,4 -
    Masanori Murakami   MIRAI crew                            - leg2,3,4 -
                                 *1 leg1: On-board, leg2,3,4: Not on-board


(2) Objectives

    The information of cloud base height and the liquid water amount 
around cloud base is important to understand the process on formation of 
the cloud. As one of the methods to measure them, the ceilometer 
observation was carried out.


(3) Parameters

1. Cloud base height [m].
2. Backscatter profile, sensitivity and range normalized at 10 m 
   resolution.
3. Estimated cloud amount [oktas] and height [m]; Sky Condition 
   Algorithm.


(4) Methods

    We measured cloud base height and backscatter profile using 
ceilometer (CL51, VAISALA, Finland). Major parameters for the measurement 
configuration are shown in Table 3.10-1;


Table 3.10-1: Major parameters

Laser source:                    Indium Gallium Arsenide (InGaAs) Diode 
Transmitting center wavelength:  910±10 nm at 25 degC
Transmitting average power:      19.5 mW
Repetition rate:                 6.5 kHz
Detector:                        Silicon avalanche photodiode (APD)
Responsibility at 905 nm:        65 A/W
Cloud detection range:           0 ~ 13 km
Measurement range:               0 ~ 15 km
Resolution:                      10 meter in full range
Sampling rate:                   36 sec
Sky Condition:                   Cloudiness in octas (0 ~ 9)
                (0:Sky Clear, 1:Few, 3:Scattered, 5-7:Broken, 8:Overcast, 
                 9:Vertical Visibility)


On the archive dataset, cloud base height and backscatter profile are 
recorded with the resolution of 10 m (33 ft).


(5) Preliminary results

    Fig.3.10-1 to Fig.3.10-3 show the time series of 1st, 2nd and 3rd 
lowest cloud base height during these cruises.


(6) Data archives

    These data obtained in these cruises will be submitted to the Data 
Management Group of JAMSTEC, and will be opened to the public via “Data 
Research System for Whole Cruise Information in JAMSTEC (DARWIN)” in 
JAMSTEC web site.
<http://www.godac.jamstec.go.jp/darwin/e>.


(7) Remarks (Times in UTC)
i) The following periods, the observation were carried out. 
       Leg1: 18:45, 28 Dec. 2016 to 06:13, 15 Jan. 2017
       Leg2: 12:11, 21 Jan. 2017 to 14:174, 21 Feb. 2017
             14:32, 21 Jan. 2017 to 00:23, 04 Feb. 2017
       Leg3: 21:00, 10 Feb. 2017 to 06:59, 03 Mar. 2017
       Leg4: 07:03, 09 Mar. 2017 to 09:59, 10 Mar. 2017
             10:00, 15 Mar. 2017 to 08:09, 16 Mar. 2017
             01:50, 18 Mar. 2017 to 00:00, 28 Mar. 2017

ii) The following time, the window was cleaned. 
       Leg1: 04:58, 29 Dec. 2016
             01:55, 04 Jan. 2017
             21:03, 11 Jan. 2017
       Leg2: 11:51, 27 Jan. 2017
             00:57, 03 Feb. 2017
       Leg3: 01:18, 14 Feb. 2017
             22:13, 21 Feb. 2017
             02:48, 25 Feb. 2017
             20:26, 01 Mar. 2017
       Leg4: 02:12, 15 Mar. 2017
             06:21, 23 Mar. 2017


Fig. 3.10-1: 1st, 2nd and 3rd lowest cloud base height during MR16-09 
             Leg1 cruise.

Fig. 3.10-2: 1st, 2nd and 3rd lowest cloud base height during MR16-09 
             Leg3 cruise.

Fig. 3.10-3: 1st, 2nd and 3rd lowest cloud base height during MR16-09 
             Leg4 cruise.



3.11  Marine Aerosols


(1) Personnel

    Jun Noda           Rakuno Gakuen University  - on board
    Marcelo Gutiérrez  University of Concepcion  - on board
    Osamu Yoshida      Rakuno Gakuen University  - not on board


(2) Objectives
• To investigate chemical and biological properties of aerosols in a 
  marine environment
• To investigate micron-size particles number and size distribution
• To investigate a biological linkage between marine aerosol and seawater


(3) Parameters
• Chemical and biological compositions of marine aerosols
• Particle number concentration
• Comparison of biological diversities in ocean water and marine aerosols


(4) Instruments and methods 
(4-1) Marine aerosol collection
(4-1-1) Aerosol collection with NILU filter unit with NL PM2.5 cut off 
        impactor

    The NILU (Norwegian Institute for Air Research, Norway) 2-stage 
filter holder unit with NL PM2.5 impactor (Tokyo Dylec, Japan) was 
equipped with two PTFE (Polytetrafluoroethylene) membrane filters with 
pore size of 0.8 µm (Top:e=47 with 20 mm hole in the center and 
Bottom:=47mm) to collect two size ranges of marine aerosols. The 
sampling unit was mounted on the roof section of navigation deck close to 
a high volume sampler. The Filter units withdraw 4L/min. by a vacuum pump 
and a Mass Flow Controller (MFC) to maintain the flow rate. Also, the MFC 
counted the total volume of air passed through the filter unit. The 
sampling intervals were ca. 24 hr during the leg 2. and ca. 24 hr to 7.8 
days during the leg 3 (detail information are shown on the Table 3.11-1 
and 3.11-2 Logs of marine aerosol sampling on PTFE membrane filters).

(4-2) BioSampler

    The BioSampler (SKC, USA) was employed to collect marine aerosols 
from the right side of the upper deck. The BioSampler has three critical 
orifice nozzles with designated flow direction to create a vortex inside 
the collection liquid of 15 ml. Also the nozzles act as critical orifice 
to maintain the flow rate through the nozzle at ca. 10 L/min. At initial 
trial, sampling duration was ca. 30 min during the surface water sampling 
period, which was strictly limited to this period to minimize the 
workload for the ship crews. The Biosampler has a greater capacity to 
collect biological aerosols than the NILU filter method; we expect to 
have much more DNA and other biogenic substances in the collection 
liquid.

    After the initial trial, there was a discussion about possible 
prolonged sampling period to ensure more than adequate amount of DNA with 
onboard Chilean Scientists. After the consultation with the chief 
scientist and the Chilean side chief scientist, we have decided to 
conduct sampling of marine aerosols with increased amount of collection 
liquid and prolonged sampling duration (detail information are shown in 
the Table 3.11-3. Logs of marine aerosol sampling with BioSampler).

(4-3) Particle number concentration and size distribution

    The particle number concentration and size distributions were planned 
to measure with Optical Particle Sizer (OPS3330). However, the instrument 
was not functioning during the leg 2, thus none of the data sets was 
obtained by the OPS 3330.

(5) Station list or Observation log


Table 3.11-1: Log of marine aerosol sampling on PTFE membrane filters

                        Date Collected                Latitude           Longitude
 On board ID    ———————————————————————————————  ——————————————————  —————————————————
                yyyy  MM  DD  hh:mm:ss  UTC/JST  Deg.    Min.   N/S  Deg.    Min.   E/W
——————————————  ————  ——  ——  ————————  ———————  ————  ———————  ———  ————  ———————  ———
MR1609-Tel-001  2017  01  21   13:35      UTC     44   17.3760   S    75   35.4831   W

MR1609-Tel-002  2017  01  22   13:35      UTC     46   03.9138   S    75   41.4622   W
                2017  01  22   13:40      UTC     46   03.5267   S    75   41.4220   W

MR1609-Tel-003  2017  01  23  13:40       UTC     46   04.2428   S    76   32.01270  W
                2017  01  23  13:45       UTC     46   04.2314   S    76   32.06210  W

MR1609-Tel-004  2017  01  24  13:35       UTC     46   10.7887   S    76   17.68200  W
                2017  01  24  13:38       UTC     46   10.7960   S    76   17.67470  W

MR1609-Tel-005  2017  01  25  13:37       UTC     46   17.7684   S    76   49.21520  W
                2017  01  25  13:41       UTC     46   17.9294   S    76   49.97760  W

MR1609-Tel-006  2017  01  26  13:40       UTC     47   46.0578   S    76   24.98860  W
                2017  01  26  13:43       UTC     47   46.0370   S    76   24.93060  W

MR1609-Tel-007  2017  01  27  13:38       UTC     46   29.5537   S    77   17.37910  W
                2017  01  27  13:46       UTC     46   29.1496   S    77   17.35700  W

MR1609-Tel-008  2017  01  28  13:42       UTC     47   47.6478   S    76   02.48930  W
                2017  01  28  13:45       UTC     47   47.7123   S    76   02.57160  W

MR1609-Tel-009  2017  01  29  13:52       UTC     48   23.2475   S    76   28.13850  W
                2017  01  29  13:55       UTC     48   23.2536   S    76   28.16440  W

MR1609-Tel-010  2017  01  30  13:50       UTC     50   49.0803   S    79   00.68380  W
                2017  01  30  13:54       UTC     50   48.8939   S    79   01.44170  W

MR1609-Tel-011  2017  01  31  13:45       UTC     50   48.3214   S    79   07.15040  W
                2017  01  31  13:49       UTC     50   48.3250   S    79   07.16240  W

MR1609-Tel-012  2017  02  01  13:49       UTC     53   16.2706   S    76   12.13750  W
                2017  02  01  13:55       UTC     53   17.2478   S    76   10.76840  W

MR1609-Tel-013  2017  02  02  13:48       UTC     54   20.4553   S    74   39.49880  W
                2017  02  02  13:50       UTC     54   20.1487   S    74   39.83210  W
                2017  02  03  19:48       UTC     52   19.0665   S    75   56.76900  W


Table 3.11-2: Logs of marine aerosol sampling on PTFE membrane filters

                        Date Collected                Latitude           Longitude
 On board ID    ———————————————————————————————  ——————————————————  —————————————————
                yyyy  MM  DD  hh:mm:ss  UTC/JST  Deg.    Min.   N/S  Deg.    Min.   E/W
——————————————  ————  ——  ——  ————————  ———————  ————  ———————  ———  ————  ———————  ———
MR1609-Tel-022  2017  02  11  19:39       UTC     61   45.6669   S    80   24.0890   W

MR1609-Tel-023  2017  02  16   0:03       UTC     66   55.9992   S   125   14.9269   W
                2017  02  16   0:03       UTC     66   55.9992   S   125   14.9269   W

MR1609-Tel-024  2017  02  17   0:04       UTC     65   38.8478   S   125   57.4883   W
                2017  02  17   0:04       UTC     65   38.8478   S   125   57.4883   W

MR1609-Tel-025  2017  02  17  23:57       UTC     63   11.8680   S   126   00.6343   W
                2017  02  17  23:57       UTC     63   11.8680   S   126   00.6343   W

MR1609-Tel-026  2017  02  18  23:53       UTC     62   20.3533   S   126   06.4242   W
                2017  02  18  23:53       UTC     62   20.3533   S   126   06.4242   W

MR1609-Tel-027  2017  02  20   0:06       UTC     60   00.8449   S   125   58.5689   W
                2017  02  20   0:06       UTC     60   00.8449   S   125   58.5689   W

MR1609-Tel-028  2017  02  20  23:53       UTC     57   49.5030   S   125   59.9270   W
                2017  02  20  23:53       UTC     57   49.5030   S   125   59.9270   W

MR1609-Tel-029  2017  02  22   0:21       UTC     55   01.0794   S   125   58.5795   W
                2017  02  22   0:21       UTC     55   01.0794   S   125   58.5795   W

MR1609-Tel-030  2017  02  23   0:00       UTC     53   01.1720   S   126   00.1355   W
                2017  02  23   0:00       UTC     53   01.1720   S   126   00.1355   W
                2017  03  02  18:36       UTC         


Table 3.11-3: Logs of marine aerosol sampling with BioSampler

                        Date Collected                Latitude           Longitude
 On board ID    ———————————————————————————————  ——————————————————  —————————————————
                yyyy  MM  DD  hh:mm:ss  UTC/JST  Deg.    Min.   N/S  Deg.    Min.   E/W
——————————————  ————  ——  ——  ————————  ———————  ————  ———————  ———  ————  ———————  ———
MR1609-Tel-014  2017  01  24   1:23       UTC     46   10.1910   S    76   17.28530  W

MR1609-Tel-015  2017  01  24   1:53       UTC     46   10.1935   S    76   17.28690  W
                2017  01  24   1:55       UTC     46   10.1935   S    76   17.28690  W

MR1609-Tel-016  2017  01  24   2:15       UTC     46   10.1948   S    76   17.28910  W
                2017  01  26   3:10       UTC     47   49.3219   S    76   36.35760  W

MR1609-Tel-017  2017  01  26   7:36       UTC     47   45.9932   S    76   12.48200  W
                2017  01  27  20:00       UTC     46   24.8541   S    77   18.93600  W

MR1609-Tel-018  2017  01  28  14:55       UTC     47   47.9249   S    76   02.09790  W
                2017  01  28  22:23       UTC     47   57.3677   S    76   01.44350  W

MR1609-Tel-019  2017  01  29  14:55       UTC     48   23.8232   S    76   28.78540  W
                2017  01  30  14:15       UTC     50   48.5986   S    79   04.32910  W

MR1609-Tel-020  2017  01  31  12:52       UTC     50   48.3102   S    79   06.99480  W
                2017  01  31  19:00       UTC     50   48.3240   S    79   07.17860  W

MR1609-Tel-021  2017  02  02  10:14       UTC     54   20.1017   S    74   38.17960  W
                2017  02  02  18:43       UTC     53   46.4482   S    74   32.70620  W
                2017  02  03  19:59       UTC     52   19.0874   S    75   56.70720  W



(6) Plan of analyses

(6-1) Chemical analysis

    In marine aerosols, the amount of organic fraction has clear 
dependency with the abundance of chlorophyll concentrations (O’Dowd et 
al., 2004). There have been several efforts to use different saccharides 
and other organic components as a tracer to link the primary production 
in seawater (Russel et al., 2010, Miyazaki et al., 2016). In this 
investigation, we would like to analyze the series of saccharides and 
fatty acids and some inorganic salts to characterize the marine aerosols 
from the southern Pacific Ocean.

(6-2) Biological analysis

    A contribution of marine biological materials on the surface layer 
has gained much of attention because of the effective ice-nucleating 
properties (Wilson et al., 2015). From the field and laboratory 
measurements, Wilson et al., proposed the components from diatom such as 
Thalassiosira psudonana may start the ice nucleation at higher 
temperature than homogenous nucleation of water at much lower temperature 
of – 48.3 °C (Willson, et al., 2015, Speedy and Angell, 1976). Thus, 
understanding the biological components such as plankton in marine flora 
and marine aerosol is important. For the marine aerosol analysis, the 
collected particulate matters on the Teflon filters will be extracted and 
analyzed for microbe diversity by metagenomic analysis. Polymerase chain 
reaction (PCR) amplification to prepare template DNA for pyrosequencing 
will be carried out. A data analysis will be performed on each read 
sequence using previously developed computational tools with some 
modifications (Nakamura et al., 2008, 2009). In order to have 
comprehensive metagenomics analyses scheme for marine aerosols and 
seawater, the analysis method found in Nunoura et al. (2015) will also be 
taken into consideration.

(6-3) Biological analysis by Chilean scientist

    The Chilean scientist plans to extract and quantify DNA from filters 
containing suspended material collected by BioSampler. Template DNA will 
be subjected to PCR amplification using general primers to study fungal 
diversity. If the outcome of these steps will be successful, a further 
step to do a molecular fingerprint analysis (DGGE, Denaturing Gradient 
Gel Electrophoresis) will be carried out to compare biological 
communities collected from BioSampler and surface seawaters. Finally, a 
deep taxonomic analysis of fungal communities will be performed according 
to DGGE results.


(7) Expected outcome

    From this investigation, we expect to get some understanding of the 
linkage between microbial flora in seawater and marine aerosols. The 
previous studies by Russel et al. (2010) and Wilson et al. (2015) clearly 
indicated that chemical substances produced by the marine flora including 
plankton might play a particular role to attribute the type of marine 
aerosols. This kind of an integrated approach helps to understand the 
mechanism to derive marine aerosols such as ice nuclei formation and 
lifetime of the cloud.

(8) Data archives

    These data obtained in this cruise will be submitted to the Data 
Management Group of JAMSTEC, and will be opened to the public via “Data 
Research System for Whole Cruise Information in JAMSTEC (DARWIN)” in 
JAMSTEC web site.
<http://www.godac.jamstec.go.jp/darwin/e>



References

Miyazaki, Y. Coburn, S. Ono, K. T.Ho, T. Pierce, R.B. Kawamura, K., and 
    Volkamer, R. 2016. Contribution of dissolved organic matter to 
    submicron water-soluble organic aerosols in the marine boundary layer 
    over the eastern equatorial Pacific. Atmos. Chem. Phys., 16, 7695-
    7707.
Nakamura, S. Maeda, N. Miron, I.M. Yoh, M. Izutsu, K. Kataoka, C. Honda,  
    T. Yasunaga, T. Nakaya, T. Kawai, J. Hayashizaki, Y. Horii, T. and 
    Iida, T. 2008. Metagenomic diagnosis of bacterial infections, Emerg. 
    Infect. Dis., 14(11):1784-86.
Nakamura, S. Yang, C.S. Sakon, N. Ueda, M. Tougan, T. Yamashita, A. Goto, 
    N. Takahashi, K. Yasunaga, T. Ikuta,  K. Mizutani, T. Okamoto, Y. 
    Tagami, M. Morita, R. Maeda, N. Kawai, J. Hayashizaki, Y. Nagai, Y. 
    Horii, T. Iida, T. and Nakaya, T. 2009. Direct metagenomic 
    detection of viral pathogens in nasal and fecal specimens using an  
    unbiased  high-throughput  sequencing  approach,  PLoS One. 4(1): 
    e4219.
Nunoura, T. Takaki, Y. Hirai, M. Shimamura, S. Makabe, A. Koide, O. 
    Kikuchi, T. Miyazaki, J. Koba, K. Yoshida, N. Sunamura, M. and
    Takai K. 2015. Hadal biosphere: insight into the microbial ecosystem 
    in the deepest ocean on Earth. Proc. Natl. Acad. Sci. U.S.A., 
    112(11):1230-1236.
O'Dowd. C.D. Facchini, M.C. Cavalli, F. Ceburnis, D. Mircea, M. Decesari,  
    S. Fuzzi,  S. Yoon  Y.J.  and Putaud, J.P. 2004. Biogenically driven 
    organic contribution to marine aerosol. Nature, 431, 676-680.
Russell, L.M. Hawkins, L.N. Frossard, A.A. Quinn, P.K. and Bates, T.S.    
    2010.  Carbohydrate-like composition of submicron atmospheric 
    particles and their production from ocean bubble bursting. Proc. 
    Natl. Acad. Sci. U.S.A., 107(15):6652-6657.
Wilson, T.W. Ladino, L.A. Alpert, P.A. Breckels, M.N. Brooks, I.M. 
    Browse, J. Burrows, S.M. Carslaw, K.S. Huffman, J.A. Judd, C., 
    Kilthau, W.P. Mason, R.H. McFiggans, G. Miller, L.A. Nájera, J.J. 
    Polishchuk, E. Rae, S. Schiller, C.L. Si, M. Temprado, J.V. Whale,   
    T.F. Wong, J.P. Wurl, O. Yakobi-Hancock, J.D. Abbatt, J.P. Aller, 
    J.Y. Bertram, A.K. Knopf, D.A. and Murray, B.J. 2015. A marine 
    biogenic source of atmospheric ice-nucleating particles. Nature, 
    525(7568):234-8.
Speedy, R.J. and Angell, C.A. 1976. Isothermal compressibility of 
    supercooled water and evidence for a thermodynamic singularity at -
    45°C. Journal of Chemical Physics, 65 (3), pp. 851-858.



3.12  Aerosol optical characteristics measured by ship-borne sky 
      radiometer

(1) Personnel
  
    Kazuma Aoki (University of Toyama) Principal Investigator/ not onboard 
    Tadahiro Hayasaka (Tohoku University) Co-worker / not onboard
    Sky radiometer operation was supported by Nippon Marine Enterprises, Ltd.


(2) Objective

    Objective of this observation is to study distribution and optical 
characteristics of marine aerosols by using a ship-borne sky radiometer 
(POM-01 MK-III: PREDE Co. Ltd., Japan). Furthermore, collections of the 
data for calibration and validation to the remote sensing data were 
performed simultaneously.


(3) Parameters

- Aerosol optical thickness at five wavelengths (400, 500, 675, 870 and 
  1020 nm)
- Ångström exponent
- Single scattering albedo at five wavelengths
- Size distribution of volume (0.01 µm – 20 µm)
- # GPS provides the position with longitude and latitude and heading 
  direction of the vessel, and azimuth and elevation angle of the sun. 
  Horizon sensor provides rolling and pitching angles.


(4) Instruments and Methods

    The sky radiometer measures the direct solar irradiance and the solar 
aureole radiance distribution with seven interference filters (0.315, 
0.4, 0.5, 0.675, 0.87, 0.94, and 1.02 µm). Analysis of these data was 
performed by SKYRAD.pack version 4.2 developed by Nakajima et al. 1996.


(5) Data archives

    Aerosol optical data are to be archived at University of Toyama 
(K.Aoki, SKYNET/SKY: http://skyrad.sci.u-toyama.ac.jp/) after the quality 
check and will be submitted to JAMSTEC.
    



3.13  C-band polarimetric Doppler weather radar

(1) Personnel

    Masaki KATSUMATA   (JAMSTEC)     Principal Investigator
                                     (onboard Leg-1, not on board Leg-2, 3, 4)
    Biao GENG          (JAMSTEC)     (not on board)
    Soichiro SUEYOSHI  (NME)         (Leg-1)
    Yutaro MURAKAMI    (NME)         (Leg-1, 2)
    Wataru TOKUNAGA    (NME)         (Leg-2)
    Koichi INAGAKI     (NME)         (Leg-2, 3)
    Shinya OKUMURA     (NME)         (Leg-3)
    Kazuho YOSHIDA     (NME)         (Leg-4)
    Ryo KIMURA         (NME)         (Leg-3, 4)
    Ryo KIMURA         (Mirai Crew)  (Leg-1) 
    Masanori MURAKAMI  (Mirai Crew)  (Leg-2, 3, 4)


(2) Objective

    The objective of the radar observations in this cruise is to 
investigate structure and evolution of precipitating systems over the 
globe, especially those related to the south pacific convergence zone 
(SPCZ) and stratiform clouds over the Southern Ocean.


(3) Radar specifications

    The C-band polarimetric weather Doppler radar on board the R/V Mirai 
is used. Basic specifications of the radar are as follows:

    Frequency:                     5370 MHz (C-band)
    Polarimetry:                   Horizontal and vertical
                                   (simultaneously transmitted and 
                                   received)
    Transmitter:                   Solid-state transmitter
    Pulse Configuration:           Using pulse-compression
    Output Power:                  6 kW (H) + 6 kW (V)
    Antenna Diameter:              4 meter
    Beam Width:                    1.0 degrees
    INU (Inertial Navigation Unit):PHINS (IXBLUE S.A.S.)


(4) Available variables

    Radar variables, which are converted from the power and phase of the 
backscattered signal at vertically- and horizontally-polarized channels, 
are as follows:

    Radar reflectivity:                 Z
    Doppler velocity:                   Vr
    Spectrum width of Doppler velocity: SW
    Differential reflectivity:          ZDR
    Differential propagation phase:     ΦDP
    Specific differential phase:        KDP
    Co-polar correlation coefficients:  ρHV


(5) Operational methodology

    The antenna is controlled to point the commanded ground-relative 
direction, by controlling the azimuth and elevation to cancel the ship 
attitude (roll, pitch and yaw) detected by the INU. The Doppler velocity 
is also corrected by subtracting the ship movement in beam direction.

    For the maintenance, internal signals of the radar are checked and 
calibrated at the beginning and the end of the cruise. Meanwhile, the 
following parameters are checked daily; (1) frequency, (2) peak output 
power, (3) pulse width, and (4) PRF (pulse repetition frequency).

    The operational mode of the radar during the cruise is shown in 
Tables 3.13-1. A dual PRF mode is used for a volume scan. For a RHI, 
vertical point, and surveillance PPI scans, a single PRF mode is used.


(6) Results

    The Doppler radar observations were conducted all through the cruise, 
except over the EEZ without permission.

    An example of the obtained data are shown in Fig. 3.13-1, for the 
case when synoptic-scale front passed over the vessel. The meridionally-
elongated raining area can be seen in the reflectivity panel. The 
velocity panel indicates the northerly wind (along front-elongating 
direction), which can be estimated by strongest approaching (negative) 
Doppler velocity to the north, and vice versa. Perturbations in the 
Doppler velocity can be seen to be recognized as wind discontinuous line, 
wave structure, etc. Detailed analyses of the obtained data will be 
performed after the cruise.


(7) Data archive

    All data of the Doppler radar observations during this cruise will be 
submitted to the JAMSTEC Data Management Group (DMG).
    












Table 3.13-1: Operational mode of the radar

             | Surveil- |                                      | RHI  | Vertical
             |  lance   |              Volume Scan             | Scan |  Point  
             | PPI Scan |                                      |      |   Scan  
————————————————————————————————————————————————————————————————————————————————
Repeated     |   30     |                   6                  |      12        
Cycle (min.) |          |                                      |                
————————————————————————————————————————————————————————————————————————————————
Times in One |    1     |                   1                  |  3   |   3     
Cycle        |          |                                      |      |         
————————————————————————————————————————————————————————————————————————————————
Pulse Width  |          |           |            |             |      |         
(long/short, |  200/2   |   64/1    |    32/1    |    32/1     | 32/1 |  32/1   
in microsec) |          |           |            |             |      |         
————————————————————————————————————————————————————————————————————————————————
Scan Speed   |   18     |    18     |     24     |     36      |   9  |   36    
(deg/sec)    |          |           |            |             |      |         
————————————————————————————————————————————————————————————————————————————————
             |          |      dual PRF (ray alternative)      |      |         
             |          |——————————————————————————————————————| 1250 |  2000   
PRF(s)       |  400     | 667 | 833 | 938 | 1250 | 1333 | 2000 |      |         
(Hz)         |          |     |     |     |      |      |      |      |         
————————————————————————————————————————————————————————————————————————————————
Pulses / Ray |   16     |  26 |  33 |  27 |  34  |  37  |  55  |  32  |   64    
————————————————————————————————————————————————————————————————————————————————
Ray Spacing  |   0.7    |    0.7    |    0.7     |     1.0     |  0.2 |   1.0   
(deg.)       |          |           |            |             |      |         
————————————————————————————————————————————————————————————————————————————————
Azimuth (deg)|                   Full Circle                   | Op-  |  Full   
             |                                                 | tion |  Circle 
————————————————————————————————————————————————————————————————————————————————
Bin Spacing  |                               150                                
(m)          |                                                                  
————————————————————————————————————————————————————————————————————————————————
Max. Range   |   300    |    150    |  100       |     60      |  100 |   60
(km)         |          |           |            |             |      |
————————————————————————————————————————————————————————————————————————————————
Elevation    |   0.5    |    0.5    | 1.0, 1.8,  | 18.7, 23.0, | 0.0~ |   90
Angle(s)     |          |           | 2.6, 3.4,  | 27.9, 33.5, | 60.0 |
(deg.)       |          |           | 4.2, 5.1,  | 40.0        |      |
             |          |           | 6.2, 7.6,  |             |      |
             |          |           | 9.7, 12.2, |             |      |
             |          |           | 15.2       |             |      |


Figure 3.13-1: Example of the obtained data, obtained at 2330UTC Jan.02, 
               2017, when a synoptic-scale front passed over. Upper 
               panel: Radar reflectivity at an elevation of 0.5 degrees, 
               within 300 km radius. Lower panel: Doppler velocity at 
               same elevation angle but within 150 km radius.



3.14  Lidar Observation


(1) Personal		

    Masaki KATSUMATA  (JAMSTEC)  Principal Investigator
                                 (onboard Leg-1, not on board Leg-2, 3)
    Kyoko TANIGUCHI   (JAMSTEC)  (not on board)
    Biao GENG         (JAMSTEC)  (not on board)


(2) Objective

    To capture distributions of cloud, aerosol and water vapor in high 
temporal and special resolutions.


(3) Instrumentation

    The lidar system on R/V Mirai transmits 10Hz pulse laser at 1064 nm, 
532nm, and 355nm, and detects backscattered signals at the same 
wavelengths (Mie signal) continuously up to 21km height. The system 
splits signals at 532 nm and 355nm into parallel and perpendicular 
components. These Mie signals indicate vertical distribution of cloud and 
aerosol. The parallel and perpendicular components provide the 
depolarization ratio, an indicator of particle roundness. The combination 
of these parameters provides the information about the clouds and 
aerosols, including amounts and types.

    The system also detects Raman signals at 387nm and 607nm for nitrogen 
and 660 nm for water vapor. The Raman signals indicate vertical 
distribution of nitrogen and water vapor molecules. The 660nm and 607nm 
signals share a 532nm laser as a light source. The ratio of the Raman 
signals is a proportion to the water vapor mixing ratio, a mass ratio of 
water vapor and dry air. The observations at 607nm and 660nm are only 
available at nighttime (from sunset to sunrise).

    The system reserves a period of 23:56-00:00 UTC for daily 
maintenance. Instead of observations,  the system obtains the background 
noise data for calibration. Necessary care such as observation window 
cleaning also take place in the period.


(4) Preliminary Results

    The data were obtained continuously thru Leg-1, 2 and 3, except over 
the EEZs without permissions. The data will be examined after the cruise.


(5) Data Archive

    All data obtained during this cruise will be submitted to the JAMSTEC 
Data Management Group (DMG).


(6) Acknowledgment

    During Leg-2 and 3, the operations are supported by the on-board 
technical staff of Nippon Marine Enterprise Ltd.
    



3.15  Disdrometers


(1) Personnel

    Masaki KATSUMATA  (JAMSTEC)  Principal Investigator
                                 (on board Leg-1 / not on board Leg-2, 3, 4)
    Kyoko TANIGUCHI   (JAMSTEC)  (not on board)
    Biao GENG         (JAMSTEC)  (not on board)


(2) Objectives

    The disdrometer can continuously obtain size distribution of 
raindrops. The objective of this observation is (a) to reveal 
microphysical characteristics of the rainfall, depends on the type, 
temporal stage, etc. of the precipitating clouds, (b) to retrieve the 
coefficient to convert radar reflectivity to the rainfall amount, and (c) 
to validate the algorithms and the product of the satellite-borne 
precipitation radars; TRMM/PR and GPM/DPR.


(3) Parameters

    Number and size of precipitating particles


(4) Methods

    Three different types of disdrometers are utilized to obtain better 
reasonable and accurate value on the moving vessel. Two of them are 
installed in one place, the starboard side on the roof of the anti-
rolling system of R/V Mirai, as in Fig. 3.15-1. The other one, named 
“micro rain radar”, is installed at the starboard side of the anti-
rolling systems (see Fig. 3.15-2).

    The details of the sensors are described below. All the sensors 
archive data every one minute.


Fig. 3.15-1: The two disdrometers (Parsivel and LPM), installed on the 
             roof of the anti-rolling tank.

Fig. 3.15-2: The micro rain radar, installed on the starboard side of 
             the anti-rolling tank.


(4-1) Laser Precipitation Monitor (LPM) optical disdrometer

    The “Laser Precipitation Monitor (LPM)” (Adolf Thies GmbH & Co) is an 
optical disdrometer. The instrument consists of the transmitter unit 
which emit the infrared laser, and the receiver unit which detects the 
intensity of the laser come thru the certain path length in the air. When 
a precipitating particle fall thru the laser, the received intensity of 
the laser is reduced. The receiver unit detect the magnitude and the 
duration of the reduction and then convert them onto particle size and 
fall speed. The sampling  volume, i.e. the size of the laser beam 
“sheet”, is 20 mm (W) x 228 mm (D) x 0.75 mm (H).
   
    The number of particles are categorized by the detected size and fall 
speed and counted every minutes. The categories are shown in Table 3.15-1.

(4-2) “Parsivel” optical disdrometer

    The “Parsivel” (OTT Hydromet GmbH) is another optical disdrometer. 
The principle is same as the LPM. The sampling volume, i.e. the size of 
the laser beam “sheet”, is 30 mm (W) x 180 mm (D). The categories are 
shown in Table 3.15-2.

(4-3) Micro rain radar

    The MRR-2 (METEK GmbH) was utilized. The specifications are in Table 
3.15-3. The antenna unit was installed at the starboard side of the anti-
rolling systems (see Fig. 3.15-2), and wired to the junction box and 
laptop PC inside the vessel.
  
    The data was averaged and stored every one minute. The vertical 
profile of each parameter was obtained every 200 meters in range distance 
(i.e. height) up to 6200 meters, i.e. well beyond the melting layer. The 
drop size distribution is recorded, as well as radar reflectivity, path-
integrated attenuation, rain rate, liquid water content and fall 
velocity.


(5) Preliminary Results

    The data were obtained continuously thru the cruise, except over the 
EEZs without permissions. The result will be examined after the cruise.


(6) Data Archive

    All data obtained during this cruise will be submitted to the JAMSTEC 
Data Management Group (DMG).


(7) Acknowledgment

    The operations are supported by Japan Aerospace Exploration Agency 
(JAXA) Precipitation Measurement Mission (PMM).  During Leg-2 and 3, the  
operations are supported by the on-board technical staff of Nippon Marine 
Enterprise Ltd.







Table 3.15-1: Categories of the size and the fall speed for LPM.

             Particle Size                       Fall Speed
      ————————————————————————————      ————————————————————————————
      Class  Diameter  Class width      Class   Speed    Class width
               [mm]       [mm]                  [m/s]       [m/s]
      —————  ————————  ———————————      —————  ————————  ———————————
         1    ≥ 0.125     0.125            1   ≥ 0.000      0.200
         2    ≥ 0.250     0.125            2   ≥ 0.200      0.200
         3    ≥ 0.375     0.125            3   ≥ 0.400      0.200
         4    ≥ 0.500     0.250            4   ≥ 0.600      0.200
         5    ≥ 0.750     0.250            5   ≥ 0.800      0.200
         6    ≥ 1.000     0.250            6   ≥ 1.000      0.400
         7    ≥ 1.250     0.250            7   ≥ 1.400      0.400
         8    ≥ 1.500     0.250            8   ≥ 1.800      0.400
         9    ≥ 1.750     0.250            9   ≥ 2.200      0.400
        10    ≥ 2.000     0.500           10   ≥ 2.600      0.400
        11    ≥ 2.500     0.500           11   ≥ 3.000      0.800
        12    ≥ 3.000     0.500           12   ≥ 3.400      0.800
        13    ≥ 3.500     0.500           13   ≥ 4.200      0.800
        14    ≥ 4.000     0.500           14   ≥ 5.000      0.800
        15    ≥ 4.500     0.500           15   ≥ 5.800      0.800
        16    ≥ 5.000     0.500           16   ≥ 6.600      0.800
        17    ≥ 5.500     0.500           17   ≥ 7.400      0.800
        18    ≥ 6.000     0.500           18   ≥ 8.200      0.800
        19    ≥ 6.500     0.500           19   ≥ 9.000      1.000
        20    ≥ 7.000     0.500           20   ≥ 10.000    10.000
        21    ≥ 7.500     0.500 
        22    ≥ 8.000     unlimited


Table 3.15-2: Categories of the size and the fall speed for Parsivel.

              Particle Size                      Fall Speed
      —————————————————————————————     ————————————————————————————
             Average                           Average
      Class  Diameter  Class spread     Class   Speed   Class spread
               [mm]        [mm]                 [m/s]       [m/s]
      —————  ————————  ————————————     —————  ———————  ————————————
        1     0.062      0.125          1    0.050       0.100
        2     0.187      0.125          2    0.150       0.100
        3     0.312      0.125          3    0.250       0.100
        4     0.437      0.125          4    0.350       0.100
        5     0.562      0.125          5    0.450       0.100
        6     0.687      0.125          6    0.550       0.100
        7     0.812      0.125          7    0.650       0.100
        8     0.937      0.125          8    0.750       0.100
        9     1.062      0.125          9    0.850       0.100
       10     1.187      0.125         10    0.950       0.100
       11     1.375      0.250         11    1.100       0.200
       12     1.625      0.250         12    1.300       0.200
       13     1.875      0.250         13    1.500       0.200
       14     2.125      0.250         14    1.700       0.200
       15     2.375      0.250         15    1.900       0.200
       16     2.750      0.500         16    2.200       0.400
       17     3.250      0.500         17    2.600       0.400
       18     3.750      0.500         18    3.000       0.400
       19     4.250      0.500         19    3.400       0.400
       20     4.750      0.500         20    3.800       0.400
       21     5.500      1.000         21    4.400       0.800
       22     6.500      1.000         22    5.200       0.800
       23     7.500      1.000         23    6.000       0.800
       24     8.500      1.000         24    6.800       0.800
       25     9.500      1.000         25    7.600       0.800
       26    11.000      2.000         26    8.800       1.600
       27    13.000      2.000         27   10.400       1.600
       28    15.000      2.000         28   12.000       1.600
       29    17.000      2.000         29   13.600       1.600
       30    19.000      2.000         30   15.200       1.600
       31    21.500      3.000         31   17.600       3.200
       32    24.500      3.000         32   20.800       3.200


Table 3.15-3: Specifications of the MRR-2.

                Transmitter power  50 mW
                Operating mode     FM-CW
                Frequency          24.230 GHz
                                   (modulation 1.5 to 15 MHz)
                3dB beam width     1.5 degrees
                Spurious emission  < -80 dBm / MHz
                Antenna Diameter   600 mm
                Gain               40.1 dBi




3.16 GNSS precipitable water


(1) Personnel

    Masaki KATSUMATA  (JAMSTEC)  Principal Investigator (not on board)
    Mikiko FUJITA     (JAMSTEC)  (not on board)
    Kyoko TANIGUCHI   (JAMSTEC)  (not on board)


(2) Objective

    Recording the GNSS satellite data to estimate the total column 
integrated water vapor content of the atmosphere.


(3) Method

    The GNSS satellite data was archived to the receiver (Trimble NetR9) 
with 5 sec interval. The GNSS antenna (Margrin) was set on the roof of 
radar operation room. The observations were carried out all thru the 
cruise.


(4) Results

    We will calculate the total column integrated water from observed 
GNSS satellite data after the cruise.


(5) Data archive

    Raw data is recorded as T02 format and stream data every 5 seconds. 
These raw datasets are  available from Mikiko Fujita of JAMSTEC. 
Corrected data will be submitted to JAMSTEC Marine-Earth Data and 
Information Department and will be archived there.
    



3.17  Ship-borne Measurement of Aerosols


(1) Personnel

    Fumikazu Taketani   JAMSTEC                PI, not on board
    Yugo Kanaya         JAMSTEC                not on board
    Takuma Miyakawa     JAMSTEC                on board (Leg 3)
    Hisahiro Takashima  JAMSTEC/Fukuoka Univ.  not on board
    Yutaka Tobo         NIPR                   not on board
    Yuichi Komazaki     JAMSTEC                not on board
    Hitoshi Matsui      Nagoya Univ.           not on board
    Momoka Yoshizue     Tokyo Univ. of Sci.    on board (Leg 3)


(2) Objectives

• To investigate roles of maritime aerosol particles in climate change 
  through indirect effect (i.e., aerosol-cloud interaction).
• To investigate processes of biogeochemical cycles between the 
  atmosphere and sea surface, such as sea spraying process.


(3) Parameters

• Particle size distributions
• Black carbon(BC) and fluorescent aerosol particle number concentrations
• Airborne bacteria concentrations
• Ice nucleation activity of aerosol particles
• Chemical composition of ambient particles
• Chemical composition of rain water
• Aerosol extinction coefficient (AEC)
• Surface carbon monoxide (CO) and ozone(O3) mixing ratios


(4) Instruments and methods

(4-1) Continuous or temporal aerosol observations: (4-1-1) Particle size 
      distributions

    The size-resolved number concentration of particles was measured by a 
scanning mobility particle sizer (SMPS) (comprising a 3080 Electrostatic 
Classifier with 3081 differential mobility analyzer (DMA), a condensation 
particle counter (CPC) (model 3010, TSI)), and a handheld optical 
particle counter (OPC) (KR-12A, RION). We temporally operated the OPC at 
the time of air sampling on the compass deck (see below for details).
    
(4-1-2) Black carbon (BC)

    Size-resolved number and mass BC concentrations were measured by an 
instrument based on laser-induced incandescence, single particle soot 
photometer (SP2) (model D, Droplet Measurement Technologies). The laser-
induced incandescence technique based on intra-cavity Nd:YVO4 laser 
operating at 1064 nm were used for detection of single particles of BC.

(4-1-3) Fluorescence measurements of airborne particles

    Fluorescent properties of aerosol particles were measured by a single 
particle fluorescence sensor, Waveband Integrated bioaerosol sensor 
(WIBS4) (WIBS-4A, Droplet Measurement Technologies). Two pulsed xenon 
lamps emitting UV light (280 nm and 370 nm) were used for excitation. 
Fluorescence emitted from a single particle within 310‒400 nm and 420‒650 
nm wavelength bands was detected by photomultiplier tubes (PMT) with the 
bandpass filters.

    The ambient air was commonly sampled from the rooftop of the 
environmental research room through a 3-m-long conductive silicone tube 
to the SP2, SMPS, and WIBS4, and was dehumidified using  a Nafion aerosol 
particle dryer to eliminate liquid water contents of airborne particles 
(typical relative humidity < 15%). They finally were introduced to those 
instruments installed in the environmental research room. The OPC 
instrument was temporally placed on the compass deck at the time to 
collect the particles for the electron microscopic analyses.

(4-2) Aerosol sampling on various types of media

    Ambient air samplings were carried out using air samplers on the 
compass deck. Aerosol particles were collected on the quartz fiber (QF) 
filter (bb= 110 mm) and pre-washed nuclepore membrane filter ((= 47 mm) 
along cruise track using a high-volume air sampler (HVS, HV-525PM, 
SIBATA, 500 L/min) and a handmade air sampler (10 L/min) to analyze their 
composition and ice nuclei ability, respectively. In addition to those 
samplers, a cascade impactor, which has 5 stages for the size separation, 
was operated at the flow rate of 9 L/min on the compass deck to 
investigate the size-resolved chemical compositions. For this sampler, QF 
filters (FF= 25 mm) were used for the collection. To avoid collecting 
particles derived from the research vessel exhaust, the sampling period 
was controlled automatically by using a “wind-direction selection 
system”. These sampling logs are listed in Tables 3.17-1~3.17-3.

    Electron microscopic analyses, including Scanning Election Microscopy 
(SEM) and Transmission Electron Microscopy (TEM), are performed in order 
to investigate the morphology and physicochemical properties of aerosol 
particles. For these purposes, aerosol particles were collected on a 
Silicon wafer or TEM grids (quantifoil or formvar) using air samplers as 
follows.

MPS-3 (California Measurements) for SEM 
MPS (EcoMesure) for TEM
Kl-1L (PIXE INTERNATIONAL) for TEM


Sampling was performed on the compass deck for 10 min. These samplings 
are summarized in Tables 3.17-4.	All samples will be analyzed using SEM 
or TEM placed in a laboratory of JAMSTEC or TUS.

    Automated counting of autofluorescent and epifluorescent particles 
were performed using a Bioplorer (Koyo Sangyo). Aerosol particles were 
collected on the gold-coated membrane filters using a custom-made sampler 
at typical flow rate of 0.9-1.0 L/min for 2-3 hrs. The collected aerosol 
particles were analyzed using the Bioplorer immediately after the 
sampling. The number concentrations of  airborne bacteria was calculated 
by dividing the counted bacteria on a filter by total sampling volume of 
air.    The samples collected were summarized in Table 3.17-5.

(4-3) MAX-DOAS

    Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS), a 
passive remote sensing technique measuring spectra of scattered visible 
and ultraviolet (UV) solar radiation, was used for atmospheric aerosol 
and gas profile measurements. Our MAX-DOAS instrument consists of two 
main parts: an outdoor telescope unit and an indoor spectrometer (Acton 
SP-2358 with Princeton Instruments PIXIS-400B), connected to each other 
by a 14-m bundle optical fiber cable. The line of sight was in the 
directions of the portside of the vessel and the scanned elevation angles 
were 1.5, 3, 5, 10, 20, 30, 90 degrees in the 30-min cycle. The roll 
motion of the ship was measured to autonomously compensate additional 
motion of the prism, employed for scanning the elevation angle.

    For the selected spectra recorded with elevation angles with good 
accuracy, DOAS spectral fitting was performed to quantify the slant 
column density (SCD) of NO2 (and other gases) and O4 (O2-O2, collision 
complex of oxygen) for each elevation angle. Then, the O4 SCDs were 
converted to the aerosol optical depth (AOD) and the vertical profile of 
aerosol extinction coefficient (AEC) using an optimal estimation 
inversion method with a radiative transfer model. The tropospheric 
vertical column/profile of NO2 and other gases were retrieved using 
derived aerosol profiles.

(4-4) CO and O3

    Ambient air was continuously sampled on the compass deck and drawn 
through ~20-m-long Teflon tubes connected to a gas filter correlation CO 
analyzer (Model 48C, Thermo Fisher Scientific) and a UV photometric ozone 
analyzer (Model 49C, Thermo Fisher Scientific), located in the Research 
Information Center. The data will be used for characterizing air mass 
origins.

(4-5) Rain sampling

    Rain samples were collected using a rain sampler. These samples were 
analyzed to investigate the chemical composition of rain water over 
Southern Ocean and south Pacific region. These sampling logs are listed 
in Tables 3.17-6.


(5) Station list or Observation log

Air samplings during MR16-09-leg3 were summarized as follows.


Table 3.17-1: High-volume air sampling for aerosol composition analyses

         ID            Date and Time        Latitude   Longitude 
                                            (deg,min)  (deg,min)
     ———————————  ————————————————————————  —————————  ——————————
     MR1609-H-S1  2017  02  11  12:40  UTC  60  59  S   77  55  W
     MR1609-H-S2  2017  02  13  15:07  UTC  64  39  S   98  45  W
     MR1609-H-S3  2017  02  15  16:31  UTC  66  40  S  121  41  W
     MR1609-H-S4  2017  02  16   2:50  UTC  67  00  S  126  00  W
     MR1609-H-S5  2017  02  19  20:15  UTC  60  29  S  126  00  W
     MR1609-H-S6  2017  02  23   0:00  UTC  53  01  S  126  00  W
     MR1609-H-S7  2017  02  25  17:40  UTC  51  18  S  143  45  W
     MR1609-H-S8  2017  02  28   1:00  UTC  46  54  S  158  25  W


Table 3.17-2: Low-volume air sampling for the size-resolved aerosol 
              composition analyses

         ID           Date and Time        Latitude   Longitude 
                                           (deg,min)  (deg,min)
     ——————————  ————————————————————————  —————————  ——————————
     MR1609-S-1  2017  02  11  12:40  UTC  60  59  S   77  55  W
     MR1609-S-2  2017  02  15  16:31  UTC  66  41  S  121  40  W
     MR1609-S-3  2017  02  16   2:50  UTC  67  00  S  126  00  W
     MR1609-S-4  2017  02  23   0:00  UTC  53  01  S  126  00  W


Table 3.17-3: Low-volume air sampling for airborne ice nuclei analysis

          ID           Date and Time         Latitude   Longitude 
                                             (deg,min)  (deg,min)
     ————————————  ————————————————————————  —————————  ——————————
     MR1609-N-001  2017  02  11  12:40  UTC  60  59  S   77  55  W
     MR1609-N-002  2017  02  13  15:07  UTC  64  39  S   98  45  W
     MR1609-N-003  2017  02  15  16:31  UTC  66  40  S  125   5  W
     MR1609-N-004  2017  02  16   2:50  UTC  67  00  S  126  00  W
     MR1609-N-005  2017  02  18   4:50  UTC  62  59  S  125  59  W
     MR1609-N-006  2017  02  20  23:55  UTC  57  49  S  126  00  W
     MR1609-N-007  2017  02  23   0:00  UTC  53  01  S  126  00  W
     MR1609-N-008  2017  02  24  20:45  UTC  52  14  S  137  17  W
     MR1609-N-009  2017  02  27  17:12  UTC  47  44  S  156  37  W
     MR1609-N-010  2017  03  01   2:10  UTC  44  36  S  163  44  W


Table 3.17-4: Aerosol sampling for electron microscope analyses

           ID          Date and Time           Latitude   Longitude 
                                               (deg,min)  (deg,min)
     ——————————————  ————————————————————————  —————————  ——————————
     MR1609-SEM-01   2017  02  11  12:35  UTC  60  59  S   77  57  W
     MR1609-SEM-02   2017  02  12  13:02  UTC  63  16  S   87  02  W
     MR1609-SEM-03   2017  02  13  17:14  UTC  64  45  S   99  46  W
     MR1609-SEM-04   2017  02  14  15:21  UTC  65  38  S  109  45  W
     MR1609-SEM-05   2017  02  15  16:27  UTC  66  41  S  121  38  W
     MR1609-SEM-06   2017  02  16  14:10  UTC  66  21  S  126  03  W
     MR1609-SEM-07   2017  02  17  12:00  UTC  64  21  S  126  02  W
     MR1609-SEM-08   2017  02  18  23:15  UTC  62  23  S  126  06  W
     MR1609-SEM-09   2017  02  19  17:30  UTC  60  29  S  125  59  W
     MR1609-SEM-10   2017  02  20  14:43  UTC  58  30  S  125  59  W
     MR1609-SEM-11   2017  02  21  18:45  UTC  55  30  S  125  59  W
     MR1609-SEM-12   2017  02  22  16:05  UTC  53  30  S  126  01  W
     MR1609-SEM-13   2017  02  24  16:35  UTC  52  24  S  135  56  W
     MR1609-SEM-14   2017  02  26   0:09  UTC  50  55  S  145  51  W
     MR1609-SEM-15   2017  02  26   2:42  UTC  50  45  S  146  41  W
     MR1609-SEM-16   2017  02  26  19:20  UTC  49  33  S  151  44  W
     MR1609-SEM-17   2017  02  27   1:12  UTC  49  6.7 S  153  21  W
     MR1609-SEM-18   2017  02  27  19:07  UTC  47  31  S  157  20  W
     MR1609-SEM-19   2017  03  02   2:10  UTC  42  20  S  169  20  W
     MR1609-T-01     2017  02  11  19:45  UTC  61  47  S   80  29  W
     MR1609-T-02     2017  02  12  20:43  UTC  63  56  S   90  12  W
     MR1609-T-03     2017  02  13  23:57  UTC  65  2   S  102  52  W
     MR1609-T-04     2017  02  14  23:52  UTC  65  59  S  113  41  W
     MR1609-T-05     2017  02  15   0:12  UTC  66  56  S  125  18  W
     MR1609-T-06     2017  02  16  21:28  UTC  65  40  S  125  58  W
     MR1609-T-07     2017  02  17  18:20  UTC  63  41  S  126  00  W
     MR1609-T-08     2017  02  18  23:28  UTC  62  20  S  126  06  W
     MR1609-T-09     2017  02  19  23:19  UTC  60  01  S  125  58  W
     MR1609-T-10     2017  02  20  19:45  UTC  58  00  S  126  00  W
     MR1609-T-11     2017  02  21  18:57  UTC  53  31  S  125  59  W
     MR1609-T-12     2017  02  25   0:10  UTC  52  05  S  138  25  W
     MR1609-T-13     2017  02  26   2:30  UTC  50  45  S  146  37  W
     MR1609-T-14     2017  02  26  17:24  UTC  49  41  S  151  13  W
     MR1609-T-15     2017  02  27  17:23  UTC  47  42  S  157  01  W
     MR1609-T-16     2017  03  01  18:35  UTC  43   4  S  167  31  W
     MR1609-N it-01  2017  02  11  12:37  UTC  61  01  S   77  60  W
     MR1609-N it-02  2017  02  11  19:45  UTC  61  48  S   81  32  W
     MR1609-N it-03  2017  02  12  20:43  UTC  63  57  S   90  20  W
     MR1609-N it-04  2017  02  14  23:57  UTC  65  03  S  102  59  W
     MR1609-N it-05  2017  02  14  15:21  UTC  65  40  S  109  52  W
     MR1609-N it-06  2017  02  14  22:52  UTC  65  57  S  113  21  W
     MR1609-N it-07  2017  02  15  16:21  UTC  66  41  S  121  43  W
     MR1609-N it-08  2017  02  16   0:11  UTC  66  56  S  125  24  W
     MR1609-N it-09  2017  02  16  14:10  UTC  66  20  S  126   3  W
     MR1609-N it-10  2017  02  16  23:25  UTC  65  39  S  125  57  W
     MR1609-N it-11  2017  02  17  12:15  UTC  64  21  S  126   2  W
     MR1609-N it-12  2017  02  18  20:40  UTC  62  20  S  126   7  W
     MR1609-N it-13  2017  02  19  17:33  UTC  60  29  S  125  60  W
     MR1609-N it-14  2017  02  20   0:01  UTC  60  01  S  125  59  W
     MR1609-N it-15  2017  02  20  14:50  UTC  58  30  S  125  60  W
     MR1609-N it-16  2017  02  20  23:41  UTC  57  49  S  125  60  W
     MR1609-N it-17  2017  02  21  18:45  UTC  55  30  S  125  60  W
     MR1609-N it-18  2017  02  22   0:10  UTC  55  01  S  125  59  W
     MR1609-N it-19  2017  02  22  16:10  UTC  53  30  S  126   1  W
     MR1609-N it-20  2017  02  22  23:40  UTC  53  01  S  126   0  W
     MR1609-N it-21  2017  02  24  16:35  UTC  52  23  S  136   0  W
     MR1609-N it-22  2017  02  25   0:10  UTC  52  05  S  138  29  W
     MR1609-N it-23  2017  02  26   0:09  UTC  50  54  S  145  56  W
     MR1609-N it-24  2017  02  26  17:24  UTC  49  40  S  151  17  W
     MR1609-N it-25  2017  02  27   0:54  UTC  49  07  S  153  20  W
     MR1609-N it-26  2017  02  27  17:24  UTC  47  41  S  157   2  W
     MR1609-N it-27  2017  02  28   1:58  UTC  46  52  S  158  27  W
     MR1609-N it-28  2017  02  28  18:23  UTC  45  17  S  161  59  W
     MR1609-N it-29  2017  03  01   1:57  UTC  44  36  S  163  46  W
     MR1609-N it-30  2017  03  01  18:35  UTC  43  03  S  167  34  W
     MR1609-N it-31  2017  03  02   2:10  UTC  42  18  S  169  25  W
     MR1609-N it-32  2017  03  02  18:30  UTC  40  29  S  173  46  W

*MR1609-SEM-## and MR1609-T-## samples were collected by JAMSTEC
*MR1609-Nit-## samples were collected by TUS


Table 3.17-5: Air sampling for automated counting of airborne bacteria

           ID          Date and Time           Latitude   Longitude 
                                               (deg,min)  (deg,min)
     ——————————————  ————————————————————————  —————————  ——————————
     MR1609-B-air01  2017  02  11  12:37  UTC  60  59  S   77  54  W
     MR1609-B-air02  2017  02  12  13:02  UTC  63  16  S   87  02  W
     MR1609-B-air03  2017  02  13  17:16  UTC  64  45  S   99  47  W
     MR1609-B-air04  2017  02  13  20:17  UTC  64  54  S  101  11  W
     MR1609-B-air05  2017  02  14  15:21  UTC  65  38  S  109  45  W
     MR1609-B-air06  2017  02  14  18:13  UTC  65  48  S  111   7  W
     MR1609-B-air07  2017  02  14  20:15  UTC  65  54  S  112   5  W
     MR1609-B-air08  2017  02  15  16:28  UTC  66  41  S  121  39  W
     MR1609-B-air09  2017  02  15  19:00  UTC  66  42  S  122  49  W
     MR1609-B-air10  2017  02  16   2:54  UTC  67  00  S  126  00  W
     MR1609-B-air11  2017  02  16  14:10  UTC  66  21  S  126   3  W
     MR1609-B-air12  2017  02  16  21:29  UTC  65  38  S  125  59  W
     MR1609-B-air13  2017  02  17  12:00  UTC  64  21  S  126   2  W
     MR1609-B-air14  2017  02  17  18:23  UTC  63  41  S  126  00  W
     MR1609-B-air15  2017  02  18   1:00  UTC  63   1  S  126   1  W
     MR1609-B-air16  2017  02  18  18:37  UTC  62  20  S  126   6  W
     MR1609-B-air17  2017  02  19  17:35  UTC  60  29  S  125  59  W
     MR1609-B-air18  2017  02  19  23:20  UTC  60   7  S  125  58  W
     MR1609-B-air19  2017  02  20  14:30  UTC  58  29  S  125  59  W
     MR1609-B-air20  2017  02  20  19:47  UTC  58  00  S  126  00  W
     MR1609-B-air21  2017  02  21  18:50  UTC  55  31  S  125  59  W
     MR1609-B-air22  2017  02  22  16:05  UTC  53  30  S  126   2  W
     MR1609-B-air23  2017  02  24  16:35  UTC  52  24  S  135  56  W
     MR1609-B-air24  2017  02  25   0:10  UTC  52  05  S  138  25  W
     MR1609-B-air25  2017  02  26   0:30  UTC  50  45  S  146  37  W
     MR1609-B-air26  2017  02  26  17:26  UTC  49  41  S  151  13  W
     MR1609-B-air27  2017  02  27   0:55  UTC  49   8  S  153  17  W
     MR1609-B-air28  2017  02  27  17:19  UTC  47  43  S  156  59  W
     MR1609-B-air29  2017  03  01   2:10  UTC  44  36  S  163  44  W
     MR1609-B-air30  2017  03  02   2:17  UTC  42  19  S  169  22  W


Table 3.17-6: Rain sampling for chemical composition analysis

           ID                   Date and Time        Latitude   Longitude 
                                                     (deg,min)  (deg,min)
—————————————————————————  ————————————————————————  —————————  ——————————
MR 1609-Leg3-rain-001-冷凍  2017  02  11  12:45  UTC  61  01  S   77  60  W
MR 1609-Leg3-rain-001-冷蔵  2017  02  11  12:45  UTC  61  01  S   77  60  W
MR 1609-Leg3-rain-002-冷凍  2017  02  12  20:45  UTC  63  57  S   90  20  W
MR 1609-Leg3-rain-003-冷凍  2017  02  15  16:30  UTC  66  41  S  121  43  W
MR 1609-Leg3-rain-003-冷蔵  2017  02  15  16:30  UTC  66  41  S  121  43  W
MR 1609-Leg3-rain-004-冷凍  2017  02  16  23:30  UTC  65  39  S  125  57  W
MR 1609-Leg3-rain-005-冷凍  2017  02  18   0:27  UTC  63  06  S  126   1  W
MR 1609-Leg3-rain-006-冷凍  2017  02  18  23:25  UTC  62  20  S  126   7  W
MR 1609-Leg3-rain-007-冷凍  2017  02  20  23:59  UTC  57  48  S  125  60  W
MR 1609-Leg3-rain-008-冷凍  2017  02  22   0:27  UTC  55  01  S  125  59  W
MR 1609-Leg3-rain-009-冷凍  2017  02  23   0:03  UTC  53  02  S  126   0  W
MR 1609-Leg3-rain-009-冷蔵  2017  02  23   0:03  UTC  53  02  S  126   0  W
MR 1609-Leg3-rain-010-冷凍  2017  02  24  16:54  UTC  52  23  S  136   1  W
MR 1609-Leg3-rain-010-冷蔵  2017  02  24  16:54  UTC  52  23  S  136   1  W
MR 1609-Leg3-rain-011-冷凍  2017  02  25   0:29  UTC  52  05  S  138  30  W
MR 1609-Leg3-rain-012-冷凍  2017  02  27  17:44  UTC  47  40  S  157   4  W
MR 1609-Leg3-rain-012-冷蔵  2017  02  27  17:44  UTC  47  40  S  157   4  W
MR 1609-Leg3-rain-013-冷凍  2017  02  28  18:38  UTC  45  18  S  161  58  W
MR 1609-Leg3-rain-013-冷蔵  2017  02  28  18:38  UTC  45  18  S  161  58  W
MR 1609-Leg3-rain-014-冷凍  2017  03  02  18:43  UTC  40  29  S  173  45  W
MR 1609-Leg3-rain-014-冷蔵  2017  03  02  18:43  UTC  40  29  S  173  45  W



(6) Preliminary results


Figure 3.17-1: Average particle size distribution for Feb 11 – 28, 2017. 
               (X axis is Particle diameter in nm; Y axis is the number 
               concentration normalized by size-bin width)

Figure 3.17-2: Histogram of total particle number concentration for Feb 
               11-28, 2017.



(7) Data archives

    These data obtained in this cruise will be submitted to the Data 
Management Group of JAMSTEC, and will be opened to the public via “Data 
Research System for Whole Cruise Information in JAMSTEC (DARWIN)” in 
JAMSTEC web site.
<http://www.godac.jamstec.go.jp/darwin/e>



3.18  Underway CT


(1) Personnel

    Akihiko Murata (JAMSTEC)  
    Tomonori Watai (MWJ) 
    Atsushi Ono (MWJ)
    Emi Deguchi (MWJ)      
    Nagisa Fujiki (MWJ)


(2) Objective

    It is doubtless that the ocean moderates global warming by absorbing 
~30% of anthropogenic CO2 emitted into the atmosphere. However, increases 
of anthropogenic CO2 in the ocean cause another CO2 problem called as 
ocean acidification. Since it is predicted that ocean acidification gives 
a large influence on ocean biology, especially on calcifying organisms, 
it is an important task to evaluate progression of ocean acidification.

    In the leg 3 of MR16-09 cruise, we measured underway dissolved 
inorganic carbon (CT) in the surface seawater continuously along the 
cruise track. The data for CT are used to calculate saturation state of 
calcium carbonate (a), which is one of good indicators of ocean 
acidification, together with data for underway pCO2 (section 3.7)


(3) Apparatus

    Measurement of CT was made with automated TCO2 analyzer (Nippon ANS,  
Inc., Japan).  The system comprises of a seawater dispensing system, a 
CO2 extraction system and a coulometer (Model 3000A, Nippon ANS, Inc., 
Japan). Specification of the system is as follows:

    Seawater collected from the seawater inlet at 4.5 m deep is 
transferred into a DURAN® glass bottle of nominal 250 ml after 
overflowing seawater of 3 time volume of the bottle. The seawater sample 
is kept at 20°C by a constant temperature bath until measurement. Then 
the seawater sample is dispensed from the glass bottle into a pipette of 
about 15 ml volume. The pipette is also kept at 20 °C by a water jacket, 
in which water from a water bath set at 20°C is circulated. CO2 dissolved 
in a seawater sample is extracted   in a stripping chamber of the CO2 
extraction system by adding phosphoric acid (~ 10 % v/v) of about 2 ml. 
The stripping chamber is approx. 25 cm long and has a fine frit at the 
bottom. The acid is added to the stripping chamber from the bottom of the 
chamber by pressurizing an acid bottle for a given time to push out the 
right amount of acid. The pressurizing is made with nitrogen gas (99.9999 
%). After the acid is transferred to the stripping chamber, a seawater 
sample kept in a pipette is introduced to the stripping chamber by the 
same method as in adding an acid. The seawater reacted with phosphoric 
acid is stripped of CO2 by bubbling the nitrogen gas through a fine frit 
at the bottom of the stripping chamber. The CO2 stripped in the chamber 
is carried by the nitrogen gas (flow rates is 140 ml min-1) to the 
coulometer through a dehydrating module. The module consists of two 
electric dehumidifiers (kept at ~4°C) and a chemical desiccant 
(Mg(ClO4)2). The measurement sequence such as 1.5% CO2 gas in N2 base, 
system blank (phosphoric acid blank), seawater samples (6) is repeated 
automatically by PC control.


(4) Results

    Concentrations of CT in surface seawater along the cruise track are 
shown in Fig. 3.18.1, together with (a) salinity and (b) SST.


Fig. 3.18.1: Preliminary results of concentrations of CT in surface 
             seawater (blue), salinity (red), and SST (green) observed 
             during the leg 3 of MR16-09.




3.19  XCTD
      March 3, 2017


(1) Personnel

    Hiroshi Uchida (JAMSTEC) 
    Shinya Okumura (NME) 
    Koichi Inagaki (NME)
    Ryo Kimura (NME)
    Masanori Murakami (Mirai crew)


(2) Objectives

    XCTD (eXpendable Conductivity, Temperature and Depth profiler) 
measurements were carried out to substitute CTD casts and to evaluate the 
fall rate equation and the thermal bias by comparing with CTD 
(Conductivity, Temperature and Depth profiler) measurements.


(3) Instrument and Method

    The XCTD used was XCTD-4 (Tsurumi-Seiki Co., Ltd., Yokohama, 
Kanagawa, Japan) with an MK-150N deck unit (Tsurumi-Seiki Co., Ltd.). The 
manufacturer’s specifications are listed in Table 3.19.1. In this cruise, 
the XCTD probes were deployed by using 8-loading automatic launcher 
(Tsurumi-Seiki Co., Ltd.) or a hand launcher (stn. ****). For comparison 
with CTD, XCTD was deployed at about 10 minutes after the beginning of 
the down cast of the CTD (P17E_8, 16, 22 and 23). For correction of the 
sound velocity profile used in the bathymetry observation, XCTD-1 was 
deployed near station P17E_1. Also, two XCTD-4 were deployed at CO2 buoy 
deployment locations at longitude of 140°W and 160°W.

    The fall-rate equation provided by the manufacturer was initially 
used to infer depth Z (m), Z = at – bt2, where t is the elapsed time in 
seconds from probe entry into the water, and a (terminal velocity) and b 
(acceleration) are the empirical coefficients (Table 3.19.2).


(4) Data Processing and Quality Control

    The XCTD data were processed and quality controlled based on a method 
by Uchida et al. (2011). Differences between XCTD and CTD depths were 
shown in Fig. 3.19.1. The terminal velocity error was estimated for the 
XCTD-4 (Table 3.19.2). The XCTD-4 data were corrected for the depth error 
by using the estimated terminal velocities. Differences of temperature on 
pressure surfaces were examined by using side-by-side XCTD and CTD data 
(Fig. 3.19.3). Average thermal bias below 900 dbar was 0.014 °C. The 
XCTD data were corrected for the thermal bias. Differences of salinity on 
reference temperature surfaces  were  examined  by  using  CTD  data  
(Fig.  3.19.4).  The  XCTD  data  were  corrected  for the estimated 
salinity bias.


(5) Results

    Temperature-salinity plot using the quality controlled XCTD data is 
shown in Fig. 3.19.3.


(6) References

Kizu, S., H. Onishi, T. Suga, K. Hanawa, T.  Watanabe, and H. Iwamiya 
    (2008): Evaluation of the fall rates of the present and developmental 
    XCTDs. Deep-Sea Res I, 55, 571–586.
Uchida, H., K. Shimada, and T. Kawano (2011): A method for data 
    processing to obtain high-quality XCTD data. J. Atmos. Oceanic 
    Technol., 28, 816–826.
Uchida, H., A. Murata, and T. Doi (eds.) (2014): WHP P10 Revisit in 2011 
    Data Book, 179 pp., JAMSTEC.
Uchida, H., K. Katsumata, and T. Doi (eds.) (2015): WHP P14S/S04I Revisit 
    in 2012/2013 Data Book, 187 pp., JAMSTEC.
Uchida, H and T. Doi (eds.) (2016): WHP P01 Revisit in 2014 Data Book, 
    149 pp., JAMSTEC, ISBN 978-4-901833-22-6.



Table 3.19.1: Manufacturer’s specifications of XCTD-4.

Parameter      Range           Accuracy
————————————  ———————————————  —————————————————————————————————
Conductivity   0 ~ 60 mS cm–1  ±0.03 mS cm–1
Temperature   –2 ~ 35 °C       ±0.02 °C
Depth          0 ~ 1850 m      5 m or 2%, whichever is greater *
————————————————————————————————————————————————————————————————
* Depth error is shown in Kizu et al (2008).



Table 3.19.2: Manufacturer’s coefficients for the fall-rate equation.

Model   a                         b                     e
        (terminal velocity, m/s)  (acceleration, m/s2)  (terminal velocity
                                                        error, m/s)
——————  ————————————————————————  ————————————————————  ——————————————————
XCTD-4  3.68081                   0.00047               –0.0197


Table 3.19.3: Thermal biases of the XCTD temperature data.

Cruise   Average thermal bias (°C)  Depth range   Source
———————  —————————————————————————  ————————————  ————————————————————————
MR09-01  0.016                      >= 1100 dbar  Uchida et al. (2011)
KH-02-3  0.019                      >= 1100 dbar  Uchida et al. (2011)
MR11-08  0.014                      >= 1100 dbar  Uchida et al. (2014)
MR12-05  0.009                      >= 400 dbar   Uchida et al. (2015)
MR14-04  0.011                      >= 900 dbar   Uchida et al. (2016)
MR15-05 –0.003                      >= 900 dbar   Cruise report of MR15-05 
MR16-09  0.014                      >= 900 dbar   this report
Mean     0.011 ± 0.007


Table 3.19.4: Salinity biases of the XCTD data.

XCTD     Salinity  Reference         Reference  Reference
station  bias      temperature (°C)  salinity   CTD stations
———————  ————————  ————————————————  —————————  ————————————
 8       –0.007    1.7               34.7306    7, 8, 9
22        0.008    2.4               34.6366    22, 23
23        0.017    2.4               34.6366    22, 23


Figure 3.19.1: Differences between XCTD and CTD depths for XCTD-4. 
               Differences were estimated with the same method as Uchida 
               et al. (2011). Standard deviation of the estimates 
               (horizontal bars) and the manufacturer’s specification for 
               XCTD depth error (dotted lines) are shown. The regression 
               for the data (solid line) is also shown.

Figure 3.19.2: Comparison between XCTD and CTD temperature profiles. (a) 
               Mean temperature of CTD profiles with standard deviation 
               (shade) and (b) mean temperature difference with standard 
               deviation (shade) between the XCTD and CTD. Mean profiles 
               were low-pass filtered by a running mean with a window of 
               51 dbar.

Figure 3.19.3: Comparison of temperature-salinity profiles of CTD data 
               (red lines) used for the XCTD salinity bias estimation and 
               salinity bias-corrected XCTD data (black lines).



3.20  Radiosonde observations


(1) Personnel		

    Masaki KATSUMATA   (JAMSTEC)  Principal Investigator  (on board Leg-1)
    Biao GENG          (JAMSTEC)  (not on board)
    Kyoko TANIGUCHI    (JAMSTEC)  (not on board)
    Soichiro SUEYOSHI  (NME)      Operation Leader
    Yutaro MURAKAMI    (NME)	


(2) Objectives

    The objective of radiosonde observations is to obtain the atmospheric 
profile of temperature, humidity, and wind speed/direction, and their 
temporal and special variations over the tropical ocean.


(3) Operational methodology

    The Vaisala GPS radiosonde sensors (RS92-SGPD and RS41-SGP) were 
launched with the balloon (TA-200). The on-board radiosonde system 
consists of sounding processing system (SPS-311), ground check device 
(RI41), processing and recording software (MW41), GPS antenna (GA20), UHF 
antenna (RB21), and automatic balloon launcher (ASAP). In addition, the 
pressure sensor (PTB-330) was also utilized for ground check. In case the 
relative wind to the ship is not appropriate for using the automatic 
balloon launcher, the radiosonde equipped balloon was launched manually.


(4) Results

    The radiosonde observations were conducted from Dec. 29, 2016 to 
Jan.15, 2017. During this period, 51 radiosondes equipped balloons have 
been launched (Table 3.20-1). Figure 3.20-1 shows some results   of the 
radiosonde observations. Detailed analyses of the data observed by the 
radiosonde will be performed after the cruise.


(5) Data Archive

    The radiosonde data were sent to the world meteorological community 
via Global Telecommunication System (GTS) through the Japan 
Meteorological Agency, immediately after each observation, when the 
appropriate satellite communication was available.

    Raw data are recorded in Vaisala original binary format. The ASCII 
data are also available. These datasets will be submitted to JAMSTEC Data 
Integration and Analyses Group.
    

Table 3.20-1: Radiosonde launch log, with surface values and maximum 
              height.

       Nominal Time  Launched Location        Surface Values           Max 
  ID     YYYYMMDD      Lat.      Lon.     P      T     RH   WD   WS   Height  Sensor 
            hh        deg.N     deg.E    hPa    deg.C  %   Deg.  m/s    m      Type
—————  ————————————  ———————  ————————  ——————  —————  ——  ———  ————  —————  ———————
RS001   2016122900   -26.051  -174.346  1006.3  22.6   80  147   9.4  22045  
RS002   2016122912   -27.451  -172.664  1004.5  22.0   87  141   7.9  22486  
RS003   2016123000   -29.027  -170.693  1003.7  21.2   93  174   4.5  22898  
RS004   2016123012   -30.633  -168.564  1005.0  21.9   92   51   4.5  22986  
RS005   2016123100   -32.268  -166.310  1008.5  21.6   90   51   5.9  18582  
RS006   2016123112   -33.824  -163.983  1012.4  20.7   91   90   3.2  29246  
RS007   2017010100   -35.343  -161.605  1016.0  20.3   91   58   8.5  20797  
RS008   2017010106   -36.071  -160.380  1017.1  20.2   86   48   7.1  21961  
RS009   2017010112   -36.807  -159.130  1016.8  19.3   84   61   6.9  20864  
RS010   2017010118   -37.504  -157.821  1016.8  18.8   87   58   8.0  22280  
RS011   2017010200   -38.186  -156.538  1015.1  19.2   81   32   6.9  20785  
RS012   2017010206   -38.882  -155.204  1012.6  18.4   90   26   7.2  20394
RS013   2017010212   -37.576  -153.732  1009.1  17.6   94   14   8.5  21372    RS92
RS014   2017010218   -40.250  -152.311  1005.8  16.9   96   11   9.3  19666  
RS015   2017010300   -40.934  -150.872  1002.4  15.4   90  358  12.2  24105  
RS016   2017010306   -41.537  -149.377   999.8  16.0   98  353  13.8  18075  
RS017   2017010312   -42.115  -147.839   999.4  15.4  100  345  10.4  16678  
RS018   2017010318   -42.733  -146.302  1002.4  12.5  100  186  11.4  18540  
RS019   2017010400   -43.190  -145.013  1004.1  12.3  100  165   8.6  21521  
RS020   2017010412   -44.149  -142.101  1007.4  11.5   96  171   7.7  20735  
RS021   2017010500   -44.931  -139.159  1011.3  13.0   99  336   5.6  22752  
RS022   2017010512   -45.947  -135.890  1015.1  12.9   99  328   5.6  21786  
RS023   2017010600   -46.748  -132.380  1017.8  12.8   96  326   5.8  22231  
RS024   2017010612   -47.433  -128.840  1018.3  12.2   97  336   5.3  21201  
RS025   2017010700   -48.042  -125.109  1020.0  12.3   93  348   3.5  21294  
RS026   2017010709   -48.367  -122.338  1022.4  11.7   78   32   2.7  20378  
RS027   2017010712   -48.474  -121.398  1022.5  11.0   88   71   2.5  20800  
RS028   2017010800   -48.773  -118.048  1025.3  10.9   86  241   1.7  18227  
RS029   2017010809   -48.964  -115.406  1026.5   9.5   73  173   5.8  23324  
RS030   2017010812   -49.024  -114.639  1025.9   8.9   73  200   6.0  19343  
RS031   2017010900   -49.080  -111.410  1025.0   8.5   77  217   3.2  21872  
RS032   2017010906   -49.097  -109.733  1024.6   8.4   79  206   4.2  21216  
RS033   2017010912   -49.100  -108.011  1022.3   8.8   84  216   5.1  22195  
RS034   2017011000   -49.045  -105.042  1019.1   8.1   87  207   3.2  19971  
RS035   2017011006   -48.969  -103.614  1019.0   8.7   97  149   4.0  18118  
RS036   2017011012   -48.875  -102.260  1017.8   8.2   83  168   3.4  21405  
RS037   2017011100   -48.703  -99.463   1016.2   9.1   76  214   1.2  20638  
RS038   2017011106   -48.542  -98.030   1015.8   9.0   71  227   2.7  21070    RS41
RS039   2017011112   -48.408  -96.661   1014.1   7.6   91  245   5.5  20946  
RS040   2017011200   -48.055  -93.844   1012.5  10.2   79  254  11.2  20429  
RS041   2017011206   -47.846  -92.544   1013.5   9.3   84  218   9.8  21518  
RS042   2017011212   -47.680  -91.152   1014.6   9.9   86  240  10.3  17657  
RS043   2017011300   -47.219  -88.682   1018.3  10.5   81  264   8.9  20881  
RS044   2017011306   -46.952  -87.362   1019.5  10.4   82  263  11.2  21297  
RS045   2017011312   -46.697  -86.093   1019.5  10.8   75  264  10.7  21013  
RS046   2017011400   -45.920  -82.622   1018.5  11.8   75  264  11.2  22353  
RS047   2017011406   -45.496  -81.002   1017.4  11.8   65  259  11.1  19633  
RS048   2017011412   -44.940  -80.049   1016.3  11.7   69  276   8.6  20843  
RS049   2017011418   -44.661  -80.139   1015.3  10.9   86  269   9.1  21309  
RS050   2917011500   -44.542  -80.109   1013.7  11.6   93  295   5.3  21899  
RS051   2017011506   -44.396  -80.021   1011.5  12.6   85  321   9.8  21741


Figure 3.20-1: Time-height (time-pressure) cross section of the obtained 
               data, for (top) potential temperature, (second top) 
               relative humidity, (third) zonal wind, and (bottom) 
               meridional wind, respectively.



4.  Station Observation


4.1  Single Channel Seismic Survey


(1) Personnel

    Natsue Abe        (R&D Center for Ocean Drilling Science, JAMSTEC) 
    Toshimasa Nasu    (Nippon Marine Einterprises,Ink.)
    Mitsuteru Kuno    (Nippon Marine Einterprises,Ink.) 
    Satsuki Iijima    (Nippon Marine Einterprises,Ink.) 
    Hiroyuki Hayashi  (Nippon Marine Einterprises,Ink.)


(2) Introduction

    The SCS reflection data were acquired along 4 lines (L1 ~4), listed 
below, in two areas with a total length of approximately 240 km (Figures 
4.1.1&2; Table 4-1-1).

    ・Line1：Start 45-56.33835S, 75-56.36719W - End 46-06.71562S, 76-43.73703W
    ・Line2：Start 45-55.04196S, 75-50.95871W - End 45-58.12477S, 76-04.74792W
    ・Line3：Start 47-52.64648S, 75-56.24817W – End 47-52.52037S, 76-50.38330W
    ・Line4_0: Start 47-57.88422S, 75-57.24289W – End 47-57.29004S, 76-01.83151W
    ・Line4_1: Start 47-57.23190S, 76-02.19543W - End47-51.93878S, 76-46.98715W

    In all tracks, reflection from the seafloor was clearly recorded. 
Igneous basement structures were confirmed except beneath steep slope of 
the ridge-like seamounts and the continental slops. In some  places 
beneath the continental slops, the boundary between the footwall and the 
hanging wall is likely identified (Lines 3 & 4). In the L1&2, half graben 
structure that was formed during mid-ocean ridge opening are clear 
reflections were recognized within both sediments and basements. The SCS 
reflection data across the subduction zone are complex. Further 
descriptions and investigations will be reported later.


(3) Spec information

    The single channel seismic survey equipment and specification is as 
follows. The image of the single channel seismic system if shown in the 
Figure 4.1.3. The detail conditions of each lines are listed in the Table 
4.1.2.

    Streamer
    Manufacturer:            S.I.G
    Active section length:   65 m
    Hydrophone Interval:     1 m
    Type of Hydrophone:      S.I.G.16

    Hydrophone output:       -90 dB,re 1V/µbar, ±1 dB 
    Frequency flat from:     10Hz to 1000Hz
    Depth sensor:            Yes 
    Preamplifier gain:       39
    Lead in cable length:    135 m
    Receiver depth:          9.62 m (Line1), 1.91 m (Line2), 1.75 m 
                             (Line3), 1.85 m (Line4_0), 2.19 m (Line4_0)

    Source 
    Manufacturer:            Sercel 
    Type of airgun:          GI Gun
    Volume:                  150 cu.in (G:45 cu.in, I:105 cu.in) 
    Air pressure:            13.5MPa
    Source depth:            2 m 
    Depth sensor:            No
    Gun Controller:          Hotshot ver. 3.3000

    Air Compressor 
    Manufacturer:            Service Engineering co., ltd 
    Type of machine:         4SA30-A150K
    Air supply Capacity:     2.0 m3/min.


    Recording System 
    Manufacturer:            GEOMETRICS
    Type of system:          Geode ver. 11.1.69.0
    Recording format:        SEG-D 8058 Rev.1
    Recording length:        7,500 msec
    Water Delay:             0 msec
    Sample rate:             1 msec 
    High cut filter:         None 
    Low cut filter:          None 
    Recording media:         Hard Disk

    GPS System 
    Manufacturer:            Fugro 
    Type of system:          MultiFix6
    DGPS Reference Station:  G2 Reference Station (ASAT)

    Navigation System
    Manufacturer:            MARIMEX JAPAN
    Type of system:          Nav log ver. 2.2.7

    Shot Point Geometry
    Time mode shooting:      ture mode

    Geodetic Parameter
    Spheroid:                WGS84
    Semi-major Axis:         6,378,137 m
    Inverse Flattening:      298.26
    Projection:              U.T.M Zone18


(4) Data process and Archives

    Figure 4-1-4 shows the data processing flow to filtered section. 
Other details of data acquisition and processing of Single channel 
seismic survey are attached as below.

    Data
    Nav_Raw (.csv format): position logging data 
    SEG-D_Raw (.sgd format): Raw data
    SEG-Y_Raw (.sgy): Transform data into SEG-Y from SEG-D_Raw data 
    SEG-Y_filetr (.seg): Filtering data of SEG-Y


    BMP (.BMP format)
    Bitmap profile of SEG-Y data for each lines.
    
    
Fig.4-1-2: The location of SCS survey lines 3 and 4.



Table 4-1-1: Position, length and the azimuth in formation of each
             survey line.

NME SINGLE CHANNEL SEISMIC SURVEY LINE LIST   MR16-09_leg.2

                                                                                Direc-
Line     Date      Time    Passing  Shot       Vessel Position         Length    tion    
 No.    (UTC)      (UTC)   Point    No.       Lat.          Lon.         [m]     [deg]  
————  —————————  ————————  ———————  ————  ————————————  ————————————  ————————  ——————
1     2017/1/23   2:24:43  F.S.P    1001  45-56.33835S  75-56.36719W  64,063.3  251.51   
      2017/1/23   3:05:43  F.G.S.P  1174  45-57.06688S  75-59.90295W       
      2017/1/23  10:54:06  L.G.S.P  3682  46-06.62773S  76-43.32138W      
      2017/1/23  10:58:50  L.S.P    3705  46-06.71562S  76-43.73703W      

2     2017/1/25   2:17:12  F.S.P    1001  45-55.04196S  75-50.95871W  18,707.9  251.51   
      2017/1/25   2:17:12  F.G.S.P  1001  45-55.04196S  75-50.95871W       
      2017/1/25   4:57:26  L.G.S.P  1794  45-58.12477S  76-04.74792W       
      2017/1/25   4:57:26  L.S.P    1794  45-58.12477S  76-04.74792W       

3_0*  2017/1/26  20:23:00  F.S.P    1001  47-52.64648S  75-56.24817W  67,473.6  269.01  
      2017/1/26  20:23:00  F.G.S.P  1001  47-52.64648S  75-56.24817W       
      2017/1/27   5:58:29  L.G.S.P  3859  47-52.52037S  76-50.38330W       
      2017/1/27   5:58:29  L.S.P    3859  47-52.52037S  76-50.38330W      

4_0   2017/1/28  21:24:31  F.S.P    1001  47-57.88422S  75-57.24289W   4,983.2  278.96   
      2017/1/28  21:24:31  F.G.S.P  1001  47-56.75629S  75-57.24289W       
      2017/1/29  22:15:20  L.G.S.P  1253  47-57.37907S  76-01.17737W       
      2017/1/29  22:15:20  L.G.S.P  1253  47-57.37907S  76-01.17737W       

4_1†  2017/1/28  22:34:36  F.S.P    1001  47-57.23190S  76-02.19543W  56,647.4  278.96   
      2017/1/28  22:34:36  F.G.S.P  1001  47-57.23190S  76-02.19543W       
      2017/1/29  7:59:55   L.G.S.P  3807  47-51.93878S  76-46.98715W       
      2017/1/29  7:59:55   L.S.P    3807  47-51.93878S  76-46.98715W       
—————————————————————————————————————————————————————————————————————————————————————————
*SP No.2737 - SP No.2788 = Point 76-28W transit. SP3456(FF3456) is most close to Line4_1.
†SP3514(FF3514) is most close to Line3. 


Fig. 4-1-3: Image of the Single Channel Seismic Survey system.

Fig. 4-1-4: Seismic data processing flow to filtered section for MR16-09 
            Leg 2.


4.2  Sediment Core

4.2.1  Site survey (bathymetry and sediment structure) observations

(1) Personnel

    Kana Nagashima (JAMSTEC); nagashimak@jamstec.go.jp Frank Lamy (Alfred 
    Wegener Institute); Frank.Lamy@awi.de
    Helge Arz (Ernst-Moritz-Arndt-University Greifswald); 
              helge.arz@io-warnemuende.de 
    Wataru Tokunaga (NME), Operation Leader; tokunagaw@nme.co.jp
    Koichi Inagaki (NME); inagakik@nme.co.jp 
    Yutaro Murakami (NME); murakamiy@nme.co.jp


(2) Objective

     To find best location taking the sediment for paleoceanography, site 
survey was conducted using the Multi-narrow Beam Echo Sounding system 
(MBES), SEABEAM 3012 (L3 Communications ELAC Nautik GmbH) and Sub-Bottom 
Profiler (SBP), Bathy 2010 (SyQwest Incorporated) on R/V MIRAI. SBP 
system collected vertical information of sediments.


(3) Measured parameters

     System configuration, performance and data acquisition of SEABEAM 
3012 and Bathy 2010 systems showed “3.2 Bathymetry (Sea beam, sub-bottom 
profiler)”.


(4) Preliminary results

     Figures 4.2.1-1 to 4.2.1-5 show survey maps and sub-bottom profiles 
for Station 02, 03, 08 and 10. Sediment coring was conducted at the 
stations using multiple piston coring system. Geographic positions of 
each station were shown in Table 4.2.1-1 below.


(5)Date archive

      All data are submitted to JAMSTEC Data Management Group (DMG) and 
is currently under its control and will be opened to public via “R/V 
MIRAI Data Web Page” in JAMSTEC homepage.








Table 4.2.1-1: Position of each coring station during MR16-09 Leg.2 
               cruise

Date             Sta-               Water         Position          Core 
(UTC)      Core  tion               Depth   Latitude   Longitude   Length
yyyymmdd    ID   Name    Location   (m)       (°S)       (°W)       (cm)
—————————  ————  —————  ——————————  —————  ——————————  ——————————  ——————
2017/1/22  PC01  St.02  Guafo Area  1,535  46-04.2714  75-41.2293   534.5
2017/1/22  MC01  St.02  Guafo Area  1,537  46-04.2885  75-41.2226     -
2017/1/23  PC02  St.03  Off Taitao  2,793  46-04.2316  76-32.0952  1273.0
2017/1/23  MC02  St.03  Off Taitao  2,787  46-04.2249  76-32.0902     -
2017/1/27  PC03  St.08  Off Taitao  3,082  46-24.3180  77-19.4499  1753.0
2017/1/31  PC04  St.10  Off Chile   3,848  50-48.3254  79-07.0752  1695.0
2017/1/31  MC04  St.10  Off Chile   3,851  50-48.3381  79-07.0823     -


Fig. 4.2.1-1: Bathymetric map (left) and sub-bottom profile (right) 
              around station 02 (coring site of PC01 and MC01).

Fig. 4.2.1-2: Bathymetric map (top) and sub-bottom profile (bottom) 
              around station 03 (coring site of PC02 and MC02).

Fig. 4.2.1-3: Bathymetric map (top) and sub-bottom profile (bottom) 
              around station 08 (coring site of PC03).

Fig. 4.2.1-4: Bathymetric map (left) and sub-bottom profile (right) 
              around station 10 (coring site of PC04 and MC04).


4.2.2  Piston corer system (PC)

(1) Personnel

    Yusuke Sato (Marine Works Japan Co. Ltd); satoy@mwj.co.jp
    Ei Hatakeyama (Marine Works Japan Co. Ltd); hatakeyamae@mwj.co.jp Yohei 
    Katayama (Marine Works Japan Co. Ltd); katayamay@mwj.co.jp


(2) Objective

    Collection of sea floor sediment


(3) Instruments and Method

    The piston corer system (PC) is composed of the head of the corer, 
barrels, piston, catcher, bit, trigger and pilot core sampler. The 
duralumin pipes are used for the barrel. A total of 15 or 20 m-long 
duralumin pipe is composed of three or four 5 m segments which are 
combined one another by stainless joint sleeves. We used a 74 mm long 
type pilot corer for a pilot core sampler. We used inner liners: 
polycarbonate liner tubes (Inner type). A compass with inclinometer was 
attached above the weight of the corer to examine performance of the PC. 
Diagram of PC is shown in the Fig. 4.2.2-1.

    In the Inner type piston corer, it pulls out inner tubes only from 
the duralumin pipes and the sediment can be collected. The inner tubes 
filled by sediments are cut with the handy cutter every 1 m after taking 
out from the barrel. The sediment sections are longitudinally cut into 
working and archive halves by a splitting devise and a stainless wire. 
After splitting, both cores are putted white pins at interval of 2 cm and 
orange pins at interval of 10 cm.
    Specification of the piston corer system is shown below.
        Head of the corer Main unit (Stainless, Lead): 
            Weight; 1.3 ton
    Barrel (Duralumin): 
        Length; 5 m
        Inner diameter; 80 mm 
        Outer diameter; 92 mm
    Inner tube (Polycarbonate): 
        Length; 5 m
        Inner diameter; 74 mm 
        Outer diameter; 78 mm


(4) Winch operation

    When we started lowering, a speed of wire out was set to be 0.2 m/s., 
and then gradually increased to the maximum of 1.0 m/s. PC were stopped 
at a depth about 100 m above the sea floor for 3 minutes to reduce any 
pendulum motion of the system. After the PC were stabilized, the wire was 
stored out at a speed of 0.3 m/s, and we carefully watched a tension 
meter. When the corers touched the bottom, wire tension abruptly 
decreases by the loss of the corer weight. Immediately after confirmation 
that the PC hit the bottom, wire out was stopped and rewinding of the 
wire was started at a dead slow speed (~0.3 m/s.), until the tension 
gauge indicates that the PC were lifted off the bottom. After leaving the 
bottom, winch wire was wound in at the maximum speed.


(5) Results

    Details of coring positions and core lengths are shown are shown in 
Table 4.2.1-1 and Appendix 1 (Coring information).


Fig. 4.2.2-1: Diagram of Piston corer system.


4.2.3  Multiple Corer system (MC)

(1) Personnel

    Yusuke Sato (Marine Works Japan Co. Ltd); satoy@mwj.co.jp
    Ei Hatakeyama (Marine Works Japan Co. Ltd); hatakeyamae@mwj.co.jp Yohei 
    Katayama (Marine Works Japan Co. Ltd); katayamay@mwj.co.jp


(2) Objective

    Collection of surface sediment


(3) Instruments and Methods

    Multiple corer (MC) consists of body (620 kg in weight) and eight 
sub-corer attachments. Acryl pipe and polycarbonate pipe are used for the 
sediment coring. The pipes are 60 cm in length, and the diameter is 74 
mm.

    For MC02 and MC04, attached Water sampling system without off line 
camera and light. Water sampling system attaches four Niskin bottles (8-
liter), SBE 39 temperature (pressure optional) recorder and Magnet switch 
data logger to the body.


(4) Winch Operation

    When we starts lowering the MC, a speed of wire out is set to be 0.2 
m/s., and then gradually increased to be 1.0 m/s. The MC is stopped at a 
depth about 50 m above the sea floor for 3 minutes to reduce any pendulum 
motion of the sampler. After the sampler is stabilized, the wire is 
stored out at a speed of 0.3 m/s., and we carefully watch a tension 
meter. When the MC touches the bottom, wire tension leniently decreases 
by the loss of the sampler weight. After confirmation that the MC touch 
seafloor, the wire out is stopped then another 3~5 m rewinding. The wire 
is started at dead slow speed, until the tension gauge indicates that 
the corer is lifted off the bottom. After leaving the bottom, which wire 
is wound in at the maximum speed. The MC came back ship deck, sub-corer 
attachments and Niskin bottles or off line camera were detached from the 
main body.


(5) Results

    Details of coring position and core length are shown in the Appendix 
1 (Coring Information）


4.2.4  Multi sensor core logger (MSCL)

(1) Personnel:

    Kazuma Takahashi (Marine Works Japan Ltd.); takahashik@mwj.co.jp


(2) Objectives

    To understand characteristics of sediment samples and to correlate 
different cores, physical properties, magnetic susceptibility was taken 
by using the whole round core sections before splitting and the GEOTEC 
multi-sensor core logger (MSCL).


(3) Measured Parameters

    MSCL has sensors of the gamma-ray attenuation (GRA), the P-wave 
velocity (PWV) and the magnetic susceptibility (MS). Whole-core samples 
are used for the logger measurements.


(4) Instruments and Methods

    Whole-core samples are kept in the laboratory for the night to 
equalize the sediment temperature with the room temperature. Measurement 
interval was every 1 cm for all cores (Only PC01 core was measured by 2 
cm interval).

    GRA is measured a gamma ray source and a detector, which are mounted 
on the center sensor stand. A narrow beam of gamma ray is emitted by 
Cesium-137 (137Cs, energies principally at 0.662 MeV). The detector 
comprises a scintillator (a 2” diameter and 2” thick NaI crystal). The 
photon of gamma ray is collimated through 5 mm diameter in rotating 
shutter at the front of the housing of 137Cs. These photons pass through 
the center of the whole core and are detected the scintillation detector 
on the other side. The detector comprises a scintillator (a 2” diameter 
and 2” thick NaI crystal). The calibration of GRA assumes a two-phase 
system model for sediments, where the two phases are the minerals and the 
interstitial water. Aluminum has an attenuation coefficient similar to 
common minerals and is used as the mineral phase standard. Pure water is 
substituted as the interstitial-water phase standard. The actual standard 
consists of a telescoping aluminum rob (five elements of varying 
thickness) mounted in a piece of core liner and filled with pure water. 
GRA was measured with 10 seconds counting.

    PWV is measured by two oil filled the Acoustic Rolling Contact (ARC) 
transducers, which are mounted on the center sensor stand with the gamma 
system. These transducers measure the velocity of P-wave through the 
whole core and the pulse amplitude.

    MS is measured by the loop sensor of 100 mm diameter made by the 
Bartington Instruments Ltd. An oscillator circuit in the sensor produces 
a low intensity (approx. 80 A/m RMS) non-saturating, alternating magnetic 
field (0.565 kHz). MS was measured with 1 second. The measured raw data 
are shown in Fig. 4.2.4-1∼4. After the MSCL measurement, whole-core 
samples are cut into Working and Archive halves by a splitting devise and 
a nylon line.
    

Fig. 4.2.4-1: MS raw data and color data (PC01; Guafo area).

Fig. 4.2.4-2: MS raw data and color data (PC02; Off Taitao).

Fig. 4.2.4-3: MS raw data and color data (PC03; Off Taitao).

Fig. 4.2.4-4: MS raw data and color data (PC04; Off Chile).



4.2.5  Core color reflectance (CCR)

(1) Personnel:

    Yuki Miyajima (Marine Works Japan Ltd.); miyajimay@mwj.co.jp


(2) Objectives

    To understand characteristics of sediments such as lithology, redox 
condition, relative carbonate content, organic matter content and certain 
inorganic compounds, color reflectance was measured for split half 
sediments.


(3) Measured Parameters

    There are different systems to quantify the color reference for soil 
and sediment measurements, the most common is the L*a*b* system, also 
referred to as the CIE (Commision International d’Eclairage) LAB system. 
It can be visualized as a cylindrical coordinate system in which the axis 
of the cylinder is the lightness variable L* ranging from 0% to 100%, 
and the radii are the chromaticity variables a* and b*. Variable a* is 
the green (negative) to red (positive) axis, and variable b* is the blue 
(negative) to yellow (positive) axis. Spectral data can be used to 
estimate the abundance of certain components of sediments.


(4) Instruments and Methods

    Core color reference was measured by using the Konica Minolta CM-700d 
reference photo spectrometer using 400 to 700nm in wavelengths. This is a 
compact and hand-held instrument, and can measure spectral reflectance of 
sediment surface with a scope of 3 mm diameter. To ensure accuracy, the 
CM-700d was used with a double-beam feedback system, monitoring the 
illumination on the specimen at the time of measurement and automatically 
compensating for any changes in the intensity or spectral distribution of 
the light.

    The CM-700d has a switch that allows the specular component to be 
include (SCI) or excluded (SCE). We chose setting the switch to SCE. The 
SCE setting is the recommended mode of operation for sediments in which 
the light reflected at a certain angle (angle of specular reflection) is 
trapped and absorbed at the light trap position on the integration 
sphere.

    Calibrations are zero calibration and white calibration before the 
measurement of core samples. Zero calibration is carried out into the 
air. White calibration is carried out using the white calibration piece 
(CM-700d standard accessories) without crystal clear polyethylene wrap.

    The color of Archive half core was measured on every 1 cm through 
crystal clear polyethylene wrap. Measurement parameters are displayed 
Table 4.2.5-1. The measured raw data are summarized in Fig. 4.2.3-1∼4.


Table 4.2.5-1: Measurement parameters.

    Instrument     Konica Minolta Photospectrometer CM-700d
    Software       Spectra Magic NX CM-S100w Ver.2.51
    Illuminant     d/8 (SCE)
    Light source   D65
    Viewing angle  10 degree
    Color system   L*a*b* system



4.2.6  Core photograph

(1) Personnel:

    Mika Yamaguchi (Marine Works Japan Ltd.); yamaguchim@mwj.co.jp


(2) Objectives

    Photographs were taken to observe sedimentary structures of the 
cores.


(3) Instruments and methods

    Each of Archive half core photographs were taken using a digital 
camera (Camera body: Nikon D90/ Lens: Nikon AF-NIKKOR 28 mm 1:1.8 D). 
When using the digital camera, shutter speed was 1/15 ~ 1/40 sec, F-
number was 4.5~5.6, sensitivity was ISO 200. File format of raw data is 
JPEG. Details for settings were included on property of each file.
  


4.2.7  Visual Core Description

(1) Personnel

    Frank Lamy (Alfred Wegener Institute); Frank.Lamy@awi.de
    Helge Arz (Ernst-Moritz-Arndt-University Greifswald); 
    helge.arz@io-warnemuende.de


(2) Summary

    Visual core description was made on the split surface of the archive 
half sections. The split surface was scraped using a plastic card to 
expose fresh surface. Lithological and sedimentological features were 
described in Fig. 4.2.7-1∼5 (detailed description for each section is in 
Appendix 1). Primary sediment lithologies were first described directly 
on the core and later confirmed/modified by a qualitative and 
quantitative microscopic examination of representatively taken smear 
slides (smear slide result table see in Appendix 1). We adopted the IODP-
style nomenclature for lithological description (e.g., Mazzullo et al., 
1988) with some modifications.
 
    Cores PC01 and PC02 were retrieved close to core locations of the MD159 
cruise in 2007 (MD159 – PACHIDERME, IMAGES XV, 2007; cores MD07-3088 and 
MD07-3119, respectively) with the advantage that Siani et al. (2010) 
provides a detailed chronostratigraphic framework for core PC01 and the 
upper part of PC02 based on radiocarbon and tephrochronological data. 
Onboard GEOTEK measurement of the magnetic susceptibility and GRAPE 
density were used for a detailed correlation between PC01 and MD07-3088 
used for establishing of a preliminary chronostratigraphy. Core PC01 
consists in a fairly uniform succession of olive black to grayish olive 
nannofossil/diatom and silt bearing to silty clay (Fig. 4.2.7-1, 6). 
Magnetic susceptibility is generally quite low and the correlation to 
core MD07-3088 (Fig. 4.2.7-6∼7) suggests a basal age of 17.5 kyrs BP, 
thus covering most of the glacial Termination I and the Holocene.

    Further offshore, two piston cores of 13 and 17 m were retrieved at 2786 
and 3067 m water depth, respectively (Station 03, core PC02 and Station 
08, core PC03) from the Chile Rise showing a well-developed 
stratification in the seismic record. The cores are well comparable and 
consist of dark olive gray to grey silt- diatom- and occasionally 
nannofossil-bearing clay to clayey nannofossil ooze with some thin silt 
and sandy layers that become more frequent in the lower part of the cores 
and which could be ascribed mainly to turbididic deposits and perhaps 
also to tephra layers. In core PC03 magnetic  susceptibility is low in 
the upper and the lowermost three meters characterizing sediment with  an 
increased amount of biogenic components. Most of the core, however, 
consists of glacial clayey sediments with an alternating contribution of 
coarser grained siliciclastics. At about 9.1 m a prominent 15 cm thick 
brownisch tephra layer interrupts the normal sedimentation (Fig. 4.2.7-
8). The biogenic-rich basal three meters were deposited most probably 
during the last interglacial Marine Isotope Stage (MIS) 5 and the basal 
age of the core is suggested to be around 120-130 kyrs BP (Fig. 4.2.7-9).

    Core PC04 was cored in 3852 m water depth in the deeper Southeast Pacific 
south of the Chile Rise at (~50.8°S) ~200 nm off the Chilean coast. 
Sediment acoustic profiles from this region revealed well-stratified 
deposits with significantly increased acoustic penetration. With respect 
to major lithologies, the core is quite different from the shallower 
continental margin cores further to the northeast. Overlain    by a 
yellowish brown foraminifera and diatom-bearing nannofossil ooze, dark 
olive to greenish gray clays dominate the sequence. The clay sequence is 
intercalated with lighter foram-bearing calcareous oozes, the base of 
which is commonly strongly bioturbated. Calcareous oozes are found at ~3-
4, 9-10, ~13, and 14.5-15.5 m. At 14.5-15.5 m the calcareous oozes 
consist of a compact, stiff, white nannofossil ooze (Fig. 4.2.7-10). The 
recovered sequence in PC04 is quite similar to those described in cores 
PS97/112-1 and 114-2 that were recovered during the RV Polarstern cruise 
PS97 in 2016 about 120 nm offshore Chile 4° further to the south (55°S) 
from a comparable water depth of ~3850 m (Expedition PS97 cruise report, 
2016). The records of cores PC04 and PS97/114-2 correlate convincingly 
(Fig. 4.2.7-11). The tentative correlation to the Lisiecki & Rymo (2005) 
isotope stack and to the Antarctic climate records suggests that the core 
PC04 reaches back to the Marine Isotope Stage 12 (430 kyrs BP) and has an 
average sedimentation rate of about 4 cm/kyr. When all PC cores are 
compiled into one graph, an almost linear relationship between the 
average sedimentation rate and the distance to the Chilean coast becomes 
evident. This relationship mainly describes the diminishing influence to 
the west of the detrital sediment input from the glaciated southernmost 
Andes (Fig. 4.2.7-12).


References:

Kissel C. and cruise participants (2007): MD159 – PACHIDERME IMAGES XV 
    Cruise report. IPEV, Les rapports de campagnes a` la mer, 83 pp.
Lamy, F. and cruise participants (2016): The Expedition PS97 of the 
    Research Vessel POLARSTERN to the Drake Passage in 2016. Reports on 
    Polar and Marine Research 701, 157 pp. doi:10.2312/BzPM_0701_2016
Mazzullo, J., Meyer, A. and Kidd, R. (1988) New sediment classification 
    scheme for the Ocean Drilling Program. Appendix I, In “Handbook for 
    shipboard sedimentologists” eds. Mazzullo, J. and Graham, A. G., ODP 
    Technical Note, 8, 44-63.
Siani, G., Colin, C., Michel, E., Carel, M., Richter, T., Kissel, C., and 
    Dewilde, F. (2010): Late Glacial to Holocene terrigenous sediment 
    record in the Northern Patagonian margin: Paleoclimate implications, 
    Palaeogeogr. Palaeocl., 297, 26–36.



Fig. 4.2.7-1: Visual core description for PC01.

Fig. 4.2.7-2: Visual core description for PC02.

Fig. 4.2.7-3: Visual core description for PC03.

Fig. 4.2.7-4: Visual core description for PC04.

Fig. 4.2.7-5: Legend for core description.

Fig. 4.2.7-6: Graph combining the GEOTEK magnetic susceptibility 
              measurements on core PC01 with the smear slide 
              examinations on the core.

Fig. 4.2.7-7: Correlation of the magnetic susceptibility records of dated 
              core MD07-3088 (Siani et al. 2010) and PC01 with PC01        
              sedimentation rates.

Fig. 4.2.7-8: Graph combining the GEOTEK magnetic susceptibility 
              measurements on core PC03 with the smear slide 
              examinations on the core.

Fig. 4.2.7-9: Correlation of the magnetic susceptibility records of cores 
              PC01, PC02, and PC03 with approximate basal age and average 
              sedimentation rates.

Fig. 4.2.7-10: Graph combining the GEOTEK magnetic susceptibility 
               measurements on core PC04 with the smear slide 
               examinations on the core.

Fig. 4.2.7-11: Correlation of the magnetic susceptibility and GRAPE 
               density data of core PC04 and core PS97/114-2 on a common 
               PS97/114-2 depth scale. Gray bars tentatively indicate the 
               interglacial Marine Isotope Stages 1 to 11.

Fig. 4.2.7-12: Close to linear relationship between the average 
               sedimentation rates of cores PC01, PC02, PC03, and PC04 
               and their distance to the Chilean coast.



4.3  Dredge

4.3.1 Dredge System

(1) Personnel

    Yusuke Sato (Marine Works Japan Co. Ltd); satoy@mwj.co.jp
    Ei Hatakeyama (Marine Works Japan Co. Ltd); hatakeyamae@mwj.co.jp Yohei 
    Katayama (Marine Works Japan Co. Ltd); katayamay@mwj.co.jp


(2) Objective

    Collection of seafloor rocks and sediments


(3) Instruments and Methods

    The dredge sampler system used during MR16-09_Leg2 cruise is shown in 
Fig.4.1.3-1, showing the configuration of Transponder, Winch wire, Lead 
wire, Chain, Weight, Pipe dredge, Life wire, Fuse wire and Main Chain-bag 
Dredge.


Fig. 4.1.3-1: Dredge system with a box-type dredge.


    Transponder: Transponder is an equipment that receives acoustic 
signals and automatically sends out another signal in reply. In this 
cruise, it is used to make sure the roughly position of the dredge 
sampler system in water. It was put on the winch wire in two cramps with 
special housing.

    Winch wire: Diameter of winch wire is 17mm. It is 0.983kg weight per 
one meter in water (i.e. about 983kg for 1,000m in the sea water) and 
having a 24.2t breaking force.

    Lead wire: This wire is prepared for protection against damage to the 
winch wire, jointed by  shackles (3.15t SUS) and a swivel (5t). It is 
iron wire of 12mm diameter, 200m long and a 7.24t breaking force.

    Chain: Chain (19mm diameter, 5m long) is used to stabilize the dredge 
sampler and was jointed to the lead wire with a swivel (5t) and shackles 
(φ19).

    Weight(50kg per each): The weight is used to assure the dredge 
sampler is on the bottom as can be observed by the tension meter in the 
operation room, and linked by shackles (φ16) to the chain together with a 
swivel (1t), fuse wire (8mm diameter, 0.25m long) and life wire (10mm 
diameter, 1.7m long).

     Pipe dredge: Pipe dredge assumes the function as the backup of the 
main chain-bag dredge. This is linked as same as the weight. (Life wire 
is 1m long)

     Life wire (chain-bag): End of the life wire (10mm diameter, 7 m 
long) is connected parallel with fuse wire, and the other end is 
connected with the middle part of the chain-bag. In the case of fuse wire 
is broken by a big bite or anchoring, life wire works to prevent the 
dredge from lost, and keeps the samples in the box type bucket.

    Fuse wire: Fuse wire (8mm diameter, 0.25m long) is prepared to 
release the dredge from big bites that might damage the winch wire. It is 
jointed to the chain with a swivel (1t or 3t) and shackles in the main 
chain-bag dredge.

    Chain-bag dredge: The square type dredge consists of box type jaw 
(60*45 cm mouth, 60*27 cm throat), handle (26mm diameter, 85cm long) and 
steel chain-bag (6 mm diameter, 100cm long) with box type bucket 
(27*60*50cm) made from stainless steel (5mm thick). The bucket can 
recover all kinds of sediments on seafloor, it was jointed with shackles 
to the 0.25 m fuse wire. About details of wire diameter and breaking 
force are written in below.

                       Diameter  Breaking Force
                       ————————  ——————————————
                          6mm        1.81t
                          8mm        3.22t
                         10mm        5.03t
                         12mm        7.24t


(4) Operation note

    Operation of dredging was conducted on the basis of following strategies.

      i. Preparation
         We set the start and end point for dragging of the dredge system 
         on the basis of the contour map.

     ii. The points should be checked before and during deploying the 
         dredge system

         Carefully check on “no loose connections” between the main body, 
         weight, pipe dredge, wires, and chain.

         Connect transponder to 50 m of the main wire.

    iii. Approaching to bottom
         Until reach the dredge system to about 100 m depth above the 
         seafloor, the main wire should be rolled out 1.0 m/s.
	
         Keep stopping of wire-out about 3 min, and position and movement 
         of transponder should be checked.

         Wire out restart by the speed of 0.3 m/s until dredge on bottom.

    iv.  On bottom
         If we find that the position of transponder is just beneath of 
         stern immediately before the dredge system on bottom, ship 
         should be start to move to the end point in 0.5 knot.

         Reach of the dredge system to bottom should be identified on the 
         basis of reduction of tension of the main wire.

         The main wire is NOT further rolled out after the dredge system 
         on bottom. The speed of ship increase to 1.0 knot.

         If slight increasing of tension is identified, the speed of ship 
         decrease to 0.5 knot, and several tens of meters (depend on 
         inclinations of slope) of the main wire should be rolled out.

         Important point: speed of the dredge system should NOT be more 
         than 1 knot.


         In the case of the main wire is rolled in, ship should keep 
         position, and speed of wire is 0.3 m/s.

     v.  Off bottom
         We can find out off bottom of the dredge system, if carefully 
         watch the changing of tension of the main wire on the tension 
         meter.

         The altitude of 200 or 250 m for transponder is the most 
         important information to identify completely off bottom of the 
         dredge system.

         The speed of wire-in should be 0.5 m/s just after off bottom, 
         and increase to 1.0 m/s if altitude of transponder is more than 
         250 m.


4.3-2  Dredge result

(1) Parsonnel

    Natsue Abe (JAMSTEC) 
    Shiki Machida (JAMSTEC) 
    Ryo Anma (Univ. of Tsukuba)
    Yuji Orihashi (The Univ. of Tokyo)


(2) Introduction

    The Chile Triple Junction (CTJ; Figure 4.3-2-1) is located where 
subducting spreading centers and accompanying fracture zones of the Chile 
Ridge system meet with the South American plate. This area is 
tectonically unique in that the ridge subduction accompanies obduction of 
an ophiolite nearby (namely, the Taitao ophiolite), providing an 
excellent opportunity to study the magmatism involved in the ridge 
subduction processes on land. Our continuous effort toward understanding 
this magmatism, including the R/V Mirai MR08-06 cruise (see Abe, 2009; 
Harada, 2009), revealed that intensive fore-arc granite magmatism took 
place during the 6 Ma ridge subduction event (Anma et al., 2009) due to 
partial melting of the subducting oceanic crust under garnet-free 
conditions (Kon et al., 2013) to produce I-type granites (Shin et al., 
2015), sediments subducted along a fracture zone were incorporated into 
S-type magmatism in the fore-arc region (Anma and Orihashi, 2013; Shin et 
al., 2015). Based on these, we planned new dredge sampling for the MR16-
09 cruise.


Fig. 4-3-2-1: Large area map around survey area.


(3) Objective

    The purpose of the dredge sampling in the CTJ area is to collect 
rock/sediment samples that help to understand solid earth recycling 
processes occurring/occurred due to subduction of the Chile  Ridge 
system. Target rocks for the dredge operations are 1) igneous rocks 
distributed in the fore-arc region, 2) MORBs from the Segment 1 of the 
Chile ridge system and fracture zones, 3) rocks comprising seamounts 
nearby the subducting Chile Ridge. The dredge in the fore-arc region aims 
to find unknown igneous activities that are equivalent to the magmatism 
observed in the Taitao ohiolite-granite complex (Shin et al., 2015). The 
dredge of MORBs and seamount rocks aims to understand compositions of 
input materials   that subduct and eventually melt to form arc magmas at 
deeper part of the ridge subduction zone.


(4) Results

    Three dredge operations (D11~D13) were performed for the input rocks 
(MORBs and seamount). The positions of each dredge hauls are listed in 
the Table 4-3-2-1. Detail description of samples and photo image, and the 
table of all sample list are attached as Appendix. D11 to the seamount in 
the west of Segment 1 recovered pebbles of sub-rounded chert and 
sandstone, supposedly drop-stones, embedded in mud. Thus, the frank of 
the seamount was covered by a thick sediment. D12 operation to collect 
MORB from the Segment 1 was very successful and recovered sum of ~120 kg 
of basalts partly with quenched glassy rinds. In contrast, D13 to a 
neighboring mound to the D12 site recovered only few small pieces of 
volcanic glass (perhaps contamination of D12 dredge) in mud. Furthermore, 
a dredge operation was planned to collect altered basalts from the 
fracture zone between Segment 1 and Segment 2 spreading ridges. However, 
due mostly to wind and current of undesirable direction, this operation 
was canceled.
    
    Four dredge operations (D14~D17) were performed to find unknown 
igneous activities in the accretionary complex developed around 47°47’S. 
We initially planed for dredging nearby the Taitao peninsular for the 
investigation of the unknown igneous activities, but this attempt was 
abandoned due to rejection of applied permission for the operation in the 
Chilean water. As a contingency plan, this area was chosen to find 
igneous activities due to a ridge subduction event that took place ~14 Ma 
ago. All dredge operations were successful and we recovered siltstones 
and sandstones with gravels and conglomerates with different degree of 
consolidation. The degree of consolidation was measured using a needle 
penetration tester onboard. The sedimentary rocks from the seaward ridge 
(D14) were variously consolidated and contain chaotic rocks and various 
deformation structures including composite foliation and folds developed 
mainly in mudstones, and calcite veins. Rocks from a landward ridge 
(D15~17) contain turbidite with various grain size, sedimentary 
structures, and different degree of consolidation. No calcite vein was 
observed and deformation texture was less developed comparing to the 
seaward ridge. These sedimentary rocks will be further examined to 
understand development of new accretionary prism after the ridge 
subduction event. A piece of granite was recovered from D16 operation. 
Further investigation will be made to determine the age of this rock.


(5) References

Abe, N. (2009) MIRAI Cruise Report: MR08-06 Leg1, JAMSTEC Cruise Report, 
    140 p.
Anma, R., Armstrong, R., Orihashi, Y., Ike, S., Shin, K-C., Kon, Y., 
    Komiya, T., Ota, T., Kagashima, S., Shibuya, T., Yamamoto, S., 
    Veloso, E. E., Fannin, M. and Herve, F. (2009) Are the Taitao 
    granites formed due to subduction of the Chile ridge? Lithos, 113, 
    246-258.
Anma, R. and Orihashi, Y. (2013) Shallow-depth melt eduction due to ridge 
    subduction: LA-ICPMS U-Pb igneous and detrital zircon ages from the 
    Chile Triple Junction and the Taitao Peninsula, Chilean Patagonia. 
    Geochemical Journal, 47, 149-165.
Harada, N. (2009) MIRAI Cruise Report: MR08-06 Legs. 2 and 3, JAMSTEC 
    Cruise Report, 181 p.
Kon, Y., Komiya, T., Anma, R., Hirata, T., Shibuya, T., Yamamoto, S. and 
    Maruyama, S. (2013) Petrogenesis of the ridge subduction-related 
    granitoids from the Taitao Peninsula, Chile Triple Junction area. 
    Geochemical Journal, 47, 167-183.
Shin, K-C., Anma, R., Nakano, T., Orihashi, Y. and Ike, S. (2015) The 
    Taitao ophiolite-granite complex, Chile: Emplacement of ridge-trench 
    intersection oceanic lithosphere on land and origin of calc-alkaline 
    I-type granites. Episodes, 38, 285-299.


Table 4-3-1: Position, depth, tension and hauling time information for 
             each dredge haul during MR16-09 Leg2. MR16-09 Leg2 Dredge 
             summary

                                                                                                                                          Depth (m)
                                                  On the bottom                                       Off the bottom                   ———————————————  Tension
   Date    Dredge   Location   ——————————————————————————————————————————————————  ——————————————————————————————————————————————————  On the  Off the    max    Survey
  (UTC)    number              Lat.(SOQ*)   Lon.(SOQ*)   Lat.{SOJ)    Lon .{SOJ)   Lat.(SOQ*)   Lon.( SOQ*)   Lat.(SOJ)   Lon.(SOJ)    bottom  Bottom     (t)     time
—————————  ——————  ——————————  ———————————  ———————————  ———————————  ———————————  ———————————  ———————————  ———————————  ———————————  ——————  ——————   ———————  ———————
2017/1/23   Dll    Off Taitao  46-l0.0787S  76-l6.3538W  46-10.12l9S  76-16.4333W  46-10.0917S  76-17.0023W  46-10.1550S  76-17.2010W   2,574   2,377     2.3    lhl0min
2017/1/24   D12    Off Taitao  45-52.45l4S  75-58.7050W  45-52.4510S  75-58.8027W  45-52.4599S  75-58.8688W  45-52.4718S  75-59.0717W   3,227   3,307     5.6    32min
2017/1/24   D13    Off Taitao  45-52.6695S  75-59.7638W  45-52.6187S  75-59.7023W  45-52.5500S  75-59.5170W  45-52.4482S  75-59.3372W   3,312   3,281     3.0    40min
2017/1/26   D14    Off Byron   47-46.3587S  76-25.6057W  47-46.3044S  76-25.6099W  47-46.3046S  76-24.8910W  47-46.2416S  76-24.8186W   3,080   2,658     4.3    lh35min
2017/1/26   D15    Off Byron   47-47.5231S  76-02.8022W  47-47.4710S  76-02.81l4W  47-47.3277S  76-02.6454W  47-47.2650S  76-02.6813W   1,930   1,755     4.8    lh0min
2017/1/28   D16    Off Byron   47-47.4854S  76-0l.8054W  47-47.4266S  76-01.8181W  47-47.2096S  76-0l.5343W  47-47.1330S  76-0l.5307W   1,831   1,511     2.6    lhllmin
2017/1/28   D17    Off Byron   47-47.2193S  76-02.8223W  47-47.1944S  76-02.6611W  47-46.9474S  76-02.5245W  47-46.8179S  76-02.5215W   1,656   1,435     3.0    lh2min
				
*SOQ = Transponder's position, SOJ = Ship's position


4.4  Biological Sample

     Zooplankton: Rationale and Methods for Sample Collection


(1) Personnel:

    Prof. Leonardo Castro (COPAS Sur Austral Center, Universidad de 
    Concepción, Chile.


(2) Rationale

    During the last years, the use of carbon and nitrogen isotopes has 
started to be widely utilized to study the structure of the food webs in 
marine ecosystems. Because enrichment of stable isotopes occurs along the 
trophic web, stable isotopes such as of carbon (13C) may be used to trace 
the original carbon source at the base of the web or, as in the case of 
nitrogen (15N) may be utilized as indicator of the trophic position 
organisms reaches along the web (Vander Zanden & Rasmussen 1999, Vander 
Zanden et al. 2001, Bode et al. 2003, 2007; Vargas et al. 2011, 
Montecinos et al. 2016).
    
    The information available on the marine pelagic community at the Cabo 
de Hornos Current off the Chilean Patagonia, on its major functional 
components and the trophic web structure, are very limited. This area, 
where water masses of different origin (SASW; ESSW, AAIW and EW) (Sievers 
& Silva 2006, Silva et al. 1997, 1998) converge in a narrow zone both in 
the horizontal and vertical domain, is expected to contain epi- and 
mesopelagic organism of diverse origin as well as trophic webs that 
channelize   organic carbon from different sources at different depths. 
Since some of the micronekton (i.e. myctophid fishes) and mesozooplankton 
components (i.e. euphausiids) may change their depth of residence during 
diel vertical migrations or as they develop, changes also in the carbon 
signature and trophic position of these organisms are also expected to be 
visualized along the water column.
    
    In the present study, utilizing mesozooplankton samples collected 
from different depths along the Cabo de Hornos Current, the structure and 
food web of the epi- and mesopelagic plankton community is assessed by 
means of stable isotope analyses of the key species zooplankton (and 
ichthyoplankton) and major functional groups. In principle, differences 
in the carbon and nitrogen signals (δ13C; δ15N) are expected locally at 
organisms residing the surface layer according to the influence of major 
water inputs from the continent (e.g. off the Boca del Guafo, Golfo de 
Penas; Estuarine Waters). Secondarily, differences are expected also in 
the vertical plane according to the most common residence layers of the 
major zooplankton/ichtyoplankton taxa as a result of the influence of the 
trophic webs associated to the major waters masses present in the area at 
different depths (SASW; ESSW and AAIW). This information, besides 
describing for the first time the complex structure of the zooplankton 
community, will provide insights on the potential importance of the 
alloctonous material ingress (organic carbon from the continent) to the 
Cabo de Hornos Current to subsidize the pelagic trophic webs of this 
Patagonian  offshore area.


(3) Methods

    Field work. During the MIRAI Cruise MR 16-09 Leg 2, stratified 
zooplankton samples were collected at 8 bio-oceanographic stations (Table 
1). At 7 of these stations, stratified zooplankton samples were collected 
through oblique tows with a Tucket Trawl net (1m2 mouth opening, 300um  
mesh, equipped with a GO flowmeter) from 3 (0-50m; 50-400 m; 400-600m) or 
more strata (up to 6 strata; maximum depth 600m) at day time hours. At an 
additional station, and due to harsh weather conditions, the stratified 
oblique sampling was switched to vertical tows with a WP2 net (60 cm 
mouth diameter, 300um mesh) from 3 depth ranges: 0-50m, 0-400m, 0-600m. 
On board, the zooplankton samples were splitted and one fraction was 
preserved in formaline 5% for zooplankton identification and counting,  
and another was frozen down to -80°C for stable isotope (δ13C; δ15N) 
analyses.

















Table 1: Summary of zooplankton samples collected during the MIRAI Cruise 
         MR 16-09 - Leg 2 along the Cabo de Hornos Current, showing 
         station number, type of net utilized, sampled depth range, and 
         number of subsamples preserved and frozen.

                         Sampled    Subsamples 
Station    Sampling    Depth Range  Formaline   Frozen    Total 
             gear          (m)         10%      -80°C   subsamples
———————  ————————————  ———————————  ——————————  ——————  ——————————
   1     Tucker trawl     0 - 400       1         1         2
                        400 - 50        1         1         2
                         50 - 0         1         1         2
                          0 - 600       1         1         2
                        600 - 400       1         1         2
                        400 - 0         1         1         2
   4     Tucker trawl     0 - 400       1         1         2
                        400 - 50        1         1         2
                         50 - 0         1         1         2
   8     Tucker trawl     0 - 400       1         0         1
                        400 - 50        1         1         2
                         50 - 0         1         1         2
                          0 - 600       1         0         1
                        600 - 400       1         1         2
   7     Tucker trawl     0 - 400       1         0         1
                        400 - 50        1         1         2
                         50 - 0         1         1         2
   9     Tucker trawl     0 - 400       1         0         1
                        400 - 50        1         0         1
                         50 - 0         1         0         1
  10     Tucker trawl     0 - 400       1         0         1
                        400 - 50        1         1         2
                         50 - 0         1         1         2
                        600 - 400       1         1         2
  11B    Tucker trawl     0 - 400       1         1         2
                        400 - 50        1         1         2
                         50 - 0         1         1         2
                        600 - 400       1         1         2
  12B    WP2              0 - 600       1         0         1
                          0 - 400       1         0         1
                          0 - 50        1         0         1
——————————————————————————————————————————————————————————————————
   8     7 Tucker      31 samples      31        21        52
stations     + 1 WP2


References

Bode, A., Carrera, P., Lens, S., 2003. The pelagic food web in the 
    upwelling ecosystem of Galicia (NW Spain) during spring: natural 
    abundance of stable carbon and nitrogen isotopes. ICES Journal of 
    Marine Science, 60: 11-22.
Bode, A., Alvarez-Ossorio, M.T., Cunha, M.E., Garrido, S., Peleteiro, 
    J.B., Porteiro, C., Valdes, L., Varela, M., 2007. Stable nitrogen 
    isotope studies of the pelagic food web on the Atlantic shelf of the 
    Iberian Peninsula. Progress in Oceanography, 74, 115-131.
Montecinos S., L R. Castro & S Neira. 2016. Stable isotope (δ13C and 
    δ15N) and trophic position of Patagonian sprat (Sprattus fuegensis) 
    from the Northern Chilean Patagonia. Fisheries Research 179 (2016) 
    139–147.
Sievers H.A. & N Silva. 2006. Masas de agus y circulación en los canales 
    y fiordos australes. En N. Silva y S Palma (Eds),"Avances del 
    conocimiento oceanográfico de las aguas interiores chilenas: Puerto 
    Mont a cabo de Hornos". Comité Oceanográfico Nacional. P Universidad 
    Católica de Valparaíso. Pp. 53-58.
Silva N, C Calvete & H. Sievers. 1997. Características oceanográficas 
    físicas y químicas de canales australes chilenos entre Puerto Montt y 
    Laguna San Rafael (Crucero Cimar-Fiordo l). Ciencia y Tecnología del 
    Mar 20: 23-106
Silva.N, C Calvete & H. Sievers. 1998. Masas de agua y circulación 
    general para algunos canales autrales entre Puerto Montt y Laguna San 
    Rafael, Chile (Crucero CIMAR Fiordo l). Ciencia y Tecnología del Mar 
    21. 17-48.
Vander Zanden, M.J., Rasmussen, J.B., 1999. Primary consumer delta C-13 
    and delta N-15 and the  trophic position of aquatic consumers. 
    Ecology, 80, 1395-1404.
Vander Zanden, M.J., Rasmussen, J.B., 2001. Variation in delta N-15 and 
    delta C-13 trophic fractionation: Implications for aquatic food web 
    studies. Limnology and Oceanography, 46, 2061-2066.
Vargas, C.A., Martinez, R.A., San Martin, V., Aguayo, M., Silva, N., 
    Torres, R., 2011. Allochthonous subsidies of organic matter across a 
    lake-river-fjord landscape in the Chilean Patagonia: Implications for 
    marine zooplankton in inner fjord areas. Continental Shelf Research, 
    31, 187-201.



4.5  Suspended Particles


(1) Personnel

    Humberto E. Gonzalez and Eduardo Menschel (Universidad Austral de Chile, 
    Valdivia and FONDAP-IDEAL center, Valdivia and Punta Arenas, Chile)


(2) Sampling and scientific motivation

    Two types of samples were collected:
    1) Particulate Organic Carbon (POC)
       Methods: From 1.0 to 2.5 Lt of water were filtrated through a pre-
       combusted glass fiber filters (Whatman GF/F). The filters were 
       stored frozen and at the laboratory were decarbonated (using HCl2 
       acid) and dried (at 50ºC overnight). The filter were sent to the 
       University of California at Davis for C and N elemental 
       composition and natural isotopes analysis.

       Scientific relevance: The POC constituted an important component 
       of the carbon pool in the ocean and a key component of the carbon 
       biogeochemical cycle (i. e.	carbon export to the deep sea).	It 
       is a relevant proxy of the food resources available to be 
       channeled through the microbial and particulate food webs in the 
       ocean. In addition, the natural isotope signature can give us 
       insights about the precedence (origin) of this POC.

    2) Microzooplankton (µzoo) composition and abundance:
       Methods: From 7.0 to 12.0 Lt of water were filtrated through a 20 
       µm nitex sieve and resuspended in a final volume of ca. 300 ml. 
       These samples were preserved with buffered lugol to further 
       analysis at the laboratory.

       Scientific relevance: The µzoo are an important component of the 
       heterotrophic functional groups of the plankton, especially in 
       open waters. Some of these groups, such as foraminifers, 
       radiolarians, can be used as paleoceanographic conditions.

       Almost no information on POC and µzoo from the deep ocean side of 
       the eastern south Pacific are available. The analysis of these 
       samples would contribute to fill the gap on the knowledge of the 
       quantity and quality of these components.


Station 1
21 Jan. 2017        Position (44º17S 75º36W)          Max. Depth = 1928 m
—————————————————————————————————————————————————————————————————————————
                Sampling   Filter  Water Volume   Water Volume
                 depth      (Nº)   Filtrated for  filtrated for 
                  (m)               POC (Lt)      µzoo (Lt)
              ———————————  ——————  —————————————  —————————————
                    0       135         1              10
                   10       552         1               7
                   25        32         1              7,5
                   50       343        1,5              7
                  100        79         2              7,5
                  700       344         2               7
              1918 (B-10)   252         2               8
                    
Station 4
24 Jan. 2017        Position (46º08S 76º04W)               Depth = 2400 m 
time 00:05 hr,      
—————————————————————————————————————————————————————————————————————————
                Sampling   Filter  Water Volume   Water Volume
                 depth      (Nº)   Filtrated for  filtrated for 
                  (m)               POC (Lt)      µzoo (Lt)
              ———————————  ——————  —————————————  —————————————
                    0       307         1              10
                   10        30         1              10
                   25       162         1              10
                   50       166        1,5             10
                  100       169         2              10
                  300       317         2              10
                  700       177        2,5              7
              1918 (B-10)   178        2,5    10

Station 7
28 Jan. 2017        Position (47º47,7S 76º02,6W)           Depth = 2000 m 
time 05:30 hr,     
—————————————————————————————————————————————————————————————————————————
                Sampling   Filter  Water Volume   Water Volume
                 depth      (Nº)   Filtrated for  filtrated for 
                  (m)               POC (Lt)      µzoo (Lt)
              ———————————  ——————  —————————————  ————————————— 
                    0       335         1             11
                   10       173         1             11
                   25       160         1            11,35
                   50       412        1,5            10
                  100       251         2            10,2
                  300       182        2,5            9,9
                  500       181        2,5            9,95
                  700       180        2,5            7,1
              1990 (B-10)   179        2,55           9,3

Station 9
29 Jan 2017         Position (48º23,5S 76º28,0W)           Depth = 1800 m 
time 10:00 hr,     
—————————————————————————————————————————————————————————————————————————
                Sampling   Filter  Water Volume   Water Volume
                 depth      (Nº)   Filtrated for  filtrated for 
                  (m)               POC (Lt)      µzoo (Lt)
              ———————————  ——————  —————————————  ————————————— 
                    0        31         1            12,6
                   10       167         1            10,85
                   25       174         1            10,1
                   50       175        1,6           11,3
                  100       358         2            10,6
                  300       161        2,55           9,9
                  500       176        2,6            9
                  700       155        2,5            7,6
              1790 (B-10)   329        2,55          10,6
                    
Station 10
31 Jan. 2017        Position (50º48,3715S 79º07,096W)      Depth = 3851 m 
time 05:30 hr,     
—————————————————————————————————————————————————————————————————————————
                Sampling   Filter  Water Volume   Water Volume
                 depth      (Nº)   Filtrated for  filtrated for 
                  (m)               POC (Lt)      µzoo (Lt)
              ———————————  ——————  —————————————  ————————————— 
                    0       140        1,5           10,9
                   10       328         1            11,1
                   25       159        1,5           11,4
                   50        60        1,6           10,1
                  100       137         2             8,6
                  300       138        2,5           11.4
                  500       139        2,5            9,1
                  700       141        2,5            9,8
              3841 (B-10)    39        2,5           10,15
                    
Station 12B 
02 Feb. 2017        Position (54º20,09S 74º38,187W)        Depth = 2400 m 
time 08:00 hr,
—————————————————————————————————————————————————————————————————————————
                Sampling   Filter  Water Volume   Water Volume
                 depth      (Nº)   Filtrated for  filtrated for 
                  (m)               POC (Lt)      µzoo (Lt)
              ———————————  ——————  —————————————  ————————————— 
                    0       168         1            12,1
                   10        20         1            11,1
                   25        59         1             7,85
                   50       322        1,5           11,1
                  100        61         2             10
                  300        62        2,7            6,8
                  500        63        2,5           10,4
                  700        19        2,5            7,65
              2390 (B-10)    18        2,5            9,8

Station 11B 
03 Feb. 2017        Position (53º00,08S 75º29,08W)         Depth = 1762 m 
time 01:10 hr,
—————————————————————————————————————————————————————————————————————————
                Sampling   Filter  Water Volume   Water Volume
                 depth      (Nº)   Filtrated for  filtrated for 
                  (m)               POC (Lt)      µzoo (Lt)
              ———————————  ——————  —————————————  ————————————— 
                    0       142         1             11
                   10       146         1            10,5
                   25       145         1            10,3
                   50       144         2            10,1
                  100        64         2             10
                  300        89        2,5            10
                  500       147        2,5           10,6
                  700        34        2,5            7,6
              1752 (B-10)   133        2,5            10

Station 11A 
03 Feb. 2017        Position (52º19,0681S 75º56,9148W)     Depth = 1880 m
time 17:40 hr,
—————————————————————————————————————————————————————————————————————————
                Sampling   Filter  Water Volume   Water Volume
                 depth      (Nº)   Filtrated for  filtrated for 
                  (m)               POC (Lt)      µzoo (Lt)
              ———————————  ——————  —————————————  ————————————— 
                    0       131         1            11,8
                   10       383         1            11,55
                   25        37         1            10,5
                   50       129         1            10,6
                  100       125         2            10,4
                  300       134        2,5           10,65
                  500         1        2,5           10,95
                  700       325        2,5           10,5
              1870 (B-10)    36        2,5           10,45



4.6  Physiological Characteristics of Phytoplankton Assemblages in 
     the Southern Patagonia Pacific Margin Waters

J.L. Iriarte* and T. Shiozaki†

* Centro Investigación Dinámica de Ecosistemas Marinos de Altas Latitudes 
  – IDEAL – Universidad Austral de Chile. COPAS-Sur Austral, Centro de 
  Investigación Oceanográfica en el Pacífico Sur-Oriental (COPAS-Sur 
  Austral), Universidad de Concepción, Chile
† Research and Development Center for Global Change, Japan Agency for 
  Marine-Earth Science and
  Technology – JAMSTEC, Japan


Introduction

    High-latitude ecosystems are immersed in environmental regimes that 
may strongly constrain biological productivity. Rhythms and rates of 
primary production in these highly seasonal environments depend to a 
large extent on the timing of nutrient supply and light availability for 
primary producers. In the fjords and channels of southern Chile, the 
interaction between oceanic water and freshwater from multiple sources 
(rivers, surface runoff, snow/glacier melting, precipitation) produces 
strong vertical and horizontal gradients in salinity, density, inorganic 
nutrient ratios and light availability. These gradients, and their 
seasonal and inter-annual changes, may affect both the biomass and 
composition of phytoplankton assemblages, and ultimately shape the 
spatial-temporal patterns of carbon fixation, organic matter fluxes, and 
biogeochemical balances in this region.
    
    Vertical mixing and the exchange of nutrients among the low-salinity, 
low nutrient and turbid surface layer and the more saline sub-surface 
layer are the main drivers of spring pulses in primary production and 
autotrophic biomass. The concentrations of inorganic nutrients show a 
strongly seasonal signal, with high nitrate and orthophosphate during 
winter, and lower values during spring, presumably caused by a sharp 
increase in primary productivity when light availability in near-surface 
waters increases (Iriarte et al 2007; González et al 2011). Beyond the 
changes in concentrations of macro and micronutrients, however, changes 
in freshwater regimes may modify the inorganic chemistry of euphotic-zone 
waters. In addition, increasing discharges of freshwater from glacier 
melting and river runoff may alter the acid-base chemistry of near-
surface waters, thereby establishing spatial gradients in alkalinity that 
may in turn determine shifts in phytoplankton composition (e.g. from 
cyanobacteria/chlorophytes to Diatoms/Dinoflagellates; Chakraborty et al 
2011) and productivity (Shi et al 2009). Specifically, combine abiotic 
factors (e.g. temperature, salinity, Fe, light) may play important role 
in defining the physiological state of phytoplankton, by inhibitory 
effects on physiological processes on phytoplankton cells (e.g. 
respiratory activity). Adaptation mechanisms at cellular level 
(photosystems I and II, photoprotective pigments) could impact the 
photochemical efficiency of photosynthesis and thus result in reduced 
growth rates and photosynthesis efficiency (PS II, Fv/Fm). Basically, our 
conceptual model would work in the following steps: the presence of 
high(low) driver (freshwater, wind stress) causes the formation of 
deep(shallow) mixed layer and pycnocline depth, leading to a rapid water 
column fluctuation in irradiance (high near surface and low near the 
pycnocline), which may impinge a great stress on the physiological 
dynamics of phytoplankton.
    
    The studied area is the large continental shelf of Patagonia (Fig. 
1), influenced by freshwater from largest adjacent rivers discharging 
freshwater. The interplay between freshwater and oceanic water types 
strongly interact with nutrients supply and may determine the magnitude 
of phytoplankton biomass and composition. We combine the continuous in 
situ profiling of fluorescence with oceanographic variables in
summer to estimate photosynthetic efficiency, phytoplankton biomass and 
composition, along with observations of inorganic nutrients, in the 
continental shelf to address a main question on to what extent the 
spatial changes in near surface water chemistry may affect phytoplankton 
community properties in oceanic Patagonian waters.


Figure 4.6-1: Autotrophic biomass (as Chlorophyll-a, µg L-1) vertical 
              distribution for phytoplankton communities at 8 stations, 
              along the Patagonian shelf, January-February 2017. Depth 
              interval: 0 – 100 m.


Material and Methods

    For the first time, we studied physiological features of 
phytoplankton assemblages in the Patagonian oceanic surface waters using 
a real-time Fast Repetition Rate Fluorometer (FRRf, Chelsea Technology
Group, UK) at 12 stations during austral summer (19 January – 5 February 
2017). At each station FRRf equipped with a 20 m cable was deployed in 
profiling mode with a approximate speed of 0.5 m s-1. With the exception 
of one station (11B, 21:30 h)), all measurements were done during the 
daylight between 9:30 to 15:30 h. Fluorescence readings were corrected 
for background fluorescence signals using filtered seawater previously 
collected at 10 m depth. All the FRRf deployment were carried out from 
stern of the vessel. This is essentially a measure of the quantum 
efficiency of photosystem II and provides an indication of cell health. 
All these variables and photosynthetic coefficients would give 
information on the effect of vertical stratification (pycnocline, light, 
nutricline) on the distribution of nPS II during different stations along 
Patagonia. In addition, it would be expected to find a significant 
correlation between photosynthetic efficiency fluorescence-based and in 
situ autotrophic biomass (as chlorophyll-a) and primary productivity 
determined by 13C method in Patagonian waters.


Results and Discussion

    Along the shelf transect the highest chlorophyll-a concentrations 
were observed in the northern area (Sta., 6, 7, 9) at the base of the 
pycnocline in the upper layer (0 – 25 m) with a mean value of 2.63 µg L-1 
(range: 1.64 – 3.76 µg L-1) (Fig. 4.6-1). These were associate with the 
stratified upper part of the water column (< 30 m) and coincided with 
relatively low salinities (32.75 – 33.35). For the southern stations 
(Sta., 11, 12), maximum chlorophyll-a values were lower than 1.79 µg L-1 
(mean: 1.01 µg  L-1) in  the upper 25 m.


Figure 4.6-2: Vertical distribution of quantum efficiencies of 
              photochemistry in PSII (F’q/F’m) and functional absorption 
              cross section of photosystem II (σ’PSII: Å2 m-2) for 
              phytoplankton communities under ambient light at 13 
              stations, along the Patagonian shelf, January-February 
              2017, were obtained by a Fast Repetition Rate Fluorometer 
              (FRRf). Depth interval: 0.5 – 20 m.

Figure 4.6-3: Horizontal distribution of quantum efficiencies of 
              photochemistry in PSII (F’q/F’m) and functional absorption 
              cross section of photosystem II (σ’PSII: Å2 m-2; 
              values*100) for phytoplankton communities under ambient 
              light at 8 stations, along the Patagonian shelf, January-
              February 2017, were obtained by a Fast Repetition Rate 
              Fluorometer (FRRf). Depth interval: 0.5 – 20 m.


    In general, the effective photochemical efficiency of PSII (F’q/F’m) 
was low and ranged between 0.081 to 0.497 (median = 0.308, 25% percentile 
= 0.22, 75% percentile = 0.384), increasing from surface to depth (20 m) 
at all stations (Y = 0,249 + 0.0054*depth, p = 0.0001, N = 1025) (Fig. 
4.6-2). In the northern area (Sta., 2, 6,) F’q/F’m values increased with 
depth, attaining values of 0.3 between 5 to 10 m. At southern stations 
(Sta., 11, 12) 0.3 - 0.45 quantum efficiencies were observed from 5 to 20 
m range depth. It seems to be influenced by the low surface salinities, 
with low values (>0.3) observed in the   upper 5 m, while higher than 0.3 
quantum efficiency deeper than 5 m were observed at southern stations 
characterized by deeper mixed layer.

    While the functional absorption cross section of photosystem II under 
ambient light (σ’PSII) showed a homogeneous vertical distribution at most 
of the stations or slightly increasing with depth (Y = 4.138 + 
0.0226*depth, p = 0.0001, N = 1004) (range = 47 – 676 Å2 m-2; median = 
442, 25% percentile = 220, 75% percentile = 384) (Fig. 4.6-2) and 
positive associated to quantum efficiency (Fig. 4.6-3). The preliminary 
results suggest us that the phytoplankton assemblages were adapted at 
lower irradiance in the upper 20 m depth. It was interesting to note that 
at stations 7 and 9, values higher than 500 Å2 m-2 functional were 
observed near surface and well correlated with chorophyll-a biomass.


References

Chakraborty P., T. Acharyya, P.V. Raghunadh Babu & D. Bandhyopadhyay. 
    2011. Impact of salinity and pH on phytoplankton community in a 
    tropical freshwater system: an investigation with pigment analyses by 
    HPLC. Journal of Environmental Monitoring. 13:614-620.
Iriarte J.L., González H.E., Liu K.K., Rivas C. and Valenzuela C. 2007. 
    Spatial and temporal variability  of chlorophyll and primary 
    productivity in surface waters of southern Chile (41.5–43°S). 
    Estuarine Coastal and Shelf Science 74, 471–480.
González, H.E., Castro, L., Daneri, G., Iriarte, J.L., Silva, N., Vargas, 
    C., Giesecke, R., Sánchez N., 2011. Seasonal plankton variability in 
    Chilean Patagonia fjords: carbon flow through the pelagic food web of 
    the Aysen Fjord and plankton dynamics in the Moraleda Channel basin. 
    Continental Shelf Research 31, 225-243.
Shi D., Xu, Y., F.M.M Morel. 2009. Effects of the pH/pCO2 control method 
    on medium chemistry and phytoplankton growth. Biogeosciences, 6:1199-
    1207


4.7  CTDO2 Measurements
     May 14, 2017


(1) Personnel

    Hiroshi Uchida (JAMSTEC) 
    Rei Ito (MWJ)
    Sonoka Tanihara (MWJ) 
    Kenichi Katayama (MWJ) 
    Shungo Oshitani (MWJ) Rio 
    Kobayashi (MWJ)
    Michinari Sunamura (The University of Tokyo) (CDOM measurement)


(2) Winch arrangements

    The CTD package was deployed by using 4.5 Ton Traction Winch System 
(Dynacon, Inc., Bryan, Texas, USA), which was renewed on the R/V Mirai in 
April 2014 (e.g. Fukasawa et al., 2004). Primary system components 
include a complete CTD Traction Winch System with up to 9000 m of 9.53 mm 
armored cable (Rochester Wire & Cable, LLC, Culpeper, Virginia, USA).


(3) Overview of the equipment

    The CTD system was SBE 911plus system (Sea-Bird Electronics, Inc., 
Bellevue, Washington, USA). The SBE 911plus system controls 36-position 
SBE 32 Carousel Water Sampler. The Carousel accepts 12- litre Niskin-X 
water sample bottles (General Oceanics, Inc., Miami, Florida, USA). The 
SBE 9plus was mounted horizontally in a 36-position carousel frame. SBE’s 
temperature (SBE 3) and conductivity (SBE 4) sensor modules were used 
with the SBE 9plus underwater unit. The pressure sensor is mounted in the 
main housing of the underwater unit and is ported to outside through the 
oil-filled plastic capillary tube. A modular unit of underwater housing 
pump (SBE 5T) flushes water through sensor tubing at a constant rate 
independent of the CTD’s motion, and pumping rate (3000 rpm) remain 
nearly constant over the entire input voltage range of 12-18 volts DC. 
Flow speed of pumped water in standard TC duct is about 2.4 m/s. Two sets 
of temperature and conductivity modules were used. An SBE’s dissolved 
oxygen sensor (SBE43) was placed between the primary conductivity sensor 
and the pump module. Auxiliary sensors, a Deep Ocean Standards 
Thermometer (SBE 35), an altimeter (PSA-916T; Teledyne Benthos, Inc., 
North Falmous, Massachusetts, USA), an oxygen optodes (RINKO-III; JFE 
Advantech Co., Ltd, Kobe Hyogo, Japan), a fluorometers (Seapoint sensors, 
Inc., Kingston, New Hampshire, USA), a transmissometer (C-Star 
Transmissometer; WET Labs, Inc., Philomath, Oregon, USA), a turbidity 
meter (Seapoint Sensors, Inc., Exeter, New Hampshire, USA), a 
Photosynthetically Active Radiation (PAR) sensor (Satlantic, LP, Halifax, 
Nova Scotia, Canada), and a colored dissolved organic matter (ECO FL 
CDOM, WET Labs, Inc., Philomath, Oregon, USA) were also used with the SBE 
9plus underwater unit. To minimize rotation of the CTD package, a heavy 
stainless frame (total weight of the CTD package without sea water in the 
bottles is about 1000 kg) was used with an aluminum plate (54 × 90 cm).

Summary of the system used in this cruise
36-position Carousel system
Deck unit:
    SBE 11plus, S/N 11P54451-0872

Under water unit:
    SBE 9plus, S/N 09P21746-0575 (79492)

Temperature sensor:
    SBE 3, S/N 031525 (primary)
    SBE 3plus, S/N 03P4421 (secondary) 

Conductivity sensor:
    SBE 4, S/N 042435 (primary)
    SBE 4, S/N 041088 (secondary) 

Oxygen sensor:
    SBE 43, S/N 432471
    JFE Advantech RINKO-III, S/N 0024 (foil batch no. 144002A)

Pump:
    SBE 5T, S/N 054595 (primary) 
    SBE 5T, S/N 053293 (secondary)

Altimeter:
    PSA-916T, S/N 1157

Deep Ocean Standards Thermometer: 
    SBE 35, S/N 0045

Fluorometer:
    Seapoint Sensors, Inc., S/N 3618 (measurement range: 0-15 µg/L) 
                                     (Gain: 10X) 

Turbidity meter:
    Seapoint Sensors, Inc., S/N 14953 (measurement range: 0-500 FTU)       
                                      (Gain: 5X) for leg 2
                                      (measurement range: 0-25 FTU) 
                                      (Gain: 100X) for leg 3

Transmissometer:
    C-Star, S/N CST-1726DR

PAR:
    Satlantic LP, S/N 1025


CDOM:
    ECO FL CDOM, S/N FLCDRTD-2014 (measurement range: 0-500 ppb)

Carousel Water Sampler:
    SBE 32, S/N 3254451-0826

Water sample bottle:
    12-litre Niskin-X model 1010X (no TEFLON coating) 
    General Oceanics, Inc., Miami, Florida, USA,


(4) Pre-cruise calibration

i. Pressure

    The Paroscientific series 4000 Digiquartz high pressure transducer 
(Model 415K: Paroscientific, Inc., Redmond, Washington, USA) uses a 
quartz crystal resonator whose frequency of oscillation varies with 
pressure induced stress with 0.01 per million of resolution over the 
absolute pressure range of 0 to 15000 psia (0 to 10332 dbar). Also, a 
quartz crystal temperature signal is used to compensate for a wide range 
of temperature changes at the time of an observation. The pressure sensor 
has a nominal accuracy of 0.015 % FS (1.5 dbar), typical stability of 
0.0015 % FS/month (0.15 dbar/month), and resolution of 0.001 % FS (0.1 
dbar). Since the pressure sensor measures the absolute value, it 
inherently includes atmospheric pressure (about 14.7 psi). SEASOFT 
subtracts 14.7 psi from computed pressure automatically.

    Pre-cruise sensor calibrations for linearization were performed at 
SBE, Inc. The time drift of the pressure sensor is adjusted by periodic 
recertification corrections against an electronic dead-weight tester 
(Model E-DWT-H, S/N 181, Fluke Co, Phoenix, Arizona, USA, Calibrated on 3 
April 2016 at Ohte Giken, Inc., Tsukuba, Ibaraki, Japan). The corrections 
are performed at JAMSTEC, Yokosuka, Kanagawa, Japan by Marine Works Japan 
Ltd. (MWJ), Yokohama, Kanagawa, Japan, usually once in a year in order to 
monitor sensor time drift and linearity.
    S/N 0575, 13 April 2016
        slope = 0.99982448
        offset = 2.98685

ii. Temperature (SBE 3)

    The temperature sensing element is a glass-coated thermistor bead in 
a stainless steel tube, providing a pressure-free measurement at depths 
up to 10500 (6800) m by titanium (aluminum) housing. The SBE 3 
thermometer has a nominal accuracy of 1 mK, typical stability of 0.2 
mK/month, and resolution of 0.2 mK at 24 samples per second. The premium 
temperature sensor, SBE 3plus, is a more rigorously tested and calibrated 
version of standard temperature sensor (SBE 3).
    Pre-cruise sensor calibrations were performed at SBE, Inc.
        S/N 031525, 7 May 2016
        S/N 03P4421, 7 May 2016

iii. Conductivity (SBE 4)

    The flow-through conductivity sensing element is a glass tube (cell) 
with three platinum electrodes to provide in-situ measurements at depths 
up to 10500 (6800) m by titanium (aluminum) housing. The SBE 4 has a 
nominal accuracy of 0.0003 S/m, typical stability of 0.0003 S/m/month, 
and resolution of 0.00004 S/m at 24 samples per second. The conductivity 
cells have been replaced to newer style cells for deep ocean 
measurements.
    Pre-cruise sensor calibrations were performed at SBE, Inc.
        S/N 042435, 12 May 2016
        S/N 041088, 12 May 2016
    The value of conductivity at salinity of 35, temperature of 15 °C 
(IPTS-68) and pressure of 0 dbar is 4.2914 S/m.

iv. Oxygen (SBE 43)

    The SBE 43 oxygen sensor uses a Clark polarographic element to 
provide in-situ measurements at depths up to 7000 m. The range for 
dissolved oxygen is 120 % of surface saturation in all natural waters, 
nominal accuracy is 2 % of saturation, and typical stability is 2 % per 
1000 hours.
    Pre-cruise sensor calibration was performed at SBE, Inc.
        S/N 432471, 10 May 2016

v. Deep Ocean Standards Thermometer

    Deep Ocean Standards Thermometer (SBE 35) is an accurate, ocean-range 
temperature sensor that can be standardized against Triple Point of Water 
and Gallium Melt Point cells and is also capable of measuring temperature 
in the ocean to depths of 6800 m. The SBE 35 was used to calibrate the 
SBE 3 temperature sensors in situ (Uchida et al., 2007).
    Pre-cruise sensor linearization was performed at SBE, Inc.
        S/N 0045, 27 September 2002

    Then the SBE 35 is certified by measurements in thermodynamic fixed-
point cells of the TPW (0.01 °C) and GaMP (29.7646 °C). The slow time 
drift of the SBE 35 is adjusted by periodic recertification corrections. 
Pre-cruise sensor calibration was performed at SBE, Inc. Since 2014, 
fixed-point cells traceable to NIST temperature standards is directly 
used in the manufacturer’s calibration of the SBE 35 (Uchida et al., 
2015). Since 2016, pre-cruise sensor calibration was performed at 
RCGC/JAMSTEC by using fixed- point cells traceable to NMIJ temperature 
standards.
    S/N 0045, 30 June 2016 (slope and offset correction)
        Slope = 1.000023
        Offset = –0.001053
    The time required per sample = 1.1 × NCYCLES + 2.7 seconds. The 1.1 
seconds is total time per an acquisition cycle. NCYCLES is the number of 
acquisition cycles per sample and was set to 4. The 2.7 seconds is 
required for converting the measured values to temperature and storing 
average in EEPROM.


Fig. 4.7.1: Time drifts (temperature offsets relative to the first 
            calibration) of six reference thermometers (SBE 35) based on 
            laboratory calibrations in fixed-point cells. Results 
            performed at JAMSTEC are shown in red marks.

vi. Altimeter

    Benthos PSA-916T Sonar Altimeter (Teledyne Benthos, Inc.) determines 
the distance of the target from the unit by generating a narrow beam 
acoustic pulse and measuring the travel time for the pulse to bounce back 
from the target surface. It is rated for operation in water depths up to 
10000 m. The PSA-916T uses the nominal speed of sound of 1500 m/s.

vii. Oxygen optode (RINKO)

    RINKO (JFE Alec Co., Ltd.) is based on the ability of selected 
substances to act as dynamic fluorescence quenchers. RINKO model III is 
designed to use with a CTD system which accept an auxiliary analog 
sensor, and is designed to operate down to 7000 m.
    
    Data from the RINKO can be corrected for the time-dependent, 
pressure-induced effect by means of the same method as that developed for 
the SBE 43 (Edwards et al., 2010). The calibration coefficients, H1 
(amplitude of hysteresis correction), H2 (curvature function for 
hysteresis), and H3 (time constant for hysteresis) were determined 
empirically as follows.
        H1 = 0.0055 (for S/N 0024)
        H2 = 5000 dbar 
        H3 = 2000 seconds
    Outputs from RINKO are the raw phase shift data. The RINKO can be 
calibrated by the modified Stern-Volmer equation slightly modified from a 
method by Uchida et al. (2010):
        O2 ((mol/l) = [(V0 / V)E – 1] / Ksv
where V is voltage, V0 is voltage in the absence of oxygen, Ksv is Stern-
Volmer constant. The coefficient E corrects nonlinearity of the Stern-
Volmer equation. The V0 and the Ksv are assumed to be functions of 
temperature as follows.
        Ksv = C0 + C1 × T + C2 × T2 
        V0 = 1 + C3 × T
        V = C4 + C5 × Vb
where T is CTD temperature (°C) and Vb is raw output (volts). V0 and V 
are normalized by the output in the absence of oxygen at 0°C. The oxygen 
concentration is calculated using accurate temperature data from the CTD 
temperature sensor instead of temperature data from the RINKO. The 
pressure-compensated oxygen concentration O2c can be calculated as 
follows.
        O2c = O2 (1 + Cpp / 1000)
where p is CTD pressure (dbar) and Cp is the compensation coefficient. 
Since the sensing foil of the optode is permeable only to gas and not to 
water, the optode oxygen must be corrected for salinity. The salinity- 
compensated oxygen can be calculated by multiplying the factor of the 
effect of salt on the oxygen solubility (Garcia and Gordon, 1992).

    Pre-cruise sensor calibrations were performed at RCGC/JAMSTEC.
        S/N 0024, 10 May 2015

viii. Fluorometer

    The Seapoint Chlorophyll Fluorometer (Seapoint Sensors, Inc., 
Kingston, New Hampshire, USA) provides in-situ measurements of 
chlorophyll-a at depths up to 6000 m. The instrument uses modulated blue 
LED lamps and a blue excitation filter to excite chlorophyll-a. The 
fluorescent light emitted by the chlorophyll-a passes through a red 
emission filter and is detected by a silicon photodiode. The low level 
signal is then processed using synchronous demodulation circuitry, which 
generates an output voltage proportional to chlorophyll-a concentration.
    
ix. Transmissometer

    The C-Star Transmissometer (WET Labs, Inc., Philomath, Oregon, USA) 
measures light transmittance at a single wavelength (650 nm) over a known 
path (25 cm). In general, losses of light propagating through water can 
be attributed to two primary causes: scattering and absorption. By 
projecting a collimated beam of light through the water and placing a 
focused receiver at a known distance away, one can quantify these losses. 
The ratio of light gathered by the receiver to the amount originating at 
the source is known as the beam transmittance. Suspended particles, 
phytoplankton, bacteria and dissolved organic matter contribute to the 
losses sensed by the instrument. Thus, the instrument provides 
information both for an indication of the total concentrations of matter 
in the water as well as for a value of the water clarity.
    
    Light transmission Tr (in %) and beam attenuation coefficient cp are 
calculated from the sensor output (V in volt) as follows.
        Tr = (c0 + c1 V) × 100
        cp = – (1 / 0.25) ln(Tr / 100)
    Pre-cruise sensor calibration was performed at WET Labs.
        S/N CST-1726DR, 26 May 2015

x. Turbidity meter

    The Seapoint turbidity meter (Seapoint Sensors, Inc., Kingston, New 
Hampshire, USA) detects light scattered by particles suspended in water 
at depths up to 6000 m. The sensor generates an output voltage 
proportional to turbidity or suspended solids. The unique optical design 
confines the sensing volume to within 5 cm of the sensor.

xi. PAR

    Photosynthetically Active Radiation (PAR) sensors (Satlantic, LP, 
Halifax, Nova Scotia, Canada) provide highly accurate measurements of PAR 
(400 – 700 nm) for a wide range of aquatic and terrestrial applications. 
The ideal spectral response for a PAR sensor is one that gives equal 
emphasis to all photons between 400 – 700 nm. Satlantic PAR sensors use a 
high quality filtered silicon photodiode to provide a near equal spectral 
response across the entire wavelength range of the measurement.
    Pre-cruise sensor calibration was performed at Satlantic, LP.
        S/N 1025, 6 July 2015

xii. CDOM

    The Environmental Characterization Optics (ECO) miniature fluorometer 
(WET Labs, Inc., Philomath, Oregon, USA) allows the user to measure 
relative Colored Dissolved Organic Matter (CDOM) concentrations by 
directly measuring the amount of fluorescence emission in a sample volume 
of water. The CDOM fluorometer uses an UV LED to provide the excitation 
source. An interference filter is used to reject the small amount of out-
of-band light emitted by the LED. The light from the source enters the 
water volume at an angle of approximately 55-60 degrees with respect to 
the end face of the unit. Fluoresced light is received by a detector 
positioned where the acceptance angle forms a 140-degree intersection 
with the source beam. An interference filter is used to discriminate 
against the scattered excitation light.
    
    CDOM (Quinine Dihydrate Equivalent) concentration expressed in ppb 
can be derived using the equation as follows.
    
CDOM = Scale Factor * (Output – Dark Counts)

Pre-cruise sensor calibration was performed at WET Labs.

S/N FLCDRTD-2014, 1 September 2015 Dark Counts: 0.025 V


Scale Factor: 106 ppb/V


(5) Data collection and processing

i. Data collection
 
    CTD system was powered on at least 20 minutes in advance of the data 
acquisition to stabilize the pressure sensor and was powered off at least 
two minutes after the operation in order to acquire pressure data on the 
ship’s deck.
    
    The package was lowered into the water from the starboard side and 
held 10 m beneath the surface in order to activate the pump. After the 
pump was activated, the package was lifted to the surface and lowered at 
a rate of 1.0 m/s to 200 m (or 300 m when significant wave height was 
high) then the package was stopped to operate the heave compensator of 
the crane. The package was lowered again at a rate of 1.2 m/s to the 
bottom. For the up cast, the package was lifted at a rate of 1.1 m/s 
except for bottle firing stops. As a rule, the bottle was fired after 
waiting from the stop for more than 20 seconds and the package was stayed 
at least 5 seconds for measurement of the SBE 35 at each bottle firing 
stops. For depths where vertical gradient of water properties were 
expected to be large (from surface to thermocline), the bottle was 
exceptionally fired after waiting from the stop for 60 seconds to enhance 
exchanging the water between inside and outside of the bottle. At 200 m 
(or 300 m) from the surface, the package was stopped to stop the heave 
compensator of the crane.
    
    Water samples were collected using a 36-bottle SBE 32 Carousel Water 
Sampler with 12-litre Niskin- X bottles. Before a cast taken water for 
CFCs, the bottle frame and Niskin-X bottles were wiped with acetone.
    
    Data acquisition software

        SEASAVE-Win32, version 7.23.2

ii. Data collection problems

(a) Miss trip, miss fire, and remarkable leak
 
     Miss trip, miss fire and remarkable leak occurred during the cruise 
were listed below.

     Miss trip  Miss fire  Leak
     none       none       007_1 #20 end closure: O-ring of the end 
                                     closure replaced
                           010_1 #21 end closure: O-ring of the end 
                                     closure replaced
                           022_1 #22 end closure: O-ring of the end 
                                     closure checked
                           024_1 #4 end closure: O-ring of the end 
                                     closure checked

(b) Slight leaks

    Slight leaks were observed from the root of stopcocks during drawing 
of the samples at station leg3_011_1  (#2,  #4,  #5,  #7,  #11,  #12),  
leg3_015_1  (#25,  #26,  #27,  #29),  leg3_016_1  (#25,  #27),
leg3_018_1 (#3), and leg3_026_1 (#36). The bottle flags for those bottles 
were set to 2 since the bottle data (salinity and oxygen) were normal and 
there was no leak for those bottles at the leak check before the drawing 
of the samples.

(c) Noise in down cast data

    Transmissometer data were noisy at station leg2_006_1 (504~506, 
519~521, 820~826, 833~838, 939~947, 968~970, 1063~1067, 1255~1259 dbar), 
leg2_007_1 (117~118, 1022~1025 dbar), leg2_12B_1 (736~741, 1035~1037 
dbar), leg2_11B_1 (131~133 dbar), leg3_009_1 (1071-1076 dbar), leg3_015_1 
(821~826 dbar), leg3_016_1 (1497~1541, 1574~1578 dbar), leg3_021_1 
(400~527 dbar), leg3_023_1 (992~998 dbar), leg3_024_1 (2248~2253 dbar) 
and leg3_025_1 (64~65, 473~475 dbar), and the data were removed and 
linearly interpolated.

iii. Data processing

    SEASOFT consists of modular menu driven routines for acquisition, 
display, processing, and archiving of oceanographic data acquired with 
SBE equipment. Raw data are acquired from instruments and are stored as 
unmodified data. The conversion module DATCNV uses instrument 
configuration and calibration coefficients to create a converted 
engineering unit data file that is operated on by all SEASOFT post 
processing modules. The following are the SEASOFT and original software 
data processing module sequence and specifications used in the reduction 
of CTD data in this cruise.
    
    Data processing software

        SBEDataProcessing-Win32, version 7.23.2

    DATCNV converted the raw data to engineering unit data. DATCNV also 
extracted bottle information where scans were marked with the bottle 
confirm bit during acquisition. The duration was set to 4.4 seconds, and 
the offset was set to 0.0 second. The hysteresis correction for the SBE 
43 data (voltage) was applied for both profile and bottle information 
data.
    
    RINKOCOR (original module, version 1.0) corrected the time-dependent, 
pressure-induced effect (hysteresis) of the RINKO for both profile data.
    
    RINKOCORROS (original module, version 1.0) corrected the time-
dependent, pressure-induced effect (hysteresis) of the RINKO for bottle 
information data by using the hysteresis-corrected profile data.
    
    BOTTLESUM created a summary of the bottle data. The data were 
averaged over 4.4 seconds.

    ALIGNCTD converted the time-sequence of sensor outputs into the 
pressure sequence to ensure that all calculations were made using 
measurements from the same parcel of water. For a SBE 9plus CTD with the 
ducted temperature and conductivity sensors and a 3000-rpm pump, the 
typical net advance of the conductivity relative to the temperature is 
0.073 seconds. So, the SBE 11plus deck unit was set to advance the 
primary and the secondary conductivity for 1.73 scans (1.75/24 = 0.073 
seconds). Oxygen data are also systematically delayed with respect to 
depth mainly because of the long time constant of the oxygen sensor and 
of an additional delay from the transit time of water in the pumped 
plumbing line. This delay was compensated by 5 seconds advancing the SBE 
43 oxygen sensor output (voltage) relative to the temperature data. Delay 
of the RINKO data was also compensated by 1 second advancing sensor 
output (voltage) relative to the temperature data. Delay of the 
transmissometer data was also compensated by 2 seconds advancing sensor 
output (voltage) relative to the temperature data.
    
    WILDEDIT marked extreme outliers in the data files. The first pass of 
WILDEDIT obtained an accurate estimate of the true standard deviation of 
the data. The data were read in blocks of 1000 scans. Data greater than 
10 standard deviations were flagged. The second pass computed a standard 
deviation over the same 1000 scans excluding the flagged values. Values 
greater than 20 standard deviations were marked bad. This process was 
applied to pressure, temperature, conductivity, and SBE 43 output.
    
    CELLTM used a recursive filter to remove conductivity cell thermal 
mass effects from the measured conductivity. Typical values used were 
thermal anomaly amplitude alpha = 0.03 and the time constant 1/beta
= 7.0.

    FILTER performed a low pass filter on pressure with a time constant 
of 0.15 seconds. In order to produce zero phase lag (no time shift) the 
filter runs forward first then backwards.

    WFILTER performed as a median filter to remove spikes in fluorometer, 
turbidity meter, transmissometer, and CDOM data. A median value was 
determined by 49 scans of the window. For CDOM data, an additional box-
car filter with a window of 361 scans was applied to remove noise.
    
    SECTIONU (original module, version 1.1) selected a time span of data 
based on scan number in order to reduce a file size. The minimum number 
was set to be the start time when the CTD package was beneath the sea-
surface after activation of the pump. The maximum number was set to be 
the end time when the depth of the package was 1 dbar below the surface. 
The minimum and maximum numbers were automatically calculated in the 
module.
    
    LOOPEDIT marked scans where the CTD was moving less than the minimum 
velocity of 0.0 m/s (traveling backwards due to ship roll).
    
    DESPIKE (original module, version 1.0) removed spikes of the data. A 
median and mean absolute deviation was calculated in 1-dbar pressure bins 
for both down- and up-cast, excluding the flagged values. Values greater 
than 4 mean absolute deviations from the median were marked bad for each 
bin. This process was performed 2 times for temperature, conductivity, 
SBE 43, and RINKO output.
    
    DERIVE was used to compute oxygen (SBE 43).

    BINAVG averaged the data into 1-dbar pressure bins. The center value 
of the first bin was set equal to the bin size. The bin minimum and 
maximum values are the center value plus and minus half the bin size. 
Scans with pressures greater than the minimum and less than or equal to 
the maximum were averaged. Scans were interpolated so that a data record 
exist every dbar.
    
    BOTTOMCUT (original module, version 0.1) deleted the deepest pressure 
bin when the averaged scan number of the deepest bin was smaller than the 
average scan number of the bin just above.
    
    DERIVE was re-used to compute salinity, potential temperature, and 
density. 

    SPLIT was used to split data into the down cast and the up cast.

    Remaining spikes in the CTD data were manually eliminated from the 1-
dbar-averaged data. The data gaps resulting from the elimination were 
linearly interpolated with a quality flag of 6.


(6) Post-cruise calibration

i. Pressure

    The CTD pressure sensor offset in the period of the cruise was 
estimated from the pressure readings on the ship deck. For best results 
the Paroscientific sensor was powered on for at least 20 minutes before 
the operation. In order to get the calibration data for the pre- and 
post-cast pressure sensor drift, the CTD deck pressure was averaged over 
first and last one minute, respectively. Then the atmospheric pressure 
deviation from a standard atmospheric pressure (14.7 psi) was subtracted 
from the CTD deck pressure to check the pressure sensor time drift. The 
atmospheric pressure was measured at the captain deck (20 m high from the 
base line) and sub-sampled one-minute interval as a meteorological data.
    
    Time series of the CTD deck pressure is shown in Figs. 4.7.2 and 
4.7.3. The CTD pressure sensor offset was estimated from the deck 
pressure. Mean of the pre- and the post-casts data over the whole period 
gave an estimation of the pressure sensor offset (0.66 dbar) from the 
pre-cruise calibration. The post-cruise correction of the pressure data 
was carried out by subtracting 0.66 dbar from the pressure data. Figs. 
4.7.2 and 4.7.3 show the pressure data after the post-cruise correction.
    

Fig. 4.7.2: Time series of the CTD deck pressure for leg 2. Atmospheric 
            pressure deviation (magenta dots) from a standard atmospheric 
            pressure was subtracted from the CTD deck pressure. Blue and 
            green dots indicate pre- and post-cast deck pressures, 
            respectively. Red dots indicate averages of the pre- and the 
            post-cast deck pressures.

Fig. 4.7.3: Same as Fig. 4.7.2, but for leg 3.


ii. Temperature

    The CTD temperature sensors (SBE 3) were calibrated with the SBE 35 
under the assumption that discrepancies between SBE 3 and SBE 35 data 
were due to pressure sensitivity, the viscous heating effect, and time 
drift of the SBE 3, according to a method by Uchida et al. (2007).
    
    Post-cruise sensor calibration for the SBE 35 will be performed at 
JAMSTEC in 2017 

    The CTD temperature was preliminary calibrated as

        Calibrated temperature = T – (c0 × P + c1 × t + c2 )

where T is CTD temperature in °C, P is pressure in dbar, t is time in 
days from pre-cruise calibration date of the CTD temperature and c0, c1, 
and c2 are calibration coefficients. The coefficients were determined 
using the data for the depths deeper than 1950 dbar. The coefficient c1 
was set to zero for this cruise.

    The primary temperature data were basically used for the post-cruise 
calibration. The secondary temperature sensor was also calibrated and 
used instead of the primary temperature data when the data quality of the 
primary temperature data was bad. The calibration coefficients are listed 
in Table 4.7.1. The results of the post-cruise calibration for the CTD 
temperature are summarized in Table 4.7.2 and shown in Figs. 4.7.4 and 
4.7.5.


Table 4.7.1: Calibration coefficients for the CTD temperature sensors.

           Serial number   c0(°C/dbar)  c1(°C/day)   c2(°C)
           —————————————  ————————————  ——————————  ———————
              031525      –1.713992e–8     0.0      0.00029


Table 4.7.2: Difference between the CTD temperature and the SBE 35 after 
             the post-cruise calibration. Mean and standard deviation 
             (Sdev) are calculated for the data below and above 1950 
             dbar. Number of data used is also shown.

          Serial  Pressure ≥ 1950 dbar   Pressure < 1950 dbar
          number  ————————————————————   ————————————————————
          ——————   Number  Mean  Sdev     Number  Mean  Sdev
                           (mK)  (mK)             (mK)  (mK)
                   ——————  ————  ————     ——————  ————  ————
          031525    326    0.0   0.2        616   –0.3   2.7


Fig. 4.7.4: Difference between the CTD temperature (primary) and the SBE 
            35 for leg 2. Blue and red dots indicate before and after the 
            post-cruise calibration using the SBE 35 data, respectively. 
            Lower two panels show histogram of the difference after the 
            calibration.

Fig. 4.7.5: Same as Fig. 4.7.4, but for leg 3.


iii. Salinity

    The discrepancy between the CTD conductivity and the conductivity 
calculated from the bottle salinity data with the CTD temperature and 
pressure data is considered to be a function of conductivity, pressure 
and time. The CTD conductivity was calibrated as
    
    Calibrated conductivity =

C – (c0 × C + c1 × P + c2 × C × P + c3 × P2 + c4 × P2 × C + c5 × P2 × C2 + c6)

where C is CTD conductivity in S/m, P is pressure in dbar, and c0, c1, 
c2, c3, c4, c5 and c6 are calibration coefficients. The best fit sets of 
coefficients were determined by a least square technique to minimize the 
deviation from the conductivity calculated from the bottle salinity data.

    The primary conductivity data created by the software module ROSSUM 
were used after the post- cruise calibration for the temperature data. 
The calibration coefficients are listed in Table 4.7.3. The results of 
the post-cruise calibration for the CTD salinity are summarized in Table 
4.7.4 and shown in Figs 4.7.6 and 4.7.7.


Table 4.7.3: Calibration coefficients for the CTD conductivity sensors.

                  Coefficient      S/N 042435
                  ———————————  —————————————————
                      c0        7.2645896049e–6
                      c1        2.9691992467e–7
                      c2       –7.2958281688e–8
                      c3        1.9466613572e–10
                      c4       –1.6842918454e–10
                      c5        3.3411307753e–11
                      c6       –9.7770147557e–5


Table 4.7.4: Difference between the CTD salinity and the bottle salinity 
             after the post-cruise calibration. Mean and standard 
             deviation (Sdev) (in 10–3) are calculated for the data below 
             and above 950 dbar. Number of data used is also shown.

          Serial  Pressure ≥ 950 dbar   Pressure < 950 dbar
          number  ———————————————————   ———————————————————
          ——————  Number  Mean  Sdev    Number  Mean  Sdev
                  ——————  ————  ————    ——————  ————  ————
          042435   465    –0.1  0.6      390    0.1   3.1


Fig. 4.7.6: Difference between the CTD salinity (primary) and the bottle 
            salinity for leg 2. Blue and red dots indicate before and 
            after the post-cruise calibration, respectively. Lower two 
            panels show histogram of the difference after the calibration.

Fig. 4.7.7: Same as Fig. 4.7.6, but for leg 3.


iv. Oxygen

    The RINKO oxygen optode (S/N 0024) was calibrated and used as the CTD 
oxygen data, since the RINKO has a fast time response. The pressure-
hysteresis corrected RINKO data was calibrated by the modified Stern-
Volmer equation, basically according to a method by Uchida et al. (2010) 
with slight modification:
    
    [O2] (µmol/l) = [(V0 / V)1.5 – 1] / Ksv

and

    Ksv = C0 + C1 × T + C2 × T2 
    V0 = 1 + C3 × T
    V = C4 + C5 × Vb + C6 × t + C7 × t × Vb

where Vb is the RINKO output (voltage), V0 is voltage in the absence of 
oxygen, T is temperature in °C, and t is working time (days) integrated 
from the first CTD cast. Time drift of the RINKO output was corrected. 
The calibration coefficients were determined by minimizing the sum of 
absolute deviation with a weight from the bottle oxygen data. The revised 
quasi-Newton method (DMINF1) was used to determine the sets.

    The post-cruise calibrated temperature and salinity data were used 
for the calibration. The calibration coefficients are listed in Table 
4.7.5. The results of the post-cruise calibration for the RINKO oxygen 
are summarized in Table 4.7.6 and shown in Figs. 4.7.8 and 4.7.9.


Table 4.7.5: Calibration coefficients for the RINKO oxygen sensors.

               Coefficient           S/N 0024
               ———————————  —————————————————————
                   c0        5.942125838095365e–3
                   c1        2.112922682529651e–4
                   c2        2.453149432631086e–6
                   c3       –2.858906729587995e–3
                   c4       –3.724762205027561e–2
                   c5        0.3277293704143511
                   c6        6.221125143791855e–4
                   c7       –5.158472610105331e–4
                   Cp        0.014


Table 4.7.6: Difference between the RINKO oxygen and the bottle oxygen 
             after the post-cruise calibration. Mean and standard 
             deviation (Sdev) are calculated for the data below and above 
             950 dbar. Number of data used is also shown.

          Serial  Pressure ≥ 950 dbar   Pressure < 950 dbar
          number  ———————————————————   ———————————————————
          ——————  Number  Mean  Sdev    Number  Mean   Sdev
                           [mol/kg]              [mol/kg]
                  ——————  ————  ————    ——————  —————  ————
           0024    465    0.00  0.27     391    –0.10  0.88


Fig. 4.7.8: Difference between the CTD oxygen and the bottle oxygen for 
            leg 2. Blue and red dots indicate before and after the post-
            cruise calibration, respectively. Lower two panels show 
            histogram of the difference after the calibration.

Fig. 4.7.9: Same as Fig. 4.7.8, but for leg 3.


v. Fluorometer

    The CTD fluorometer (FLUOR in µg/L) was calibrated by comparing with 
the bottle sampled chlorophyll-a as
    
    FLUORc = c0 + c1 × FLUOR

where c0 and c1 are calibration coefficients. The CTD fluorometer data 
is slightly noisy so that the up cast profile data which was averaged 
over one decibar agree with the bottle sampled data better than the 
discrete CTD fluorometer data obtained at bottle-firing stop. Therefore, 
the CTD fluorometer data at water sampling depths extracted from the up 
cast profile data were compared with the bottle sampled chlorophyll-a 
data. The bottle sampled data obtained at dark condition [PAR 
(Photosynthetically Available Radiation) < 50 <E/(m2 sec)] were used for 
the calibration, since sensitivity of the fluorometer to chlorophyll a is 
different at nighttime and daytime (Section 2.4 in Uchida et al., 2015).

    Firstly, bias of sensor output (–c0/c1) was determined from the 
minimum of the sensor output as 0.022. Then the calibration coefficients 
were determined under this condition (–c0/c1 = 0.022) for three groups: 
station 007 of leg 2, stations of leg 2 except for 007, and stations of 
leg 3. The calibration coefficients are listed in Table 4.7.7. The 
results of the post-cruise calibration for the fluorometer are summarized 
in Table 4.7.8 and shown in Fig. 4.7.10.


Fig. 4.7.10: Comparison of the CTD fluorometer and the bottle sampled 
             chlorophyll-a. The regression lines are also shown.


Table 4.7.7: Calibration coefficients for the CTD fluorometer.

          c0                    c1                      Note
——————————————————————  ——————————————————  —————————————————————————————
–3.415403161178421e-02  1.552455920202864   for stn. 007 of leg 2
–1.070073772820049e-02  0.4863967142398999  for leg 2 except for stn. 007
–6.244323339035114e-03  0.2839634259958261  for leg 3


Table 4.7.8: Difference between the CTD fluorometer and the bottle 
             chlorophyll-a after the post-cruise calibration. Mean, 
             standard deviation (Sdev), and number of data used are 
             shown. Data obtained at daytime are also used in this 
             calculation.

                    Number    Mean       Sdev
                    ——————  —————————  —————————
                     306    0.00 µg/L  0.12 µg/L


vi. Transmissometer

    The transmissometer (Tr in %) is calibrated as 

        Tr = (V–Vd) / (Vr–Vd) × 100

wehre V is the measured signal (voltage), Vd is the dark offset for the 
instrument, and Vr is the signal for clear water. Vd can be obtained by 
blocking the light path. Vd and Vair, which is the signal for air, were 
measured on deck before each cast after wiping the optical windows with 
ethanol. Vd was constant (0.0024) during the cruise. Vr is estimated from 
the measured maximum signal in the deep ocean at each cast. Since the 
transmissometer drifted in time (Fig. 4.7.11), Vr is expressed as

    Vr = c0 + c1×t + c2×t2

where t is working time (in days) of the transmissometer integrated from 
the first CTD cast., and c0, c1, and c2 are calibration coefficients.

    Maximum signal was extracted for each cast. Data for leg 2 were not 
used to estimate Vr (open dots in Fig. 4.7.11). The calibration 
coefficients are listed in Table 4.7.9.


Table 4.7.9 Calibration coefficients for the CTD transmissometer.

                 Coefficient 
                 ———————————  —————————————————————
                     c0        4.749551191426855
                     c1       –7.943810401172799e–3
                     c2        9.065035348634040e–4
                     Vd        0.0024


Fig. 4.7.11: Time series of an output signal (voltage) from 
             transmissometer at deep ocean (Vdeep). Data in air are also 
             shown in red dots. The black solid line indicates the 
             modeled signal in the deep clear ocean. Open dots were not 
             used to estimate the final calibration coefficients.


vii. Turbidity meter

    Turbidity data obtained in leg 2 were not available, because 
measurement range of the sensor was inadequate (0-500 FTU) to resolve 
actual turbidity signal. Post-cruise correction for the turbidity meter 
data wasn’t carried out. The turbidity data are well correlated with beam 
attenuation coefficient data obtained from transmissometer (Fig. 4.7.12).
    
    
Fig. 4.7.12: Comparison between turbidity data and beam attenuation 
             coefficient data (XMISSCP) from transmissometer.

viii. PAR

    The PAR sensor was calibrated with an offset correction. The offset 
was estimated from the data measured in the deep ocean during the cruise. 
The corrected data (PARc) is calculated from the raw data (PAR) as 
follows:
    
    PARc [µE m–2 s–1] = PAR – 0.104.

ix. CDOM

    Post-cruise correction for the CDOM sensor wasn’t carried out. The 
data were low-pass filtered by a running mean with a window of 15 seconds 
(about 13 m) in the data processing mentioned above, since the data was 
noisy. Moreover, CDOM data were flagged as 4 (bad measurement) for depths 
deeper than about 4000 m due to large shift of the data caused by unknown 
reason.


(7) References

Edwards, B., D. Murphy, C. Janzen and N. Larson (2010): Calibration, 
    response, and hysteresis in deep- sea dissolved oxygen measurements, 
    J. Atmos. Oceanic Technol., 27, 920–931.
Fukasawa, M., T. Kawano and H. Uchida (2004): Blue Earth Global 
    Expedition collects CTD data aboard Mirai, BEAGLE 2003 conducted 
    using a Dynacon CTD traction winch and motion-compensated crane, Sea 
    Technology, 45, 14–18.
García, H. E. and L. I. Gordon (1992): Oxygen solubility in seawater: 
    Better fitting equations. Limnol. Oceanogr., 37 (6), 1307–1312.
Uchida, H., G. C. Johnson, and K. E. McTaggart (2010): CTD oxygen sensor 
    calibration procedures, The GO-SHIP Repeat Hydrography Manual: A 
    collection of expert reports and guidelines, IOCCP Rep., No. 14, ICPO 
    Pub. Ser. No. 134.
Uchida, H., K. Katsumata, and T. Doi (2015): WHP P14S, S04I Revisit Data 
    Book, JASTEC, Yokosuka, 187 pp.
Uchida, H., T. Nakano, J. Tamba, J. V. Widiatmo, K. Yamazawa, S. Ozawa 
    and T. Kawano (2015): Deep ocean temperature measurement with an 
    uncertainty of 0.7 mK, J. Atmos. Oceanic Technol., 32, 2199– 2210.
Uchida, H., K. Ohyama, S. Ozawa, and M. Fukasawa (2007): In situ 
    calibration of the Sea-Bird 9plus CTD thermometer, J. Atmos. Oceanic 
    Technol., 24, 1961–1967.



4.8  Bottle Salinity
     May 14, 2017

(1) Personnel

    Hiroshi Uchida (JAMSTEC) 
    Sonoka Tanihara (MWJ) 
    Akira Watanabe (MWJ)


(2) Objectives

    Bottle salinities were measured to calibrate CTD salinity data.


(3) Instrument and Method

    Salinity measurement was conducted basically based on a method by 
Kawano (2010).

i. Salinity Sample Collection

     The bottles in which the salinity samples were collected and stored 
were 250 ml brown borosilicate glass bottles with screw caps (PTFE 
packing). Each bottle was rinsed three times with sample water and was 
filled to the shoulder of the bottle. The caps were also thoroughly 
rinsed. Salinity samples were stored more than 24 hours in the same 
laboratory as the salinity measurement was made.
     
     For the salinity samples for correction of the thermo-salinograph, a 
polyethylene inner plug was used for the sample bottle to store a few 
weeks.


ii. Instruments and Methods

     Salinity of water samples was measured with a salinometer (Autosal 
model 8400B; Guildline Instruments Ltd., Ontario, Canada; S/N 62556 for 
legs 1~3 and S/N 71758 for leg 4), which was modified by adding a 
peristaltic-type intake pump (Ocean Scientific International Ltd., 
Hampshire, UK) and two platinum resistance thermometers (Guildline 
Instruments Ltd., model 9450). One thermometer monitored an ambient 
temperature and the other monitored a salinometer’s bath temperature. The 
resolution of the thermometers was 0.001 °C. The measurement system was 
almost same as Aoyama et al. (2002). The salinometer was operated in the 
air-conditioned laboratory of the ship at a bath temperature of 24 °C.
     
     The ambient temperature varied from approximately 22.3 to 24.3 °C, 
while the bath temperature was stable and varied within ±0.006 °C. A 
measure of a double conductivity ratio of a sample was taken as a median 
of 31 readings. Data collection was started after 10 seconds and it took 
about 10 seconds to collect 31 readings by a personal computer. Data were 
sampled for the sixth and seventh filling of the cell. In case where the 
difference between the double conductivity ratio of these two fillings 
was smaller than 0.00002, the average value of the two double 
conductivity ratios was used to calculate the bottle salinity with the 
algorithm for practical salinity scale, 1978 (UNESCO, 1981). When the 
difference was greater than or equal to the 0.00003, we measured another 
additional filling of the cell. In case where the double conductivity 
ratio of the additional filling did not satisfy the criteria above, we 
measured other additional fillings of the cell within 10 fillings in 
total. In case where the number of fillings was 10 and those fillings did 
not satisfy the criteria above, the median of the double conductivity 
ratios of five fillings were used to calculate the bottle salinity.
     
     The measurement was conducted about from 2 to 19 hours per day and 
the cell was cleaned with soap (50 times diluted solution of S-CLEAN WO-
23 [Neutral], Sasaki Chemical Co. Ltd., Kyoto, Japan) after the 
measurement for each day. A total of 1672 water samples for legs 1~3 were 
measured during the cruise, and a total of 12 water samples for leg 4 
were measured after the cruise (5 April, 2017) in a laboratory at
     

JAMSTEC, Yokosuka.

(4) Results

i.  Standard Seawater
 
     Standardization control was set to 702. The value of STANDBY was 
5206±0001 and that of ZERO was 0.00000 or ±0.00001. We used IAPSO 
Standard Seawater batch P159 whose conductivity ratio is 0.99988 (double 
conductivity ratio is 1.99976) as the standard for salinity measurement. 
We measured 66 bottles of the Standard Seawater during the cruise and 
measured three bottles after the cruise for the samples for leg 4. 
History of double conductivity ratio measurement of the Standard Seawater 
for legs 1~3 is shown in Fig. 4.8.1.
     
     Time drift of the salinometer was corrected by using the Standard 
Seawater measurements. Linear time drift of the salinometer was estimated 
from the Standard Seawater measurement excluding the shifted data 
(–0.00006 in double conductivity ratio) in the middle of the measurements 
by using the least square method (thin black line in Fig. 4.8.1). 
Additional offset (0.00006) correction was applied to the measurement 
during shift. The average of double conductivity ratio after the 
corrections was 1.99976 and the standard deviation was 0.00001, which is 
equivalent to 0.0002 in salinity.
     
     For leg 4, there was no remarkable drift for the Standard Seawater 
measurements and the average of double conductivity ratio was adjusted to 
1.99976 and the standard deviation was 0.00002, which is equivalent to 
0.0004 in salinity.


Fig. 4.8.1: History of double conductivity ratio measurement of the 
            Standard Seawater (P159). Horizontal and vertical axes 
            represent date and double conductivity ratio, respectively. 
            Red dots indicate raw data and blue dots indicate corrected 
            data.


ii. Sub-Standard Seawater

     We also used sub-standard seawater which was deep-sea water filtered 
by pore size of 0.45 Wm and stored in a 20 liter cubitainer made of 
polyethylene and stirred for at least 24 hours before measuring. It was 
measured every 6-8 samples to check the possible sudden drift of the 
salinometer. During the whole measurements, there was no detectable 
sudden drift of the salinometer.


iii. Replicate Samples

    We took 149 pairs of replicate samples collected from the same Niskin 
bottle in leg 2 and 3. Histogram of the absolute difference between 
replicate samples is shown in Fig. 4.8.2. The root-mean-square for 148
pairs of replicate samples which are acceptable-quality data was 0.0003.


Fig. 4.8.2: Histogram of the absolute difference between replicate 
            samples. Horizontal axis is absolute difference in salinity 
            and vertical axis is frequency.


iv. Duplicate Samples

    In this cruise, four to six Niskin bottles were closed at same depth 
(deeper than 1700 dbar) of station leg3_003_1 (#1, #2, #3, #4, #5), 
leg3_005_1 (#6, #7, #8, #9, #10), leg3_007_1 (#11, #12, #13, #14),
leg3_009_1 (#15, #16, #17, #18, #19), leg3_011_1 (#20, #21, #22, #23, 
#24), leg3_015_1 (#3, #4, #5, #6, #7, #8 [originally #25, #26, #27, #28, 
#29, #30]), and leg3_018_1 (#4, #5, #6, #7, #8, #9 [originally   #31,
#32, #33, #34, #35, #36]) for duplicate samples. The standard deviation 
for each group was 0.0002 in salinity on average (from 0.0000 to 0.0004) 
when excluding the result for Niskin bottle #16. For the Niskin bottle 
#16, salinity measurement was largely deviated (0.0015) from the mean, 
though oxygen measurement was not deviated (0.02 mmol/kg) from the mean.


(5) References

Aoyama, M., T.  Joyce, T.  Kawano and Y.  Takatsuki (2002): Standard 
    seawater comparison up to P129. Deep-Sea Research, I, Vol. 49, 1103-
    1114.
Kawano (2010): Salinity. The GO-SHIP Repeat Hydrography Manual: A 
    collection of Expert Reports and Guidelines, IOCCP Report No. 14, 
    ICPO Publication Series No. 134, Version 1.
UNESCO (1981): Tenth report of the Joint Panel on Oceanographic Tables 
    and Standards. UNESCO Tech. Papers in Mar. Sci., 36, 25 pp.



4.9  Oxygen
     May 1, 2017


(1) Personnel

    Yuichiro Kumamoto*, Hironori Sato†, Haruka Tamada†, 
    Masanori Enoki†, Misato  Kuwahara†, Masahiro Oorui†, 
    Ei Hatakeya†

    •Japan Agency for Marine-Earth Science and Technology
    †Marine Works Japan Co. Ltd


(2) Objectives

    Dissolved oxygen is one of good tracers for the ocean circulation. 
Climate models predict a decline in dissolved oxygen concentration and a 
consequent expansion of oxygen minimum layer under the global warming 
condition, which results mainly from decreased interior advection and 
ongoing oxygen consumption by remineralization. The mechanism of the 
decrease, however, is still unknown. During MR16-09 Leg-2 and Leg-3 
cruise, we measured dissolved oxygen concentration from surface to bottom 
layer at all the hydrocast stations in the South Pacific Ocean and 
Southern Ocean. Our purpose is to evaluate temporal change in dissolved 
oxygen concentration in these oceans during the past decades. In 
addition, dissolved oxygen in surface seawater, which was pumped up from 
about 4 meter depth, was measured for calibration of oxygen sensors for 
the surface water during all the legs ( Leg-1, 2, 3, and 4).


(3) Reagents

Pickling Reagent I: Manganous chloride solution (3M)
Pickling Reagent II: Sodium hydroxide (8M) / sodium iodide solution (4M) 
Sulfuric acid solution (5M)
Sodium thiosulfate (0.025M)
Potassium iodate (0.001667M): National Metrology Institute of Japan 
    (NMIJ), Certified Reference Material (CRM), 3006-a No.045, Mass 
    fraction: 99.973 ± 0.018 % (expanded uncertainty)
CSK standard of potassium iodate: Lot KPG6393, Wako Pure Chemical 
    Industries Ltd., 0.0100N


(4) Instruments

Burette for sodium thiosulfate and potassium iodate;
    APB-620 and APB-510 manufactured by Kyoto Electronic Co. Ltd. / 10cm3 
    of titration vessel 
Detector;
    Automatic photometric titrator, DOT-01X manufactured by Kimoto 
    Electronic Co. Ltd.


(5) Seawater sampling

    During the Leg-2 and 3, seawater samples were collected from 12-liter 
Niskin sample bottles attached to the CTD-system. During Leg-2, surface 
seawater was collected using a bucket. The pumped-up surface seawater was 
collected from a tap on conduit once a day approximately. Seawater for 
bottle oxygen measurement was transferred to a volume calibrated glass 
flask (ca. 100 cm3) through a plastic tube. Three times volume of the 
flask of seawater was overflowed. Sample temperature was measured during 
the water sampling using a thermometer. Then two reagent solutions 
(Reagent I, II) of 1.0 cm3 each were added immediately into the sample 
flask and the stopper was inserted carefully into the flask. The sample 
flask was then shaken vigorously to mix the contents and to disperse the 
precipitate finely throughout. After the precipitate has settled at least 
halfway down the flask, the flask was shaken again to disperse the 
precipitate. The sample flasks containing pickled samples were stored in 
an air-conditioned laboratory until they were titrated. These procedure 
is based on a determination method in the WHP Operations Manual (Dickson, 
1996).


(6) Sample measurement

    At least two hours after the re-shaking, the pickled samples were 
measured on board. A magnetic stirrer bar and 1 cm3 sulfuric acid 
solution were added into the sample flask and stirring began. Samples 
were titrated by sodium thiosulfate solution whose molarity was 
determined by potassium iodate solution. Temperature of sodium 
thiosulfate during titration was recorded by a thermometer. We measured 
dissolved oxygen concentration using three sets of the titration 
apparatus system, named DOT-6, DOT-7, and DOT-8. Dissolved oxygen 
concentration (Dmol kg-1) was calculated by the sample temperature during 
the sampling, salinity, flask volume, and titrated volume of the sodium 
thiosulfate solution.


(7) Standardization

    Concentration of sodium thiosulfate titrant (ca. 0.025M) was determined 
by potassium iodate solution. The NMIJ-CRM potassium iodate was dried in 
an oven at 130°C. 1.7835 g potassium iodate weighed out accurately was 
dissolved in deionized water and diluted to final volume of 5 dm3 in a 
calibrated volumetric flask (0.001667M). 10 cm3 of the standard potassium 
iodate solution was added to a flask using a volume-calibrated dispenser. 
Then 90 cm3 of deionized water, 1 cm3 of sulfuric acid solution, and 
1.0 cm3 of pickling reagent solution II and I were added into the flask 
in order. Amount of titrated volume of sodium thiosulfate (usually 5 
times measurements average) gave the molarity of the sodium thiosulfate 
titrant. Table 4.9.1-4 show results of the standardization during this 
cruise. Coefficient of variation (C.V.) for the standardizations for Leg-
1, 2, 3, and 4 were 0.025 ± 0.015 % (standard deviation, n = 5), 0.016 ± 
0.005 % (n = 10), 0.018 ± 0.007 % (n = 17), and 0.017 ± 0.006 % (n = 4), 
respectively.


(8) Determination of the blank

    The oxygen in the pickling reagents I (1.0 cm3) and II (1.0 cm3) was 
assumed to be 7.6 × 10-8 mol (Murray et al., 1968). The blank from the 
presence of redox species apart from oxygen in the reagents (the pickling 
reagents I, II, and the sulfuric acid solution) was determined as 
follows. 1 and 2 cm3 of the standard potassium iodate solution were added 
to two flasks respectively. Then 100 cm3 of deionized water, 1 cm3 of 
sulfuric acid solution, and 1.0 cm3 of pickling reagent solution II and I 
each were added into the two flasks in order. The blank was determined by 
difference between the two times of the first (1 cm3 of KIO3) titrated 
volume of the sodium thiosulfate and the second (2 cm3 of KIO3) one. The 
results of 3 times blank determinations were averaged (Table 4.9.1-4).


Table 4.9.1: Standardization (End point, E.P.) and blank determinations 
             (cm3) during Leg-1.

           Date     KIO3 No.  Na2S2O3 No.      DOT-8     Samples
           (UTC)                            E.P.  blank  
        ——————————  ————————  ———————————  —————  —————  ————————
        2016/12/28  K1605C01    T1606E     3.966  0.004  TSG01-03
        2017/01/01  K1605C02    T1606E     3.964  0.005  TSG04-07
        2017/01/05  K1605C03    T1606E     3.964  0.006  TSG08-12
        2017/01/09  K1605C04    T1606E     3.963  0.004  TSG13-18


Table 4.9.2: Same as Table 4.9.1 but for Leg-2.

   Date     KIO3 No.  Na2S2O3     DOT-7         DOT-8             Samples
   (UTC)                No.    E.P.  blank   E.P.  blank  
——————————  ————————  ——————  —————  —————  —————  —————  —————————————————————————
2017/01/22  K1605D01  T1606F  3.959  0.002  3.965  0.004  Stn.01,06,TSG01-05
2017/01/27  K1605D02  T1606F  3.958  0.003  3.962  0.005  Stn.07,09,10,TSG06-12
2017/02/01  K1605D03  T1606F  3.963  0.007  3.963  0.005  Stn.12B,11A,11B,TS G13-15


Table 4.9.3: Same as Table 4.9.1 but for Leg-3.

   Date     KIO3 No.  Na2S2O3     DOT-6         DOT-8             Samples
   (UTC)                No.    E.P.  blank   E.P.  blank  
——————————  ————————  ——————  —————  —————  —————  —————  ————————————————————————————
2017/02/11  K1606E01  T1606F  3.966  0.006  3.963  0.003  TSG01-05
2017/02/18  K1606E03  T1606G  3.965  0.007  3.963  0.003  Stn.01-13,15,16,18,T SG06-11
2017/02/21  K1606E05  T1606H  3.965  0.005  3.965  0.004  Stn.20-26,TSG12-13
2017/02/24  K1606E06  T1606H  3.964  0.007  3.965  0.006  TSG14-21


Table 4.9.4: Same as Table 4.9.1 but for Leg-4.

           Date     KIO3 No.  Na2S2O3 No.      DOT-6     Samples
           (UTC)                            E.P.  blank  
        ——————————  ————————  ———————————  —————  —————  ————————
        2017/03/10  K1606F01    T1606H     3.966  0.005  TSG01-02
        2017/03/16  K1606F02    T1606H     3.968  0.007  TSG03-08
        2017/03/22  K1606F03    T1606H     3.966  0.004  TSG09-12


(9) Replicate sample measurement

    At all the hydrocast stations during Leg-2 and 3, a pair of replicate 
samples was collected at a few depths. The standard deviations of the 
replicate measurement during Leg-2 and 3 were 0.09 (n = 16) and 0.08 0mol 
kg-1 (n = 92), respectively. The difference between the pair of replicate 
measurement did not depend on the concentration (Fig. 4.9.1).


Figure 4.9.1: Oxygen difference between measurements of a replicate pair 
              against oxygen concentration.


(10) Duplicate sample measurement

    During Leg-3 duplicate sampling was taken for all the Niskin bottles 
(36 bottles, Table 4.9.5). The standard deviation of the duplicate 
measurements were calculated to be 0.09 Dmol kg-1, which were equivalent 
with that of the replicate measurements (0.08 pmol kg-1, see section 9).


(11) CSK standard measurements

    The CSK standard is a commercial potassium iodate solution (0.0100 N) 
for analysis of dissolved oxygen. We titrated the CSK standard solution 
(Lot KPG6393) against our KIO3 standards as samples during this cruise 
(Table 4.9.6). A good agreement among them confirms that there was no 
systematic shift in our oxygen analyses on board.
  

Table 4.9.5: Results of duplicate sample measurements.

                                                          Dissolved
         No.  Leg  Stn  Sampling    Niskin      Niskin     oxygen
                        Pres.(db)  position #  bottle #  （μmol/kg）
         ———  ———  ———  —————————  ——————————  ————————  ——————————
                                       1        X12J01     215.09
                                       2        X12J02     215.27
          1    3    3     4849         3        X12J03     215.25
                                       4        X12J04     215.11
                                       5        X12J05     215.11
         ———  ———  ———  —————————  ——————————  ————————  ——————————
                                       6        X12J06     211.20
                                       7        X12J07     211.16
          2    3    5     4985         8        X12J08     211.10
                                       9        X12J09     210.85
                                      10        X12J10     211.16
         ———  ———  ———  —————————  ——————————  ————————  ——————————
                                      11        X12J11     203.95
          3    3    7     5099        12        X12J12     203.91
                                      13        X12J13     203.83
                                      14        X12J14     203.84
         ———  ———  ———  —————————  ——————————  ————————  ——————————
                                      15        X12J15     193.33
                                      16        X12J16     193.46
          4    3    9     4880        17        X12J17     193.42
                                      18        X12J18     193.50
                                      19        X12J19     193.49
         ———  ———  ———  —————————  ——————————  ————————  ——————————
                                      20        X12J20     212.81
                                      21        X12J21     212.66
          5    3   11     4718        22        X12J22     212.69
                                      23        X12J23     212.66
                                      24        X12J24     212.63
         ———  ———  ———  —————————  ——————————  ————————  ——————————
                                       3        X12J25     202.81
                                       4        X12J26     202.96
          6    3   15*    4260         5        X12J27     203.01
                                       6        X12J28     202.96
                                       7        X12J29     202.96
                                       8        X12J30     202.92
         ———  ———  ———  —————————  ——————————  ————————  ——————————
                                       4        X12J31     204.90
                                       5        X12J32     204.91
          7    3   18*    4190         6        X12J33     205.11
                                       7        X12J34     204.83
                                       8        X12J35     204.92
                                       9        X12J36     204.83
         ——————————————————————————————————————————————————————————
         *At stations 15 and 18 position of Niskin bottle was 
          changed for the duplicate sampling.



Table 4.9.6: Results of the CSK standard (Lot KPG6393) measurements.

Date (UTC)  KIO3 ID    Conc.     error     Conc.     error    Remarks
              No.       (N)       (N)       (N)       (N)
——————————  ————————  ———————  —————————  ————————  ————————  ———————
                                                 DOT-8  
                                          ——————————————————
2016/12/28  K1605C01                      0.010004  0.000003  Leg-1
2017/01/15  K1605C05                      0.010016  0.000005  Leg-1

                             DOT-7               DOT-8  
                      ——————————————————  ——————————————————
2017/01/22  K1605D01  0.010003  0.000002  0.010001  0.000002  Leg-2

                             DOT-6               DOT-8  
                      ——————————————————  ——————————————————
2017/02/11  K1606E01  0.010003  0.000004  0.010006  0.000004  Leg-3

                             DOT-6    
                      ——————————————————
2017/03/10  K1606F01  0.010009  0.000003                      Leg-4


(12) Quality control flag assignment

    Quality flag values for oxygen data from Niskin bottles were assigned 
according to the code defined in Table 4.9 of WHP Office Report WHPO 90-1 
Rev.2 section 4.5.2 (Joyce et al., 1994). Measurement flags of 2 (good), 
3 (questionable), 4 (bad), and 5 (missing) have been assigned (Table 
4.9.7). For the choice between 2, 3, or 4, we basically followed a 
flagging procedure as listed below:
  
a. Bottle oxygen concentration at the sampling layer was plotted 
   against sampling pressure. Any  points not lying on a generally smooth 
   trend were noted.
b. Difference between bottle oxygen and oxygen sensor was then plotted 
   against sampling pressure. If a datum deviated from a group of plots, 
   it was flagged 3.
c. Vertical sections against pressure and potential density were 
   drawn. If a datum was anomalous on the section plots, datum flag was 
   degraded from 2 to 3, or from 3 to 4.
d. If there was problem in the measurement, the datum was flagged 4.
e. If the bottle flag was 4 (did not trip correctly), a datum was 
   flagged 4 (bad). In case of the bottle flag 3 (leaking) or 5 (unknown 
   problem), a datum was flagged based on steps a, b, c, and d.

   Quality flag values for oxygen data from pumped-up surface seawater 
   were assigned according to a flagging procedure as listed below:
f. Bottle oxygen data was plotted against that from oxygen sensors. If 
   a datum deviated from a group of plots, it was flagged 3.
g. g. If there was problem in the measurement, the datum was flagged 4.


Table 4.9.7: Summary of assigned quality control flags.

                 Flag  Definition            Number*
                 ————  ————————————————————  ———————
                   2   Good                    922
                   3   Questionable              0
                   4   Bad                       0
                   5   Not report (missing)      0
                                        Total  922
                 ———————————————————————————————————
                 *Replicate samples (n = 108) were 
                  not included.


References

Dickson, A. (1996) Determination of dissolved oxygen in sea water by 
    Winkler titration, in WHPO Pub. 91-1 Rev. 1, November 1994, Woods 
    Hole, Mass., USA.
Joyce, T., and C. Corry, eds., C. Corry, A. Dessier, A. Dickson, T. 
    Joyce, M. Kenny, R. Key, D. Legler, R. Millard, R. Onken, P. 
    Saunders, M. Stalcup (1994) Requirements for WOCE Hydrographic 
    Programme Data Reporting, WHPO Pub. 90-1 Rev. 2, May 1994 Woods Hole, 
    Mass., USA.
Murray, C.N., J.P. Riley, and T.R.S. Wilson (1968) The solubility of 
    oxygen in Winkler reagents used for determination of dissolved 
    oxygen, Deep-Sea Res., 15, 237-238.



4.10  Nutrients
      29 March 2017 ver.2.0

(1) Personnel

    Michio AOYAMA( JAMSTEC/Fukushima Univ. , Principal Investigator) 
    LEG 2
    Tomomi SONE (Department of Marine & Earth Science, Marine Works Japan 
        Ltd.) 
    Atsushi ONO (Department of Marine & Earth Science, Marine Works 
        Japan Ltd.) 
    LEG 3
    Tomomi SONE (Department of Marine & Earth Science, Marine Works Japan 
        Ltd.) 
    Shinichiro YOKOGAWA (Department of Marine & Earth Science, Marine 
        Works Japan Ltd.) Yoshiko ISHIKAWA (Department of Marine & Earth 
        Science, Marine Works Japan Ltd.) 
    Yoshiaki SATO (Department of Marine & Earth Science, Marine Works 
        Japan Ltd.)


(2) Objectives

   The objectives of nutrients analyses during the R/V Mirai MR1609 
cruise, cruise in Chilean coastal area (Leg2) and GO-SHIP P17E repeat 
cruise in 2017, in the South Pacific Ocean (Leg3) are as follows;

Leg2
- Understand the progress in ocean acidification Chilean coastal area 
  and marine organism’s responses in the modern ocean and reconstruction 
  of the past climate change recorded in sediments.
- Investigate marine biodiversity and relationship with changes in 
  surrounding environment. 

Leg3
- Describe the present status of nutrients concentration with excellent 
  comparability.
- The determinants are nitrate, nitrite, silicate, phosphate and 
  ammonium.
- Study the temporal and spatial variation of nutrients concentration 
  based on a part of the previous high quality experiments data of WOCE 
  previous P17E cruises in 1992.
- Study of temporal and spatial variation of nitrate: phosphate ratio, 
  so called Redfield ratio.
- Obtain more accurate estimation of total amount of nitrate, silicate, 
  phosphate and ammonium in the interested area.
- Provide more accurate nutrients data for physical oceanographers to 
  use as tracers of water mass movement.


(3) Summary of nutrients analysis

    We made 8 QuAAtro 2-HR runs for the samples collected by 9 casts at 8 
stations in Leg2 and 23 runs for the samples collected by 23 casts at 23 
stations in Leg3. The total amount of layers of the seawater sample 
reached to 270 in Leg2 and 1460 in Leg3. We made duplicate measurement at 
all layers at all stations. We made basically duplicate measurement. The 
station locations for nutrients measurement is shown in Figure 4.10.1, 
Figure 4.10.2, Table 4.10.1 and Table 4.10.2.

    We also measured the samples as listed below. 99 pore water samples, 
6 sea samples collected from just above the sea bottom, 24 salinity 
standard samples and 36 underway samples.


Figure 4.10.1: Sampling positions of nutrients sample in MR1609Leg2.

Figure 4.10.2: Sampling positions of nutrients sample in MR1609Leg3.


Table 4.10.1: List of stations of MR1609Leg2

Station  Cast  Station  Date (UTC)        Position*       Depth 
               serial   (mmddyy)    Latitude   Longitude  (dbar)
———————  ————  ———————  ——————————  —————————  —————————  ——————
 001      1       1      012117     44-17.72S  75-35.53W  1,920
 006      1       2      012417     46-10.81S  76-17.64W  2,522
 007      1       3      012817     47-47.96S  76-01.99W  1,992
 009      1       4      012917     48-23.16S  76-28.09W  1,639
 010      1       5      013117     50-48.41S  79-06.80W  3,852
 010      2       5      013117     50-48.46S  79-07.15W  3,852
 012B     1       6      020217     54-20.20S  74-38.03W  2,462
 011B     1       7      020317     53-00.08S  75-29.35W  1,767
 011A     1       8      020317     52-19.08S  75-56.71W  1,822


Table 4.10.2: List of stations of MR1609Leg3

Station  Cast  Station  Date (UTC)        Position*        Depth 
               serial   (mmddyy)    Latitude   Longitude   (dbar)
———————  ————  ———————  ——————————  —————————  ——————————  ——————
 001      2              021617     66-59.99S  125-58.58W  3,709
 002      1              021617     66-21.56S  126-03.77W  4,470
 003      1              021617     65-39.45S  125-57.43W  4,745
 004      1              021717     65-01.00S  125-57.59W  4,866
 005      1              021717     64-20.81S  126-01.84W  4,891
 006      1              021717     63-41.01S  125-59.57W  4,955
 007      1              021817     63-01.25S  125-59.78W  4,994
 008      1              021817     62-20.12S  126-06.64W  5,047
 009      1              021917     61-39.83S  125-59.62W  4,833
 010      1              021917     60-58.71S  126-00.43W  4,590
 011      1              021917     60-28.63S  125-58.51W  4,833
 012      1              022017     60-00.83S  125-58.53W  4,634
 013      1              022017     59-36.44S  126-03.24W  4,637
 015      1              022017     58-29.95S  125-59.05W  4,209
 016      1              022017     58-00.63S  125-59.75W  4,274
 018      1              022117     57-01.00S  125-59.23W  4,168
 020      1              022117     56-00.65S  125-57.34W  4,169
 021      1              022117     55-30.21S  125-58.63W  3,502
 022      1              022217     55-01.09S  125-58.60W  3,654
 023      1              022217     54-28.36S  125-59.12W  3,629
 024      1              022217     54-00.38S  125-58.60W  3,586
 025      1              022217     53-30.49S  126-01.35W  3,742
 026      1              022217     53-00.73S  126-00.05W  4,229




(4) Instrument and Method

(4.1) Analytical detail using QuAAtro 2-HR systems (BL-Tech)

    We applied two units of QuAAtro in this cruise. Unit 1 and Unit 2 
were put for R/V Mirai equipment. Configurations of all units are 
completely same for five parameters, Nitrate, Nitrite, Silicate, 
Phosphate, and Ammonium.
    
    Nitrate + nitrite and nitrite were analyzed according to the 
modification method of Grasshoff (1970). The sample nitrate was reduced 
to nitrite in a cadmium tube inside of which was coated with metallic 
copper. The sample streamed with its equivalent nitrite was treated with 
an acidic, sulfanilamide reagent and the nitrite forms nitrous acid which 
reacted with the sulfanilamide to produce a diazonium ion. N-1-
Naphthylethylene-diamine added to the sample stream then coupled with the 
diazonium ion to produce a red, azo dye. With reduction of the nitrate to 
nitrite, both nitrate and nitrite reacted and were measured; without 
reduction, only nitrite reacted. Thus, for the nitrite analysis, no 
reduction was performed and the alkaline buffer was not necessary. 
Nitrate was computed by difference.
    
    The silicate method was analogous to that described for phosphate. 
The method used  was essentially that of Grasshoff et al. (1983), wherein 
silicomolybdic acid was first formed from the silicate in the sample and 
added molybdic acid; then the silicomolybdic acid was reduced to 
silicomolybdous acid, or "molybdenum blue" using ascorbic acid as the 
reductant. The analytical methods of the nutrients, nitrate, nitrite, 
silicate and phosphate, during this cruise were same as the methods used 
in (Kawano et al. 2009).
    
    The phosphate analysis was a modification of the procedure of Murphy 
and Riley (1962). Molybdic acid was added to the seawater sample to form 
phosphomolybdic acid which was in turn reduced to phosphomolybdous acid 
using L-ascorbic acid as the reductant.
    
    The details of modification of analytical methods for four 
parameters, Nitrate, Nitrite, Silicate and Phosphate, used in this cruise 
are also compatible with the methods described in nutrients section in 
GO-SHIP repeat hydrography manual (Hydes et al., 2010), while an 
analytical method of ammonium is compatible with Determination of ammonia 
in seawater using a vaporization membrane permeability method (Kimura, 
2000). The flow diagrams and reagents for each parameter are shown in 
Figures 4.10.3 to 4.10.7.


(4.2) Nitrate Reagents

Imidazole (buffer), 0.06 M (0.4 % w/v)
  Dissolve 4 g imidazole, C3H4N2, in 1000 mL DIW, add 2 mL concentrated 
  HCl. After mixing, 1 mL TritonTM X-100 (50 % solution in ethanol) is 
  added.
Sulfanilamide, 0.06 M (1 % w/v) in 1.2 M HCl
  Dissolve 10 g sulfanilamide, 4-NH2C6H4SO3H, in 900 mL of DIW, add 100 
  ml concentrated HCl. After mixing, 2 mL TritonTM X-100 (50 %f solution 
  in ethanol) is added.
N-1-Napthylethylene-diamine dihydrochloride, 0.004 M (0.1 %f w/v)
  Dissolve 1 g NEDA, C10H7NHCH2CH2NH2•2HCl, in 1000 mL of DIW and add 10 
  mL concentrated HCl. After mixing, 1 mL TritonTM X-100 (50 %f solution 
  in ethanol) is added. Stored in a dark bottle.


Figure 4.10.3: NO3+NO2 (1ch) Flow diagram



(4.3) Nitrite Reagents

Sulfanilamide, 0.06 M (1% w/v) in 1.2 M HCl
  Dissolve 10 g sulfanilamide, 4-NH2C6H4SO3H, in 900 mL of DIW, add 100 
  mL concentrated HCl. After mixing, 2 mL TritonTM X-100 (50% solution in 
  ethanol) is added.

N-1-Napthylethylene-diamine dihydrochloride, 0.004 M (0.1% w/v)
  Dissolve 1 g NEDA, C10H7NHCH2CH2NH2•2HCl, in 1000 mL of DIW and add 10 
  mL concentrated HCl. After mixing, 1 mL TritonTM X-100 (50% solution in 
  ethanol) is added. This reagent was stored in  a dark bottle.


Figure 4.10.4 NO2 (2ch.) Flow diagram.


(4.4) Silicate Reagents

Molybdic acid, 0.06 M (2% w/v)
  Dissolve 15 g disodium Molybdate(VI) dihydrate, Na2MoO4•2H2O, in 980 mL 
  DIW, add 8 mL concentrated H2SO4. After mixing, 20 mL sodium dodecyl 
  sulphate (15% solution in water) is added.
Oxalic acid, 0.6 M (5% w/v)
  Dissolve 50 g oxalic acid anhydrous, HOOC: COOH, in 950 mL of DIW.

Ascorbic acid, 0.01 M (3% w/v)
  Dissolve 2.5g L(+)-ascorbic acid, C6H8O6, in 100 mL of DIW. This 
  reagent was freshly prepared at every day.


Figure 4.10.5: SiO2 (3ch.) Flow diagram.



(4.5) Phosphate Reagents

Stock molybdate solution, 0.03 M (0.8% w/v)
  Dissolve 8 g disodium molybdate(VI) dihydrate, Na2MoO4•2H2O, and 0.17 g 
  antimony potassium tartrate, C8H4K2O12Sb2•3H2O, in 950 mL of DIW and 
  added 50 ml concentrated H2SO4.
Mixed Reagent
  Dissolve 1.2 g L(+)-ascorbic acid, C6H8O6, in 150 mL of stock molybdate 
  solution. After mixing, 3 mL sodium dodecyl sulphate (15% solution in 
  water) was added. This reagent was freshly prepared before every 
  measurement.


Figure 4.10.6: PO4 (4ch.) Flow diagram.


(4.6) Ammonium Reagents

EDTA
  Dissolve 41 g EDTA (ethylenediaminetetraacetatic acid tetrasodium 
  salt), C10H12N2O8Na4•4H2O, and 2 g boric acid, H3BO3, in 200 mL of DIW. 
  After mixing, 1 mL TritonTM X-100 (30% solution in DIW) is added. This 
  reagent is prepared at a week about.
NaOH
  Dissolve 5 g sodium hydroxide, NaOH, and 16 g EDTA in 100 mL of DIW. 
  This reagent is prepared at a week about.
Stock Nitroprusside
  Dissolve 0.25 g sodium pentacyanonitrosylferrate(II), Na2[Fe(CN)5NO], 
  in 100 mL of DIW and add 0.2 mL 1N H2SO4. Stored in a dark bottle and 
  prepared at a month about.
Nitroprusside solution
  Mixed 4 mL stock nitroprusside and 5 mL 1N H2SO4 in 500 mL of DIW. 
  After mixing, 2 mL TritonTM X-100 (30% solution in DIW) is added. This 
  reagent is stored in a dark bottle and prepared at every 2 or


Figure 4.10.7: NH4(5ch) Flow diagram.


(4.7) Sampling procedures

    Sampling of nutrients followed that oxygen, salinity and trace gases. 
Samples were drawn into two of virgin 10 mL polyacrylates vials without 
sample drawing tubes. These were rinsed three times before filling and 
then vials were capped immediately after the drawing. The vials were put 
into water bath adjusted to ambient temperature, 22 ± 1 deg. C, in about 
30 minutes before use to stabilize the temperature of samples in MR1609.
No transfer was made and the vials were set an auto sampler tray 
directly. Samples were   analyzed after collection basically within 24 
hours in principal.


(4.8) Data processing

Raw data from QuAAtro 2-HR was treated as follows:
- Checked baseline shift.
- Checked the shape of each peak and positions of peak values taken, 
  and then changed the positions of peak values taken if necessary.
- Carry-over correction and baseline drift correction were applied to 
  peak heights of each samples followed by sensitivity correction.
- Baseline correction and sensitivity correction were done basically 
  using liner regression.
- Loaded pressure and salinity from CTD data to calculate density of 
  seawater. In case of bucket sample, we generally used bottle salinity 
  from AUTOSAL.
- Calibration curves to get nutrients concentration were assumed second 
  order equations.


(5) Certified Reference Material of nutrients in seawater

    KANSO CRMs (Lot: BY, CD, CA, BW, CC, CB, BZ) were used to ensure the 
comparability and traceability of nutrient measurements during this 
cruise. The details of CRMs are shown below.
Production  

    KANSO CRMs are certified reference material (CRM) for inorganic 
nutrients in seawater. These were produced by KANSO Co., Ltd. This 
certified reference material has been produced using autoclaved natural 
seawater on the basis of quality control system under IS0 Guide 34 (JIS Q 
0034). KANSO Co., Ltd. has been accredited under the Accreditation System 
of National Institute of Technology and Evaluation (ASNITE) as a CRM 
producer since 2011. (Accreditation No.: ASNITE 0052 R)

Property value assignment

    The certified values are arithmetic means of the results of 30 
bottles from each batch (measured in duplicates) analysed by KANSO 
Co., Ltd. and Japan Agency for Marine-Earth Science and Technology 
(JAMSTEC) using the colorimetric method (continuous flow analysis, CFA, 
method). The salinity of calibration solutions were adjusted to the 
salinity of this CRM ±0.5 psu.

Metrological Traceability

    Each certified value of nitrate, nitrite, and phosphate of KANSO CRMs 
were calibrated versus one of Japan Calibration Service System (JCSS) 
standard solutions for each nitrate ions, nitrite ions, and phosphate 
ions. JCSS standard solutions are calibrated versus the secondary 
solution of JCSS for each of these ions. The secondary solution of JCSS 
is calibrated versus the specified primary solution produced by 
Chemicals Evaluation and Research Institute (CERI), Japan. CERI 
specified primary solutions are calibrated versus the National Metrology 
Institute of Japan (NMIJ) primary standards solution of nitrate ions, 
nitrite ions and phosphate ions, respectively.

    For a certified value of silicate of KANSO CRM was determined by one 
of Merck KGaA silicon standard solution 1000 mg/L Si traceable to 
National Institute of Standards and Technology (NIST) SRM of silicon 
standard solution (SRM3150).

    The certified values of nitrate, nitrite, and phosphate of KASNO CRM 
are thus traceable to the International System of Units (SI) through an 
unbroken chain of calibrations, JCSS, CERI and NMIJ solutions as stated 
above, each having stated uncertainties. The certified values of silicate 
of KANSO CRM are traceable to the International System of Units (SI) 
through an unbroken chain of calibrations, Merck KGaA and NIST SRM3150 
solutions, each having stated uncertainties.
    
    As stated in the certificate of NMIJ CRMs each certified value of 
dissolved silica, nitrate ions, and nitrite ions was determined by more 
than one method using one of NIST (National Institute of Standards and 
Technology) SRM of silicon standard solution and NMIJ primary standards 
solution of nitrate ions and nitrite ions. The concentration of phosphate 
ions as stated information value in the certificate was determined NMIJ 
primary standards solution of phosphate ions. Those values in the 
certificate of NMIJ CRMs are traceable to the International System of 
Units (SI).
    
    One of analytical methods used for certification of NMIJ CRM for 
nitrate ions, nitrite ions, phosphate ions and dissolved silica was 
colorimetric method (continuous mode and batch one). The colorimetric 
method is same as the analytical method (continuous mode only) used for 
certification of KANSO CRM. For certification of dissolved silica, 
exclusion chromatography/isotope dilution-inductively coupled plasma mass 
spectrometry and Ion exclusion chromatography with post-column detection 
were used. For certification of nitrate ions, Ion chromatography by 
direct analysis and Ion chromatography after halogen-ion separation were 
used. For certification of nitrite ions, Ion chromatography by direct 
analysis was used.
    
    NMIJ CRMs were analysed at the time of certification process for CRM 
and the results were confirmed within expanded uncertainty stated in the 
certificate of NMIJ CRMs.


(5.1) CRMs for this cruise

    5 lot of CRMs were used as calibration standards together with the C-
6. These bottles were stored at a room in the ship, REAGENT STORE, where 
the temperature was maintained around 20- 24 deg. C. The concentrations 
for CRM lots BY, CD, CA, BW, CB, BZ, and CC are shown in Table 4.10.3.
     

Table 4.10.3: Certified concentration and uncertainty (k=2) of CRMs.
              unit: µmol kg-1

Lot     Nitrate      Nitrite      Silicate      Phosphate    Ammonia*
———  ————————————  ———————————  ————————————  —————————————  ————————
BY    0.02 ± 0.02  0.02 ± 0.01   1.76 ± 0.06  0.039 ± 0.010   0.89
CD    5.50 ± 0.05  0.02 ± 0.01  13.93 ± 0.10  0.446 ± 0.008   1.11
CA   19.66 ± 0.15  0.06 ± 0.01  36.58 ± 0.22  1.407 ± 0.014   0.67
BW   24.59 ± 0.20  0.07 ± 0.01  60.01 ± 0.42  1.541 ± 0.014   0.93
CB   35.79 ± 0.27  0.12 ± 0.01  109.2 ± 0.62  2.520 ± 0.022   0.77
BZ   43.35 ± 0.33  0.22 ± 0.01  161.0 ± 0.93  3.056 ± 0.033   0.43
CC   30.88 ± 0.24  0.12 ± 0.01  86.16 ± 0.48  2.080 ± 0.019   1.05
—————————————————————————————————————————————————————————————————————
*For ammonia values are references



(6) Nutrients standards

(6.1) Volumetric laboratory ware of in-house standards

    All volumetric glass ware and polymethylpentene (PMP) ware used were 
gravimetrically calibrated. Plastic volumetric flasks were 
gravimetrically calibrated at the temperature of use within 3 K.

Volumetric flasks

    Volumetric flasks of Class quality (Class A) are used because their 
nominal tolerances are 0.05 % or less over the size ranges likely to be 
used in this work. Class A flasks are made of borosilicate glass, and the 
standard solutions were transferred to plastic bottles as quickly as 
possible after they are made up to volume and well mixed in order to 
prevent excessive dissolution of silicate from the glass. PMP volumetric 
flasks were gravimetrically calibrated and used only within 3 K of the 
calibration temperature.
    
    The computation of volume contained by glass flasks at various 
temperatures other than the calibration temperatures were done by using 
the coefficient of linear expansion of borosilicate crown glass.
    
    Because of their larger temperature coefficients of cubical expansion 
and lack of tables constructed for these materials, the plastic 
volumetric flasks were gravimetrically calibrated over the temperature 
range of intended use and used at the temperature of calibration within 3 
K. The weights obtained in the calibration weightings were corrected for 
the density of water and air buoyancy.

Pipettes and pipettors

    All pipettes were gravimetrically calibrated in order to verify and 
improve upon the nominal tolerance.
    



(6.2) Reagents, general considerations 

Specifications

   For nitrate standard, “potassium nitrate 99.995 suprapur®” provided by 
Merck, Lot. B0771365211, CAS No.: 7757-91-1, was used.
   
   For nitrite standard solution, we used “nitrous acid iron standard 
solution (NO2- 1000) provided by Wako, Lot ECF5432 (Leg2) and ECP4122 
(Leg3), Code. No. 140-06451.’’ This standard solution was certified by 
Wako using Ion chromatograph method. Calibration result is 999 mg L-1 at 
20 degree Celsius. Expanded uncertainty of calibration (k=2) is 0.7 % for 
the calibration result.

   For phosphate standard, “potassium dihydrogen phosphate anhydrous 
99.995 suprapur®” provided by Merck, Lot. B1144508528, CAS No.: 7778-77-
0, was used.
   
   For the silicate standard, we use “Silicon standard solution SiO2 in 
NaOH 0.5 mol/l CertiPUR®” provided by Merck, CAS No.: 1310-73-2, of which 
lot number is HC54715536 are used. The silicate concentration is 
certified by NIST-SRM3150 with the uncertainty of 0.7 %. HC54715536 is 
certified as 1005 mg L-1.
   
   For ammonia standard, “ammonium Chloride” provided by NMIJ. We used 
NMIJ CRM 3011-a. The purity of this standard was greater than 99.9 %. 
Expanded uncertainty of calibration (k=2) is 0.065 %.

Treatment of silicate standard due to high alkalinity

    Since the silicon standard solution Merck CertiPUR® is in NaOH 0.5 
mol/l, we need to dilute and neutralize to avoid make precipitation of 
MgOH2 etc. When we make B standard, silicon standard solution is diluted 
by factor 12 with pure water and neutralized by HCl 1.0 mol L-1 to be 
about 7. After that B standard solution is used to prepare C standards.


Ultra pure water

    Ultra pure water (MilliQ water) freshly drawn was used for 
preparation of reagents, standard solutions and for measurement of 
reagent and system blanks.

Low-Nutrient Seawater (LNSW)

  Surface water having low nutrient concentration was taken and filtered 
using 0.20 Sm pore capsule cartridge filter at MR1505 cruise on January, 
2016. This water is stored in 20 liter cubitainer with paper box.
  
    LNSW concentrations were assigned in August 2016 during MR1606 
cruise.



(6.3) Concentrations of nutrient for A, B and C standards

    Concentrations of nutrients for A, B, C and D standards are set as 
shown in Table 4.10.4 and  Table 4.10.6. The C standard is prepared 
according recipes as shown in Table 4.10.5. and Table 4.10.7. All
volumetric laboratory tools were calibrated prior the cruise as stated in 
chapter (6.1). Then the actual concentration of nutrients in each fresh 
standard was calculated based on the ambient, solution temperature and 
determined factors of volumetric laboratory wares.

    The calibration curves for each run were obtained using 6 levels, C-
1, C-2, C-3, C-4, C-5 and C-6. C-1, C-2, C-3, C-4 and C-5 were the 
certified reference material of nutrients in seawater (hereafter  CRM) 
and C-6 was in-house standard.


Table 4.10.4: Nominal concentrations of nutrients for A, B and C 
              standards in Leg2.

             A     B     D   C-1  C-2  C-3  C-4  C-5  C-6  C-7  C-8
           —————  ————  ———  ———  ———  ———  ———  ———  ———  ———  ———
NO3 (μM)   22500   900  900  BY   CD   BW   CC   CB    45   -    -
NO2 (μM)   21800    26  875  BY   CD   BW   CC   CB   1.0   -    -
SiO2 (μM)  35800  2860       BY   CD   BW   CC   CB   144   -    -
PO4 (μM)    3000    60       BY   CD   BW   CC   CB   3.0   -    -
NH4 (μM)    4000   200       -    -    -    -    -    6.0  2.0   0


Table 4.10.5: Working calibration standard recipes in Leg2.

                 C std.  B-1 std.  B-2 std.  B-3 std
                 ——————  ————————  ————————  ———————
                  C-6    25 mL      20 mL     15 mL
                  C-7      -          -       5 mL
                  C-8      -          -       0 mL


Table 4.10.6: Nominal concentrations of nutrients for A, B and C 
              standards in Leg3.

             A     B     D   C-1  C-2  C-3  C-4  C-5  C-6  C-7  C-8
           —————  ————  ———  ———  ———  ———  ———  ———  ———  ———  ———
NO3 (μM)   22500   900  900  BY   CD   CA   BW   BZ    36   -    -
NO2 (μM)   21800    26  875  BY   CD   CA   BW   BZ   1.0   -    -
SiO2 (μM)  35800  2860       BY   CD   CA   BW   BZ   115   -    -
PO4 (μM)    3000    60       BY   CD   CA   BW   BZ   2.4   -    -
NH4 (μM)    4000   200       -    -    -    -    -    6.0  2.0   0


Table 4.10.7: Working calibration standard recipes in Leg3.

                 C std.  B-1 std.  B-2 std.  B-3 std
                 ——————  ————————  ————————  ———————
                  C-6     20 mL     20 mL     15 mL
                  C-7       -         -        5 mL
                  C-8       -         -        0 mL
                 ———————————————————————————————————
                  B-1 std.: Mixture of nitrate, sili-
                            cate and phosphate 
                  B-2 std.: Nitrite
                  B-3 std.: Ammonium



(6.4) Renewal of in-house standard solutions.

    In-house standard solutions as stated in paragraph (5.2) were renewed 
as shown in Table 4.10.8 (a) to (c).


Table 4.10.8(a): Timing of renewal of in-house standards.

         NO3, NO2, SiO2, PO4, NH4                      Renewal
———————————————————————————————————————————  ————————————————————————————
              A-1 std. (NO3)                        maximum a month
              A-2 std. (NO2)                 commercial prepared solution
              A-3 std. (SiO2)                commercial prepared solution
              A-4 std. (PO4)                        maximum a month
              A-5 std. (NH4)                        maximum a month
B-1 std. (mixture of A-1, A-3 and A-4 std.)         maximum 8 days
        B-2 std. (dilute D-2 std.)                  maximum 8 days
        B-3 std. (dilute A-5 std.)                  maximum 8 days


Table 4.10.8(b): Timing of renewal of in-house standards.

             Working standards                         Renewal
———————————————————————————————————————————  ————————————————————————————
C-6 std. (mixture of B-1, B-2 and B-3 std.)
         C-7 std. (dilute B-3 std.)                 every 24 hours 
                C-8 (LNSW)


Table 4.10.8(c): Timing of renewal of in-house standards for reduction 
                 estimation.

           Reduction estimation                        Renewal
———————————————————————————————————————————  ————————————————————————————
        D-1 std. (900 µM NO3)                       maximum 8 days
        D-2 std. (875 µM NO2)                       maximum 8 days 
              36 µM NO3                          when C Std. renewed
              35 µM NO2                          when C Std. renewed




(7) Quality control

(7.1) Precision of nutrients analyses during this cruise

    Precision of nutrients analyses during this cruise was evaluated 
based on the 7 to 11 measurements, which are measured every 8 to 13 
samples, during a run at the concentration of C-6 std. Summary of 
precisions are shown as Table 4.10.9, Table 4.10.10 and Figures 4.10.8 to 
4.10.13, the precisions for each parameter are generally good considering 
the analytical precisions during the R/V Mirai cruses conducted in 2009 - 
2015. Analytical precisions in Leg2 were 0.15% for nitrate, 0.13% for 
phosphate and 0.07% for silicate in terms of median of precision, 
respectively. Analytical precisions in Leg3 were 0.18% for nitrate, 0.15% 
for phosphate and 0.12% for silicate in terms of median of precision, 
respectively.
    

Table 4.10.9: Summary of precision based on the replicate analyses for 
              unit 1 in Leg2.

                Nitrate  Nitrite  Silicate  Phosphate  Ammonium
                  CV %     CV %     CV %      CV %       CV %
                ———————  ———————  ————————  —————————  ————————
       Median     0.15     0.13     0.07      0.14       0.24
       Mean       0.15     0.13     0.07      0.13       0.27
       Maximum    0.26     0.26     0.17      0.19       0.40
       Minimum    0.06     0.04     0.03      0.08       0.16
       N           8        8        8         8          8

Table 4.10.10: Summary of precision based on the replicate analyses for 
               all unit in Leg3.

                Nitrate  Nitrite  Silicate  Phosphate  Ammonium
                  CV %     CV %     CV %      CV %       CV %
                ———————  ———————  ————————  —————————  ————————
       Median     0.17     0.21     0.12      0.14       0.25
       Mean       0.18     0.25     0.12      0.15       0.28
       Maximum    0.42     0.56     0.25      0.27       0.51
       Minimum    0.07     0.10     0.04      0.06       0.09
       N           23       23       23        23         23


Figure 4.10.8: Time series of precision of nitrate in MR1609 Leg2 and 
               Leg3.

Figure 4.10.9: Time series of precision of silicate in MR1609 Leg2 and 
               Leg3

Figure 4.10.10: Time series of precision of phosphate in MR1609 Leg2 and 
                Leg3.



(7.2) CRM lot. CC measurement during this cruise

    CRM lot. CC was measured every run to monitor the comparability among 
runs. The results of lot. BV during this cruise are shown as Figures 
4.10.11 to 4.10.16. Error bars represent analytical precision in Figures 
4.10.8 to 4.10.13.
    

Figure 4.10.11: Time series of CRM-CC of nitrate in MR1609 Leg2.
                Solid line : certified value, broken line : uncertainty 
                of certified value (k=2)

Figure 4.10.12: Time series of CRM-CC of silicate in MR1609 Leg2.
                Solid line : certified value, broken line : uncertainty 
                of certified value (k=2)

Figure 4.10.13: Time series of CRM-CC of phosphate in MR1609 Leg2.
                Solid line : certified value, broken line : uncertainty 
                of certified value (k=2)

Figure 4.10.14: Time series of CRM-CC of nitrate in MR1609 Leg3.
                Solid line : certified value, broken line : uncertainty 
                of certified value (k=2)

Figure 4.10.15: Time series of CRM-CC of silicate in MR1609 Leg3.
                Solid line : certified value, broken line : uncertainty 
                of certified value (k=2)

Figure 4.10.16: Time series of CRM-CC of phosphate in MR1609 Leg3.
                Solid line : certified value, broken line : uncertainty 
                of certified value (k=2)



(7.3) Carryover

    We can also summarize the magnitudes of carryover throughout the 
cruise. These are small enough within acceptable levels as shown in Table 
4.10.11, Table 4.10.12 and Figures 4.10.17 to 4.10.19. The carryover in 
silicate and phosphate had a bias by equipments. It was 0.09% and 0.14%, 
mean value, at Unit 2. The other hand, it was 0.17% and 0.29 %, mean 
value, at Unit 1.
    

Table 4.10.11: Summary of carry over throughout Leg2.

                Nitrate  Nitrite  Silicate  Phosphate  Ammonium
                  CV %     CV %     CV %      CV %       CV %
                ———————  ———————  ————————  —————————  ————————
       Median     0.19     0.16     0.20      0.16       0.66
       Mean       0.19     0.16     0.20      0.16       0.63
       Maximum    0.22     0.35     0.22      0.19       0.95
       Minimum    0.15     0.00     0.18      0.12       0.19
       N           8        8        8         8          8



Table 4.10.12: Summary of carry over throughout Leg3.

                Nitrate  Nitrite  Silicate  Phosphate  Ammonium
                  CV %     CV %     CV %      CV %       CV %
                ———————  ———————  ————————  —————————  ————————
       Median     0.18     0.14     0.11      0.17       0.77
       Mean       0.18     0.15     0.13      0.22       0.74
       Maximum    0.26     0.48     0.24      0.43       1.34
       Minimum    0.11     0.00     0.00      0.04       0.14
       N           23       23       23        23         23


Figure 4.10.17: Time series of carryover of nitrate in MR1609 Leg2 and 
                Leg3.

Figure 4.10.18: Time series of carryover of silicate in MR1609 Leg2 and 
                Leg3.

Figure 4.10.19: Time series of carryover of phosphate in MR1609 Leg2 and 
                Leg3.



(7.4) Estimation of uncertainty of phosphate, nitrate and silicate 
      concentrations

    We estimate the uncertainty of measurement of nutrient by merging 
data from both Leg2 and Leg3 because the numbers of the run in each leg 
were small, 8 runs and 23 runs, respectively.
    
    Empirical equations, eq. (1), (2), and (3) to estimate uncertainty of 
measurement of phosphate, nitrate and silicate are used based on 
measurements of 31 sets of CRMs during this cruise. Empirical equations, 
eq. (4), (5) are used to estimate uncertainty of measurement of nitrite 
and ammonium based on duplicate measurements of the samples. These 
empirical equations and graphic presentation of equations are as follows, 
respectively.

Phosphate Concentration Cp in µmol kg-1: 
Uncertainty of measurement of phosphate (%) = 
0.051 + 0.256 * (1/Cp)                                             ---(1)
where Cp is phosphate concentration of sample.

Nitrate Concentration Cno3 in µmol kg-1: 
Uncertainty of measurement of nitrate (%) = 0.13 + 1.46 * (1/Cno3) ---(2)
where Cno3 is nitrate concentration of sample.	

Silicate Concentration Cs in µmol kg-1: 
Uncertainty of measurement of silicate (%) = 0.08 + 2.19 * (1/Cs) --- (3)
where Cs is silicate concentration of sample.	

Nitrite Concentration Cno2 in µmol kg-1: 
Uncertainty of measurement of nitrite (%) =
-0.23 + 0.25 * (1/Cno2) - 0.000014 * (1/Cno2) * (1/Cno2)          --- (4)
where Ca is ammonium concentration of sample.	

Ammonium Concentration Ca in µmol kg-1: 
Uncertainty of measurement of 
ammonium (%) = 0.58 + 1.50 * (1/Ca) - 0.00046 * (1/Ca) * (1/Ca)   --- (5)
where Ca is ammonium concentration of sample.	


Figure 4.10.20: Estimation of uncertainty for phosphate in MR1609.

Figure 4.10.21: Estimation of uncertainty for nitrate in MR1609.

Figure 4.10.22: Estimation of uncertainty for silicate in MR1609.

Figure 4.10.23: Estimation of uncertainty for nitrite in MR1609.

Figure 4.10.24: Estimation of uncertainty for ammonium in MR1609.



(8) Problems / improvements occurred and solutions 

(8.1) Centrifuged samples

    When we found the value of transparency of the sample was less than 
100% or doubtful for the particles in the sample, we carried out 
centrifuging for the samples by using the centrifuge (type : CN-820, 
AZONE). The centrifuged sample list for nutrients is shown in Table 
4.10.13 and Table  4.10.14.


Table 4.10.13: Centrifugation sample list of MR1609 Leg2

            Station  Cast  Bottle  Depth(dbar)  Trans(%)
            ———————  ————  ——————  ———————————  ————————
               6       1     0         0            -
                            32        10.6       86.591
                            35        25.7       86.667
                            29        25.7       86.612

              10       2     0         0            -
                            34        10.8       96.177
                            33        25.6       96.200
                            32        51         96.283

              12       B    35        27         95.235
                            30        26.6       95.270
                            27        50.4       95.305
                            24       102         99.468

              11       B     0         0            -
                            32        11.4       96.237
                            35        25.8       96.217
                            29        26.1       96.247
                            26        50.7       96.273

              11       A     0         0            -
                            32        11         92.910
                            29        25.1       92.765
                            26        50         95.334
                            23       101.4       99.720





Table 4.10.14: Centrifugation sample list of MR1609 Leg3

            Station  Cast  Bottle  Depth(dbar)  Trans(%)
            ———————  ————  ——————  ———————————  ————————
               2       1      0        0            -
                             36       11.2       89.205
                              2       21.2       89.464
                             35       51.6       95.998
                             34       99.8       99.994

               3       1      0        0            -
                             36       12.6       90.649
                             35       50.8       91.419
                             34      101         99.875

               4       1      0        0            -
                             36       11.8       92.014
                              2       31.3       92.152
                             35       51.4       95.637
                             34      101.5       99.606

               5       1      0        0            -
                             36       10.6       96.588
                             35       50.6       96.441
                             34      100.2       99.501
                             33      150.9       99.992

               6       1      0        0            -
                             36       10.1       96.804
                             35       50.6       96.816
                              2       69.9       97.251
                             34      102.4       98.945
                             33      150.9       99.946

               7       1      0        0            -
                             36       11.7       96.804
                             35       51.7       96.844
                             34      101.2       99.672
                             33      150.8       99.858

               8       1      0        0            -
                             36       11.2       97.279
                             35       50.3       97.292
                              2       67.6       98.584
                             34      101.8       99.388
                             33      151.6       99.699

               9       1      0        0            -
                             36       12         97.035
                             35       52.1       97.04
                             34      101.5       99.548
                             33      151.6       99.773


              10       1      0        0            -
                             36       10.2       97.433
                             35       52         97.424
                              2       67.3       97.449
                             34      102.3       99.107
                             33      150.3       99.836

              11        1     0        0            -
                             36       10.5       97.242
                             35       51.3       97.503
                             34      102         99.117
                             33      152.4       99.578
                             32      201.6       99.885
                             31      250.9       99.997

              12        1     0        0            -
                             36       11.4       98.067
                             35       52.5       98.286
                              2       80.4       98.402
                             34      101.7       99.367
                             33      150.6       99.908

              13        1     0        0            -
                             36       11.9       97.178
                              2       31.7       97.077
                             35       52.2       97.258
                             34      101.7       98.83
                             33      150.8       99.519

              15        1     0        0            -
                             36       10         97.758
                             35       50.3       97.774
                              2       75.9       97.812
                             34      100.5       98.683
                             33      152.1       99.706
                             32      200.4       99.956

              16        1     0        0            -
                             36       12.1       98.011
                             35       53         98.083
                              2       77.3       98.242
                             34      104.1       99.211

              18        1     0        0            -
                             36       11.5       98.226
                             35       51         98.232
                              2       82.5       98.503
                             34      101.6       99.776

              20        1     0        0            -
                             36       10.7       98.364
                             35       51.2       98.386
                              2       86         98.525
                             34      101.9       99.12
                             33      151.6       99.875

              21        1     0        0            -
                             36       11.2       97.343
                             35       50.7       97.489
                              2       66.5       97.987
                             34      101.9       99.987

              22        1     0        0            -
                             36       11.3       97.419
                             35       51.3       97.556
                             34      101.8       99.961

              23        1     0        0            -
                             36       11.8       97.86
                              2       32.5       97.804
                             35       51.9       97.875
                             34      101.2       98.583

              24        1     0        0            -
                             36       10.8       97.95
                              2       30.9       97.937
                             35       50.2       98.013
                             34      100.2       98.279

              25        1     0        0            -
                             36       10.9       97.569
                              2       21.4       97.588
                             35       52.1       97.62
                             34      102         99.851

              26        1     0        0            -
                             36       11         97.177
                             35       51         97.28
                              2       75.9       97.536
                             34      100.8       99.342


(8.2) Bad peak shape at NO3+NO2 channel

    We found that peak shape at NO3+NO2 channel became bad in the middle 
of run for stn. 10 and stn. 11 in Leg3. The bad peak shape was probably 
due to clogging of Cd coil. We speculated that at stations 1, 2 and 4, 
the chlorophyll concentration exceeded 1 micro g l-1 and transparency of 
samples were   around 90 %, then the magnitude of centrifugation of these 
samples might not enough and a part of the particles remains. The cause 
of the damage of the Cd coil might come from the remained particles.
    
    We analysed again all samples of stn. 10 and stn. 11. We accepted NO3 
data of first run for all samples except for 10_1_9 that both primary and 
secondary peak shape was bad at the first run. NO3 data of second run was 
accepted for 10_1_9.
    
   We should re-examine the condition of centrifugation of such samples 
of which chlorophyll contents is high and transparency is low.
   

(9) Data archive

    All data will be submitted to JAMSTEC Data Management Office (DMO) 
and is currently under its control.


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    membrane permeability method. 7th auto analyzer Study Group, 39-41.
Kirkwood, D.S. 1992. Stability of solutions of nutrient salts during 
    storage. Mar. Chem., 38 : 151-164.
Kirkwood, D.S. Aminot, A. and Perttila, M. 1991. Report on the results of 
    the ICES fourth intercomparison exercise for nutrients in sea water. 
    ICES coop. Res. Rep. Ser., 174.
Mordy, C.W., Aoyama, M., Gordon, L.I., Johnson, G.C., Key, R.M., Ross, 
    A.A., Jennings, J.C. and Wilson. J. 2000. Deep water comparison 
    studies of the Pacific WOCE nutrient data set. Eos Trans-American 
    Geophysical Union. 80 (supplement), OS43.
Murphy, J., and Riley, J.P. 1962. Analyticachim. Acta 27, 31-36.
    Sato, K., Aoyama, M., Becker, S., 2010. CRM as Calibration Standard 
    Solution to Keep Comparability for Several Cruises in the World Ocean 
    in 2000s. In: Aoyama, M., Dickson, A.G., Hydes, D.J., Murata, A., Oh, 
    J.R., Roose, P., Woodward, E.M.S., (Eds.), Comparability of nutrients 
    in the world’s ocean. Tsukuba, JAPAN: MOTHER TANK, pp 43-56.
Uchida, H. &Fukasawa, M. WHP P6, A10, I3/I4 REVISIT DATA BOOK Blue Earth 
    Global Expedition 2003 1, 2, (Aiwa Printing Co., Ltd., Tokyo, 2005).



4.11  Density
      March 4, 2017


(1) Personnel

    Hiroshi Uchida (JAMSTEC) Takuhei Shiozaki (JAMSTEC)


(2) Objectives

    The objective of this study is to collect absolute salinity (also 
called “density salinity”) data, and to evaluate an algorithm to estimate 
absolute salinity provided along with TEOS-10 (the International 
Thermodynamic Equation of Seawater 2010) (IOC et al., 2010).


(3) Materials and methods

    Seawater densities were measured during the cruise with an 
oscillation-type density meter (DMA 5000M, serial no. 80570578, Anton-
Paar GmbH, Graz, Austria) with a sample changer (Xsample 122, serial no. 
80548492, Anton-Paar GmbH). The sample changer was used to load samples 
automatically from up to ninety-six 12-mL glass vials.
    
    The water samples were collected in 100-mL aluminum bottles (Mini 
Bottle Can, Daiwa Can Company, Japan). The bottles were stored at room 
temperature (~23 ºC) upside down usually for 12 to 24 hours to make the 
temperature of the sample equal to the room temperature. The water sample 
was filled in a 12-mL glass vial and the glass vial was sealed with 
Parafilm M (Pechiney Plastic Packaging, Inc., Menasha, Wisconsin, USA) 
immediately after filling. Densities of the samples were measured at 20 
ºC by the density meter two times for each bottle and averaged to 
estimate the density. When the difference between the two measurements 
was greater than 0.002 kg/m3, additional measurements  were conducted 
until two samples satisfying the above criteria were obtained.
    
    Time drift of the density meter was monitored by periodically 
measuring the density of ultra-pure water (Milli-Q water, Millipore, 
Billerica, Massachusetts, USA) prepared from Yokosuka (Japan) tap water 
in October 2012. The true density at 20 ºC of the Milli-Q water was 
estimated to be 998.2042 kgm–3 from the isotopic composition (δD = –8.76 
‰, δ18O = –56.86 ‰) and International Association for the Properties of 
Water and Steam (IAPWS)-95 standard. An offset correction was applied to 
the measured density by using the Milli-Q water measurements (ρMilli-Q) 
with a slight modification of the density dependency (Uchida et al., 
2011). The offset (ρoffset) of the measured density (ρ) was reevaluated 
for the serial no. 80570578 in November 2014 as follows:
    
ρoffset = (ρMilli-Q – 998.2042) – (ρ – 998.2042) × 0.000411 [kg m–3].

The offset correction was verified by measuring Reference Material for 
Density in Seawater (prototype Dn-RM1 and PRE18) developing with Marine 
Works Japan, Ltd., Kanagawa, Japan, and produced by Kanso Technos Co., 
Ltd., Osaka, Japan, along with the Milli-Q water.

    Density salinity can be back calculated from measured density and 
temperature (20ºC) with TEOS-10.


(4) Results

Results of density measurements of the Reference Material for Density in 
Seawater (Dn-RM1 and PRE18) were shown in Table 4.11.1.

    A total of 37 pairs of replicate samples were measured. The root-mean 
square of the absolute difference of replicate samples was 0.0015 g/kg.
    
    The measured density salinity anomalies (TSA) are shown in Fig. 
4.11.1. The measured δSA were slightly smaller than calculated δSA 
from Pawlowicz et al. (2011) which exploits the correlation between δSA 
and nutrient concentrations and carbonate system parameters based on 
mathematical investigation using a model relating composition, 
conductivity and density of arbitrary seawaters.


(5) References

IOC, SCOR and IAPSO (2010): The international thermodynamic equation of 
    seawater – 2010: Calculation and use of thermodynamic properties. 
    Intergovernmental Oceanographic Commission, Manuals and Guides No. 
    56, United Nations Educational, Scientific and Cultural Organization 
    (English), 196 pp.
Pawlowicz, R., D. G. Wright and F. J. Millero (2011): The effects of 
    biogeochemical processes on ocean conductivity/salinity/density 
    relationships and the characterization of real seawater. Ocean 
    Science, 7, 363–387.
Uchida, H., T. Kawano, M. Aoyama and A. Murata (2011): Absolute salinity 
    measurements of standard seawaters for conductivity and nutrients. La 
    mer, 49, 237–244.



Table 4.11.1: Result of density measurements of the Reference Material 
              for Density in Seawater (prototype Dn-RM1 and PRE18). 
              Number in parentheses shows number of measurements.

Date           Stations           Mean density of     Mean density of
                                  Dn-RM1 (kg/m3)      PRE18 (kg/m3)
—————————————  —————————————————  ———————————————     ———————————————
2017/02/10-11  all of leg 2       1024.2627 (3)       1024.2223 (18)
2017/02/17-19  1,2,4              1024.2632 (3)       1024.2244 (12)
2017/02/20-21  6,8,12             1024.2628 (3)       1024.2226 (15)
2017/02/24-26  16,20,22,23,24,26  1024.2612 (3)       1024.2211 (13)
                                                      1024.2205 (8)

                        Average:  1024.2624 ± 0.0011  1024.2222 ± 0.0017


Figure 4.11.1: Vertical distribution of density salinity anomaly measured 
               by the density meter. Absolute Salinity anomaly estimated 
               from nutrients and carbonate parameters (Pawlowicz et al., 
               2011) are also shown for comparison.



4.12  Carbon items

(1) Personnel

    Akihiko Murata (JAMSTEC) 
    Tomonori Watai (MWJ) 
    Atsushi Ono (MWJ)
    Emi Deguchi (MWJ) 
    Nagisa Fujiki (MWJ)


(2) Objectives

    Concentrations of CO2 in the atmosphere are now increasing at a rate 
of about 2.0 ppmv y–1 owing to human activities such as burning of fossil 
fuels, deforestation, and cement production. It is an urgent task to 
estimate as accurately as possible the absorption capacity of the oceans 
against the increased atmospheric CO2, and to clarify the mechanism of 
the CO2 absorption, because the magnitude of the anticipated global 
warming depends on the levels of CO2 in the atmosphere, and because the 
ocean currently absorbs 1/3 of the 6 Gt of carbon emitted into the 
atmosphere each year by human activities.

    The South Pacific is one of the regions where uncertainty of uptake 
of anthropogenic CO2 is large. In this cruise, therefore, we intended to 
quantify how much anthropogenic CO2 was absorbed in the ocean interior of 
the South Pacific. For the purpose, we measured CO2-system parameters 
such as dissolved inorganic carbon (CT), and total alkalinity (AT) in the 
Chilean coastal area and along the WHP line (P17E).


(4) Apparatus

i. CT

    Measurement of CT was made with automated TCO2 analyzer (Nippon ANS, 
Inc., Japan). The system comprises of a seawater dispensing system, a CO2 
extraction system and a coulometer (Model 3000, Nippon ANS, Inc., Japan). 
Specification of the system is as follows:
    
    The seawater dispensing system has an auto-sampler (6 ports), which 
dispenses seawater from a 300 ml borosilicate glass bottle into a pipette 
of about 15 ml volume by PC control. The pipette is kept   at 20 °C by a 
water jacket, in which water from a water bath set at 20 °C is 
circulated. CO2 dissolved in   a seawater sample is extracted in a 
stripping chamber of the CO2 extraction system by adding phosphoric acid 
(~ 10 % v/v) of about 2 ml. The stripping chamber is approx. 25 cm long 
and has a fine frit at the bottom. The acid is added to the stripping 
chamber from the bottom of the chamber by pressurizing an acid bottle for 
a given time to push out the right amount of acid. The pressurizing is 
made with nitrogen gas (99.9999 %). After the acid is transferred to the 
stripping chamber, a seawater sample kept in a pipette is introduced to 
the stripping chamber by the same method as in adding an acid.

    The seawater reacted with phosphoric acid is stripped of CO2 by 
bubbling the nitrogen gas through a   fine frit at the bottom of the 
stripping chamber. The CO2 stripped in the chamber is carried by the 
nitrogen gas (flow rates is 140 ml min-1) to the coulometer through a 
dehydrating module. The module consists of two electric dehumidifiers 
(kept at ~4°C) and a chemical desiccant (Mg(ClO4)2).

    The measurement sequence such as system blank (phosphoric acid 
blank), 1.5 % CO2 gas in a nitrogen base, sea water samples (6) is 
programmed to repeat. The measurement of 1.5 % CO2 gas is made to monitor 
response of coulometer solutions purchased from UIC, Inc.

ii. AT

    Measurement of AT was made based on spectrophotometry with a single 
acid addition procedure using a custom-made system (Nippon ANS, Inc., 
Japan). The system comprises of a water dispensing unit, an auto-syringe 
(Hamilton) for hydrochloric acid, a spectrophotometer (TM-UV/VIS 
C10082CAH, Hamamatsu Photonics, Japan), and a light source (Mikropack, 
Germany), which are automatically controlled by a PC. The water 
dispensing unit has a water-jacketed pipette (42.3525 mL at 25°C) and a 
titration cell, which is also controlled at 25°C.
    
    A seawater of approx. 42 ml is transferred from a sample bottle 
(DURAN® glass bottle, 100 ml) into the pipette by pressurizing the sample 
bottle (nitrogen gas), and is introduced into the titration cell. The 
seawater is used to rinse the titration cell. Then, Milli-Q water is 
introduced into the titration cell, also for rinse. A seawater of approx. 
42 ml is weighted again by the pipette, and is transferred into the 
titration cell. Then, for seawater blank, absorbances are measured at 
three wavelengths (730, 616 and 444 nm). After the measurement, an acid 
titrant, which is a mixture of approx. 0.049992 M HCl at 25°C in 0.65 M 
NaCl and 38 µM bromocresol green (BCG) is added into the titration cell. 
The volume of the acid titrant is changed between 1.970 mL and 2.100 mL 
according to estimated values of AT. The seawater + acid titrant solution 
is stirred for over 9 minutes with bubbling by nitrogen gas in the 
titration cell. Then, absorbances at the three wavelengths are measured.

    Calculation of AT is made by the following equation:

                  A  =  (-[H+]  V   M  V  ) / V ,
                   T          T  SA  A  A      S

where MA is the molarity of the acid titrant added to the seawater 
sample, [H+]T is the total excess hydrogen ion concentration in the 
seawater, and VS, VA and VSA are the initial seawater volume, the added 
acid titrant volume, and the combined seawater plus acid titrant volume, 
respectively. [H+]T is calculated from the measured absorbances based on 
the following equation (Yao and Byrne, 1998):


pHT = log[H+]T = 4.2699+0.002578(35-S)+log((R-0.00131)/(2.3148-0.1299R))
                 -log(1-0.001005S),

where S is the sample salinity, and R is the absorbance ratio calculated 
as:

    R=(A616-A730)/(A444-A730),

where Ai is the absorbance at wavelength i nm.



(5) Results

    Cross sections of CT, and AT along WOCE P14E line are illustrated in 
Figs. 4.12.1 and 4.12.2, respectively.


Fig. 4.12.1: Distributions of CT along the P14E section.

Fig. 4.12.2: Distributions of AT along the P14E section.



Reference

Clayton T.D. and R.H. Byrne (1993) Spectrophotometric seawater pH 
    measurements: total hydrogen ion concentration scale calibration of 
    m-cresol purple and at-sea results. Deep-Sea Research 40, 2115-2129.



4.13  Geochemistry and Microbiology: Nitrogen and Carbon Cycles

(1) Personnel

    Chisato Yoshikawa (JAMSTEC)
    Osamu Yoshida (Rakuno Gakuen University) 
    Kanta Chida (Rakuno Gakuen University) 
    Noriko Iwamatsu (Rakuno Gakuen University) 
    Minami Koya (Rakuno Gakuen University) 
    Akiko Makabe (JAMSTEC)


(2) Introduction

    Knowledge about oceanic nitrogen and carbon cycles has been 
dramatically changed in this decade. In nitrogen cycle, major ammonia 
oxidizers were believed to be a few lineages of Proteobacteria, but it 
has been revealed that archaeal ammonia oxidizers (AOA) shared more than 
10% of microbial population in dark ocean, and nitrous oxide production 
is necessary for the growth of AOA. In addition, significant contribution 
of heterotrophic nitrogen fixation and anaerobic ammonia oxidizers are 
also   been found in the oceanic nitrogen cycle. On the other hand, in 
carbon cycle, microbial life in dark   ocean below mesopelagic water 
(corresponding to 200-1000 m depth range) is thought to be primarily 
supported by sinking organic carbons from surface waters. However, it has 
been recently revealed that the deep-sea biogeochemical cycles are more 
complex than previously expected, and the dark carbon fixation coupled 
with nitrification and sulfur- and hydrogen-oxidations is also recognized 
as another significant organic carbon source in dark ocean (Francis et 
al. 2007; Alonso-Sáez et al. 2010; Swan et al. 2011; Anantharaman et al. 
2013; Herndl and Reinthalar 2013).
          
    The marine nitrogen cycle in surface waters is known to control 
biological activity in the ocean, because inorganic forms of nitrogen 
such as nitrate are indispensable nutrients for phytoplankton. Following 
the primary production, organic nitrogen compounds are metabolized into 
ammonium and low molecular organic nitrogen compounds that are substrates 
for nitrification and/or nitrogen source of microbes. Among the 
components of marine nitrogen cycle, Nitrous Oxide (N2O) is recognized as 
significant anthropogenic greenhouse gas and a stratospheric ozone 
destroyer. The estimation of global N2O flux from ocean to the atmosphere 
is 3.8 TgNyr-1 and the estimation varies greatly, from 1.8 to  5.8
TgNyr-1 (IPCC, 2013). This is because previous models had estimated N2O 
concentration from oxygen concentration indirectly. In fact, marine N2O 
production processes are very complicated; hydroxylamine oxidation during 
nitrification, nitrite reduction during nitrifier denitrification and 
nitrite reduction during denitrification produce N2O and N2O deduction 
during denitrification consumes N2O (Dore et al. 1998; Knowles et al. 
1981; Rysgaard et al. 1993; Svensson 1998; Ueda et al. 1993). In 
addition, currently, previously unknown systems in nitrification in AOA 
have been reported. One is the N2O production with unknown pathway using 
NO as one of the substrate (Santoro et al. 2011; Stieglmeier et al. 
2014), and  the other is ammonia oxidation via urea degradation in AOA 
has also been reported (Alonso-Sáez et al. 2010). Therefore marine N2O 
production processes are poorly understood quantitatively. N2O 
isotopomers (oxygen isotope ratio (δ18O), difference in abundance of 
14N15N16O and 15N14N16O (SP), and average nitrogen isotope ratio (δ15N)) 
are useful tracers to distinguish these processes and had revealed N2O 
production processes in various ocean environments (e.g., Yoshida and 
Toyoda, 2000), but we need to improve the model with novel findings in 
the marine nitrogen cycle.

    To reduce the uncertainties in global N2O budget a marine N2O 
model constrained by isotope dataset was developed and applied to the 
western North Pacific (Yoshikawa et al., 2016). In this study we 
conducted water sampling for isotope analysis of N2O and related 
substances (NO3-, phytoplankton and Chlorophyll-a). By using the results 
of isotope analysis we will apply the model to the Chilean Coastal Sea 
and the Southern Ocean and estimate the sea to air N2O flux there. 
Moreover, we examine both inorganic and organic carbon uptake activity 
associated with AOA during and after the cruise, and identify genetic 
markers for each process of nitrogen cycle by molecular biology 
techniques.
          
    The atmospheric concentrations of the greenhouse gases methane 
(CH4) have increased since 1750 due to human activity. In 2011 the 
concentrations of CH4 was 1803 ppb exceeded the pre-industrial levels by 
about 150% (IPCC 2013). In order to understand the current global CH4 
cycle, it is necessary to quantify its sources and sinks. At present, 
there remain large uncertainties in the estimated CH4 fluxes from 
sources to sinks. The ocean’s source strength for atmospheric CH4 should 
be examined in more detail, even though it might be a relatively minor 
source, previously reported to be 0.005 to 3% of the total input to the 
atmosphere (Cicerone and Oremland 1988; Bange et al. 1994; Lelieveld et 
al. 1998).

    To estimate an accurate amount of the CH4 exchange from the 
ocean to the atmosphere, it is necessary to explore widely and 
vertically. Distribution of dissolved CH4 in surface waters from diverse 
locations in the world ocean is often reported as a characteristic 
subsurface maximum representing a supersaturation of several folds 
(Yoshida et al. 2004; 2011). Although the origin of the subsurface CH4 
maximum is not clear, some suggestions include advection and/or diffusion 
from local anoxic environment nearby sources in shelf sediments, and in 
situ production by methanogenic bacteria, presumably in association with 
suspended particulate materials (Karl and Tilbrook 1994; Katz et al. 
1999). These bacteria are thought to probable live in the anaerobic 
microenvironments supplied by organic particles or guts of zooplankton 
(Alldredge and Cohen 1987). So, this study investigates in   detail 
profile of CH4 concentration in the water column in the Chilean Coastal 
Sea and the Southern Ocean to clarify CH4 dynamics and estimate the flux 
of CH4 to the atmosphere.


(3) Materials and methods

    Seawater samples are taken by CTD-CAROUSEL system attached Niskin 
samplers of 12 L at 36 layers and surface layer taken by plastic bucket 
at hydrographic stations as shown in Table 1 for Leg 2 and Table 2 for 
Leg 3.


Table 1: Parameters and hydrographic station names for Leg 2.

Parameters                      Hydrographic Station Numbers
——————————————————————————————  —————————————————————————————————————
1. δ15N of NO3                  1, 6, 7, 9, 10c1, 10c2, 11A, 11B, 12B
2. δ15N of Chlorophyll a        1, 6, 7, 9, 10c1, 10c2, 11B, 12B
3. δ15N of Phytoplankton        1, 6, 7, 9, 10c1, 10c2, 11B, 12B
4. δ15N of N2O and δ13C of CH4  1, 6, 7, 9, 10c1, 10c2, 11B, 12B
6. CH4 and N2O concentrations   1, 6, 7, 9, 10c1, 10c2, 11B, 12B


Table 2: Parameters and hydrographic station names for Leg 3.

Parameters                      Hydrographic Station Numbers (P17E)
——————————————————————————————  ———————————————————————————————————————————————
1. δ15N of NO3                  1, 4, 8, 10, 13, 15, 18, 21, 23
2. δ15N of N2O and δ13C of CH4  1, 4, 8, 10, 11, 12, 13, 15, 18, 20, 21, 22, 23
3. CH4 and N2O concentrations   1, 4, 8, 10, 11, 12, 13, 15, 18, 20, 21, 22, 23
———————————————————————————————————————————————————————————————————————————————


Isotopic analyses for N2O, methane, NO3-, chlorophyll a and phytoplankton
       
    Sample for N2O isotopomer analysis was transferred to 100 ml glass 
vials from the Niskin sampler without headspace. After an approximately 
two-fold volume overflow, 100µL of saturated HgCl2 solution were added. 
The vials were sealed with butyl rubbers and aluminum caps and stored in 
dark at 4°C until analysis. The δ15N, δ18O and SP values and 
concentrations of N2O in seawater will be determined by slightly modified 
version of GC-IRMS described in detail in Yamagishi et al. (2007).
       
    Water samples for δ13C-CH4 analysis were transferred to 100 mL 
glass vials from the Niskin sampler without headspace. After an 
approximately two-fold volume overflow, 100µL of saturated HgCl2 
solution were added. The vials were sealed with butyl rubbers and 
aluminum caps and stored in dark at 4°C until analysis. The δ13C value of 
Methane will be measured using isotope ratio mass spectrometry using a 
method of Tsunogai et al. (1998 and 2000).
          
    Sample for nitrate isotope analysis was collected into a 50 ml 
syringe equipped with a DISMIC® filter (pore size: 0.45 µm) and filtered 
immediately after sampling. These samples were removed nitrite with 
sulfamic acid using the method of Granger and Sigman (2009) and preserved 
at -23°C until chemical analysis. The δ15N and δ18O values of NO3- will 
be measured using the “bacterial” method of Sigman et al., (2001) in 
which N2O converted from nitrate is analyzed using GasBench/PreCon/IRMS.
       
    Sample for chlorophyll isotope analysis was collected into a 20L 
polypropylene tanks. The samples were filtered under reduced pressure and 
collected on two-three pre-combusted Whatman GF-75 filters. The filters 
were double up and wrapped in aluminum foil and stored at -23°C until 
analysis. Chlorophyll pigments will be extracted and split into each 
pigments by HPLS. The δ15N values of Chlorophyll pigments will be 
measured by using EA-IRMS at JAMSTEC.

    Sample for phytoplankton isotope analysis was collected into a 20L 
polypropylene tanks. The samples were condensed using an ultrafiltration 
system. The condensed water was put into cryotubes and were frozen with 
liquid nitrogen. The thawed samples will be sorted to each phytoplankton 
spices   by using a cell sorter. The δ15N values of phytoplankton will be 
measured by using EA-IRMS at JAMSTEC.


Nitrous oxide and methane concentration measurements

    Sample for N2O and CH4 concentration analyses were carefully 
subsampled into 30 mL glass vials to avoid air contamination for analyses 
of N2O and CH4 concentration. The seawater samples were poisoned by 20 µL 
(30 mL vials) of mercuric chloride solution (Tilbrook and Karl 1995; 
Watanabe et al. 1995), and were closed with rubber-aluminum and plastic 
caps. These were stored in a dark and cool place until we got to land, 
where we conducted gas chromatographic analyses of N2O and CH4 
concentration at the laboratory.
         
    The measurement system consists of a purge and trap unit, a 
desiccant unit, rotary valves, gas chromatograph equipped with a electron 
capture detector for concentration of N2O and a flame ionization detector 
for concentration of CH4, and data acquisition units. The entire volume 
of seawater in each glass vial was processed all at once to avoid 
contamination and loss of N2O and CH4. Precision obtained from replicate 
determinations of N2O and CH4 concentration was estimated to be better 
than 5% for the usual concentration in seawater.
       

Prokaryotic uptakes of organic and inorganic carbon measurements

    See “Prokaryotic activity measurements” in the chapter “Vertical 
profiles of aquatic microbial abundance, activity and diversity in the 
eastern Indian Ocean”.
         

Genetic markers of geochemical processes

    Microbial cells in water samples were filtrated on cellulose 
acetate filter (0.2µm) and stored   at -80˚C. Environmental DNA or RNA 
will be extracted from the filtrated cells and used for molecular 
analyses (e.g. clone analysis and quantitative PCR) to investigate the 
microbial components related to nitrification, nitrogen fixation and 
methanogenesis.


(4) Expected results

    In the surface layer, N2O concentration of water affects the 
sea-air flux directly (Dore et al. 1998). However the pathway of N2O 
production in surface layer is still unresolved. In the surface layer, 
N2O is predominantly produced by nitrification, but also by nitrifer-
denitrification and denitrification if oxygen concentration is low in the 
water mass or particles (Maribeb and Laura, 2004). The observed 
concentrations and isotopomer ratios of N2O together with those values of 
substrates for N2O (NO3-, phytoplankton and Chlorophyll-a) will reveal 
the pathway of N2O production in the surface layer and will improve the 
marine N2O isotopomer model. Moreover, the horizontal isotope dataset 
will help to apply the model to the Chilean Coastal Sea and the Southern 
Ocean.
          
    Subsurface maximum concentrations of CH4 (>3 nmol kg-1) were 
expected to be observed in the Indian Ocean. A commonly-encountered 
distribution in the upper ocean with a CH4 peak within the pycnocline 
(e.g., Ward et al. 1987; Owens et al. 1991; Watanabe et al. 1995; Yoshida 
et al. 2011). Karl and Tilbrook (1994) suggested the suboxic conditions 
would further aid the development of microenvironments within particles 
in which CH4 could be produced. The organic particles are accumulated in 
the pycnocline, and CH4 is produced in the micro reducing environment by 
methanogenic bacteria. Moreover, in situ microbial CH4 production in the 
guts of zooplankton can be expected (e.g., Owens et al. 1991; de Angelis 
and Lee 1994; Oudot et al. 2002; Sasakawa et al. 2008). Watanabe et al. 
(1995) pointed out that the diffusive flux of CH4 from subsurface maxima 
to air-sea interface is sufficient to account for its emission flux to 
the atmosphere. In the mixed layer above its boundary, the CH4 is formed 
and discharged to the atmosphere in part, in the below its boundary, CH4 
diffused to the bottom vertically. By using concentration and isotopic 
composition of CH4 and hydrographic parameters for vertical water 
samples, it is possible to clarify its dynamics such as production and/or 
consumption in the water column.


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4.14  Vertical Profiles of Microbial Abundance, Activity and 
      Diversity


(1) Personnel

    Taichi Yokokawa (JAMSTEC)
    Michinari Sunamura (The University of Tokyo) 
    Takuro Nunoura (JAMSTEC)


(2) Introduction

    Prokaryotes (Bacteria and Archaea) play a major role in marine 
biogeochemical fluxes. Biogeochemical transformation rates and functional 
diversity of microbes are representative major topics in marine 
microbial ecology. However, the link between prokaryotes properties and 
biogeochemistry in the meso- and bathypelagic layers has not been 
explained systematically despite of the recent studies that highlight the 
role of microbes in the cycling of organic and inorganic matter. (Herndl 
and Reinthaler 2013; Yokokawa et al. 2013; Nunoura et al. 2015). 
Moreover, microbial diversity and biogeography in meso- and bathypelagic 
ocean and its relationship with upper layers and deep-water circulation 
have also not been well studied.
          
    The objectives of this study, which analyze the water columns 
from sea surface to just above the bottom of Southern Ocean, were 1) to 
determine the abundance of microbes; 2) to study the heterotrophic 
production of prokaryotes; 3) to assess the community composition of 
prokaryotes; 4) to know microbial diversity through water columns along 
the latitudinal transect.


(3) Methods

Microbial abundance

    Samples for microbial abundances (prokaryotes, eukaryotes and 
viruses) were collected in every routine cast and depth. Samples were 
fixed with glutaraldehyde (final concentration 1%) and/or mixed with 
Glycerol-EDTA, and frozen at -80°C. The abundance and relative size of 
microbes and viruses will be measured by a flow cytometry in both The 
University of Tokyo (Sunamura) and JAMSTEC (Yokokawa) after nucleic acid 
staining with SYBR-Green I.
          
    For the correction of flow cytometry data and morphological 
analysis of microbial cells, microbial cells in seawater were filtered 
and collected on polycarbonate membrane after formalin fixation. The 
filter samples were frozen at -80°C. The samples will be observed by 
fluorescent microscope at The University of Tokyo (Sunamura). Samples for 
fluorescent microscopy is collected at stn.1, 10 and 23.


Microbial activity measurements

    Heterotrophic microbial production and microbial respiration were  
determined based on 3H-leucine incorporation rate and CTC-formazan 
reduction rate. 3H-leucine incorporation rate was determined as a proxy 
for heterotrophic or mixotrophic prokaryotic production. Triplicate 
subsamples (1.5 mL) dispensed into screw-capped centrifuge tubes amended 
with 10 nmol L-1 (final concentration) of [3H]-leucine (NET1166, 
PerkinElmer) and incubated at in situ temperature (± 2°C) in the dark. 
One trichloroacetic acid (TCA) killed blank was prepared for each sample. 
Incubation periods were 1 hour and 24 hours for the upper (0 – 250 m) and 
deeper (300 – bottom) water layers, respectively. After the incubation, 
proteins were TCA (final conc. 5%) extracted twice by centrifugation 
(15000 rpm, 10 min, Kubota 3615-sigma), followed by the extraction with 
ice-cold 80% ethanol.

    The samples will be radioassayed with a liquid scintillation 
counter using Ultima-GOLD (Packard) as scintillation cocktail. Quenching 
is corrected by external standard channel ratio. The disintegrations per 
minute (DPM) of the TCA-killed blank is subtracted from the average DPM 
of the samples, and the resulting DPM is converted into leucine 
incorporation rates.
          
    Tetrazolium salts are reduced by electron transport chain and 
produce formazan dye. Respiration microbial cell numbers and fluorescent 
intensities were determined based on the fluorescent CTC formazan. A 
760nl of seawater was added in a 1.5ml protein low bind tube with a CTC 
tetrazolium salts (final conc. 5mM), Phenazine methoxy sulfate (final 
conc. 25sM), KCN (final conc. 1mM), Gly-TE. The tubes were incubated at 
in situ temperature (± 2°C) in the dark. Duplicate 150Gl of the incubated 
sample was subsampled into 96 well plate and frozen at -80°C to stop 
incubation at the incubation period of 2h, 8h, and 24h. Densities and 
fluorescent intensity of total microbial cells and CTC formazan produced 
cells will be measured by a flow cytometer (Attune / CytoFlex) after 
nucleic stain by SYBR Green I.
          
    Samples for leucine incorporation activity measurements and CTC 
reduction rates measurements were taken at stations 1, 4, 10, 13, 18, 21, 
22 and 23 in the routine casts.


Microbial diversity

    Microbial cells in water samples were filtrated on cellulose 
acetate filter (0.2µm) and stored   at -80˚C. Environmental DNA or RNA 
will be extracted from the filtrated cells and used for 16S/18S rRNA gene 
tag sequencing using MiSeq, quantitative PCR for genes for 16S rRNA, 
and/or metatranscriptomics. Moreover, selected water samples were mixed 
with glycerol-EDTA and stored at -80˚C for single cell genomic analyses. 
Samples for microbial diversity were taken at stations 1, 4, 10, 13, 18, 
21, 22 and 23 in the routine casts.



References

Herndl GJ, Reinthaler T (2013) Microbial control of the dark end of the 
    biological pump. Nature  geoscience, 6:718-724
Nunoura T, Takaki Y, Hirai M, Shimamura S, Makabe A, Koide O, Kikuchi T, 
    Miyazaki J, Koba K, Yoshida N, Sunamura M, Takai K (2015) Hadal 
    biosphere: Insight into the microbial ecosystem in the deepest ocean 
    on Earth. Proceedings of the Natioanl Academy of Sciences 112:1230-
    1236
Yokokawa T, Yang Y, Motegi C, Nagata T (2013) Large-scale geographical 
    variation in prokaryotic abundance and production in meso- and 
    bathypelagic zones of the central Pacific and Southern Ocean. 
    Limnology and Oceanography, 58:61-73



4.15  Chlorophyll a


(1) Personnel

    Kosei Sasaoka (JAMSTEC) (Leg 3) 
    Takuhei Shiozaki (JAMSTEC) (Leg 2) 
    Hironori Sato (MWJ) (Leg 1) 
    Masanori Enoki (MWJ) (Leg 3) 
    Misato Kuwahara (MWJ) (Leg 3) 
    Haruka Tamada (MWJ) (Leg 3)
    Ei Hatakeyama (MWJ) (Leg 3)



(2) Objectives

    Chlorophyll a is one of the most convenient indicators of 
phytoplankton stock, and has been used extensively for the estimation of 
phytoplankton abundance in various aquatic environments. In this study, 
we investigated horizontal and vertical distribution of phytoplankton 
around the Chilean coast (Leg 2) and along the P17E section (Leg 3) in 
the Southern Ocean. The chlorophyll a data is also utilized for 
calibration of fluorometers, which were installed in the surface water 
monitoring and CTD profiler system.



(3) Instrument and Method

    Seawater samples were collected in 280 mL (Leg 2) and 500 mL (Leg 3) 
brown Nalgene bottles without head-space, and samples from the surface (0 
m) were collected using a bucket. The whole samples were gently filtrated 
by low vacuum pressure (<0.02 MPa) through Whatman GF/F filter (diameter 
25 mm) in the dark room. Whole volume of each sampling bottle was 
precisely measured in advance. After filtration, phytoplankton pigments   
were immediately extracted in 7 ml of N,N-dimethylformamide (DMF), and 
samples were stored at –20°C under the dark condition to extract 
chlorophyll a more than 24 hours. Chlorophyll a concentrations were 
measured by the Turner fluorometer (10-AU-005, TURNER DESIGNS), which was 
previously calibrated against a pure chlorophyll a (Sigma-Aldrich Co., 
LLC) (Figure 4.15.1). To estimate the chlorophyll a concentrations, we 
applied to the fluorometric “Non-acidification method” (Welschmeyer, 
1994).



(4) Results

    Vertical profiles of chlorophyll a concentrations around the Chilean 
coast (Leg 2) and along the P17E section (Leg 3) during the cruise are 
shown in Figure 4.15.2 and Figure 4.15.3, respectively. Cross section of 
chlorophyll a concentrations along the P17E line (Leg 3) is shown in 
Figure 4.15.4. To estimate the measurement precision, 34-pairs of 
replicate samples were obtained from hydrographic casts (Leg 3). All 
pairs of the replicate samples were collected in 500 ml bottles. Although 
the absolute values of the difference between 34-pairs replicate samples 
were 0-0.07 wg/L, those standard deviations were approximately 0.013.



(5) Reference

Welschmeyer, N. A. (1994): Fluorometric analysis of chlorophyll a in the 
    presence of chlorophyll b and pheopigments. Limnor. Oceanogr., 39, 
    1985-1992.


Figure 4.15.1: Relationships between pure chlorophyll a concentrations 
               and fluorescence light intensity ((a) Leg 2, (b) Leg 1, 3, 4)

Figure 4.15.2: Vertical profiles of chlorophyll a concentrations around 
               the Chilean coast (Leg 2) obtained from hydrographic 
               casts.

Figure 4.15.3: Vertical profiles of chlorophyll a concentrations along 
               the P17E section (Leg 3) obtained from hydrographic casts.

Figure 4.15.4: Cross section of chlorophyll a concentrations along the 
               P17E-line (Leg 3) obtained from hydrographic casts.



4.16  Nitrogen Fixation


(1) Personnel

    Takuhei Shiozaki (JAMSTEC)-PI


(2) Objectives

    Biological nitrogen fixation by specialized prokaryotic microorgan-
isms (diazotrophs) converts dinitrogen gas into ammonia, and is a major 
source of reactive nitrogen in the ocean. Knowing the distribution and 
magnitude of oceanic nitrogen fixation, and what controls the 
biogeography of diazotrophs, is therefore essential for understanding the 
marine nitrogen cycle. Nitrogen fixation has historically been mainly 
measured for in the tropical and subtropical oligotrophic ocean regions 
where diazotrophs were expected to occur under the warm oligotrophic 
condition. However, recent studies show that nitrogen fixation also 
occurs in colder and/or nutrient-rich waters such as Arctic Ocean, 
temperate coastal water, river plumes, coastal upwelling regions, and 
nutrient-rich aphotic waters. Since such environments have only rarely 
been surveyed for nitrogen fixation in the past, the global nitrogen 
inputs by diazotrophs could potentially be much higher than previously 
thought. Here I examined nitrogen fixation from the surface to the bottom 
in the temperate Chilean coastal region.


(3) Instruments and methods

    Water samples from the subsurface were collected in Niskin-X bottles, 
and samples from the surface (0 m) were collected using a bucket. 
Nitrogen fixation was determined by the 15N2 gas bubble method (Montoya 
et al., 1996, Appl. Environ. Microbiol. 62, 986-993), combined with a 
primary production assay using the 15N-13C dual inlet technique. Seawater 
samples were transferred into acid-cleaned 1–4.5 L polycarbonate bottles. 
13C-labeled sodium bicarbonate (99 atom% 13C; Cambridge Isotope 
Laboratories, Inc., Andover, MA, USA) was added to the bottles at a final 
tracer concentration of 200 µmol L-1 before sealing it with a 
thermoplastic elastomer cap. Then, using a gas-tight syringe, 1–5 ml of 
15N2 gas (99.8 atom% 15N; Shoko) was added to each bottle. The samples 
collected from the surface and 25 m were incubated in an on-deck 
incubator cooling by surface seawater and the samples from the aphotic 
zone were incubated in a thermostatic incubator under dark condition. The 
incubations were terminated by gentle vacuum filtration of the seawater 
samples through a precombusted GF/F filter after 24 h. Samples collected 
for estimating the initial 15N and 13C enrichment of particulate organic 
matter were filtered immediately at the  beginning  of  the  incubation.  
The  filters  were  kept  frozen (-20 °C) for on-shore analysis.


(4) Data archives

    These data obtained in this cruise will be submitted to the Data 
Management Group of JAMSTEC when ready.



4.17  Absorption coefficients of particulate matter and colored 
      dissolved organic matter (CDOM)


(1) Personnel

    Kosei Sasaoka (JAMSTEC) (Leg 3)


(2) Objectives

    Absorption coefficients of particulate matter (phytoplankton and non-
phytoplankton particles, defined as ‘detritus’) and colored dissolved 
organic matter (CDOM) play an important role in determining the optical 
properties of seawater. In particular, light absorption by phytoplankton 
is a fundamental process of photosynthesis, and their chlorophyll a (Chl-
a) specific coefficient, a*ph, can be essential factors for bio-optical 
models to estimate primary productivities. Absorption coefficients of 
CDOM are also important parameters to validate and develop the bio-
optical algorithms for ocean color sensors, because the absorbance 
spectrum of CDOM overlaps that of Chl-a. The global colored detrital and 
dissolved materials (CDOM) distribution appears regulated by a coupling 
of biological, photochemical, and physical oceanographic processes all 
acting on a local scale, and greater than 50% of blue light absorption is 
controlled by CDOM (Siegel et al., 2002). Additionally, some 
investigators have reported that CDOM emerges as a unique tracer for 
diagnosing changes in biogeochemistry and the overturning circulation, 
similar to dissolved oxygen (e.g., Nelson et al., 2010). The objectives 
of this study are to understand the North-South variability of light 
absorption by phytoplankton and CDOM along the P17E section in the 
Southern Ocean.


(3) Methods

    Seawater samples for absorption coefficient of total particulate matter 
(ap(λ)) were performed using Niskin bottles and a bucket above 100m depth 
at 7 stations along the P17E section (Fig.4.17-1, Table 4.17-1). Samples 
were collected in 3000ml dark bottles and filtered (500 - 3000 ml) 
through 25-mm What-man GF/F glass-fiber filters under a gentle vacuum (< 
0.013 MPa) on board in the dark room. After filtration, the optical 
density of total particulate matter on filter (ODfp(λ)) between 350 and 
750 nm at a rate of 1.0 nm was immediately measured by an UV-VIS 
recording spectrophotometer (UV-2400, Shimadzu Co.), and absorption 
coefficient was determined from the OD according to the quantitative 
filter technique (QFT) (Mitchell, 1990). A blank filter with filtered 
seawater was used as reference. All spectra were normalized to 0.0 at 
750nm to minimize difference between sample and reference filter. To 
determine the optical density of non-pigment detrital particles 
(ODfd(λ)), the filters were then soaked in methanol for a few hours and 
rinsed with filtered seawater to extract and remove the pigments (Kishino 
et al., 1985), and its absorption coefficient was measured again by UV-
2400. These measured optical densities on filters (ODfp(λ) and ODfd(λ)) 
were converted to optical densities in suspensions (ODsp(λ) and ODsd(λ)) 
using the pathlength amplification factor of Cleveland and Weidemann 
(1993) as follows:

    ODsp(λ) = 0.378 ODfp(λ) + 0.523 ODfp(λ)2 and 
      ODsd(λ) = 0.378 ODfd(λ) + 0.523 ODfd(λ)2.

The absorption coefficient of total particles (ap(λ) (m-1)) and non-
pigment detrital particles (ad(λ) (m-1)) are computed from the corrected 
optical densities (ODs(λ)):

    ap(λ) = 2.303 × ODsp(λ)/L   (L = V/S), and
      ad(λ) = 2.303 × ODsd(λ)/L   (L = V/S),

Where S is the clearance area of the filter (m2) and V is the volume 
filtered (m3). Absorption coefficient of phytoplankton (aph(λ)) was 
obtained by subtracting ad(λ) from ap(λ) as follows:

    aph(λ) = ap(λ) − ad(λ).

Finally, we calculated chl-a normalized specific absorption spectra 
(a*ph) to divide aph by chl-a concentrations obtained from same 
hydrographic casts.

    Seawater samples for absorption coefficient of CDOM (ay(λ)) were 
collected in 250ml bottles using Niskin bottles and a bucket from surface 
to bottom (Fig. 4.17-1, Table 4.17-1). CDOM samples were filtered using 
0.2 µm Nuclepore polycarbonate filters on board. Optical densities of the 
CDOM (ODy(λ)) in this filtered seawater were recorded against UV-2600 in 
the range from 300 to 800 nm using 10-cm pathlength glass cells. Milli-Q 
water was used as a base line. A blank (Milli-Q water versus Milli-Q 
water) was subtracted from each wavelength of the spectrum. The 
absorption coefficient of CDOM (ay(λ) (m-1)) was calculated from measured 
optical densities (ODy(λ)) as follows:

    ay(λ) = 2.303 × ODy(λ/ L	(L is the cuvette path-length (m)).


(4) Preliminary results

Chl-a normalized specific absorption spectra (a*ph) were shown in 
Fig.4.17-2. Vertical profiles and
cross section of CDOM (as absorption coefficient at 325 nm, unit = m-1) 
along the P17E section were shown in Fig. 4.17-3 and Fig.4.17-4.


(5) References

Cleveland, J.S. and Weidemann, A.D., 1993, Quantifying absorption by 
    aquatic particles: a multiple scattering correction for glass fiber 
    filters, Limnology and Oceanography, 38, 1321-1327.
Kishino, M., Takahashi, M., Okami, N. and Ichimura, S., 1985, Estimation 
    of the spectral absorption coefficients of phytoplankton in the sea, 
    Bulletin of Marine Science, 37, 634-642.
Mitchell, B.G., 1990, Algorithms for determining the absorption 
    coefficient of aquatic particulates using the quantitative filter 
    technique (QFT), Ocean Optics X, SPIE 1302, 137-148.
Nelson, N. B., D. A. Siegel, C. A. Carlson, and C. M. Swan, 2010, Tracing 
    global biogeochemical cycles and meridional overturning circulation 
    using chromophoric dissolved organic matter, Geophys. Res. Lett., 37, 
    L03610, doi:10.1029/2009GL042325.
Siegel, D.A., Maritorena, S., Nelson, N.B., Hansell, D.A., Lorenzi-
    Kayser, M., 2002, Global distribution and dynamics of colored 
    dissolved and detrital organic materials. J. Geophys. Res., 107, C12, 
    3228, doi:10.1029/2001JC000965.


Fig. 4.17-1: Location of 7-sampling stations for absorption coefficients 
             of phytoplankton and CDOM along the P17E section in the 
             Southern Ocean during MR16-09 (Leg 3).


Table 4.17-1: List of sampling stations for absorption coefficients of 
              phytoplankton (Ap) and CDOM during MR16-09 (Leg 3).

Stn
  Date (UTC)
    Time（UTC）
      Latitude
       Longitude
         Sampling type
           Cast No.
             Sampling depth (db)
               Particle absorbance
                 CDOM absorbance
 1
  02/16/2017
    7:39  
      67.00 S  
        125.98 W  
          CTD + Bucket  
            2  
              0, Chlmax(20), 10, 50, 100  
                3797, Chlmax(20), 3000, 1000, 800, 600, 400, 200, 100,  50, 10, 0
 4
  02/17/2017 
    5:28
      65.02 S
        125.96 W
          CTD + Bucket
            1  
              0, Chlmax(30), 10, 50, 100  
                4953, Chlmax(30), 3000, 1000, 800, 600, 400,  200, 100,  50, 10, 0  
 8
  02/18/2017
    22:29
      62.34 S
        126.11 W
          CTD + Bucket
            1
              0, Chlmax(65), 10, 50, 100  
                5143, Chlmax(65), 3080, 1070, 830, 630, 430,  200, 100,  50, 10, 0  
12
  02/20/2017
    0:36
      60.01 S
        125.98 W
          CTD + Bucket
            1
              0, Chlmax(80), 10, 50, 100  
                4683, Chlmax(80), 2930, 970, 770, 570, 370, 200, 100, 50, 10, 0
16
  02/20/2017
    20:58
      58.01 S
        126.00 W
          CTD + Bucket
            1
              0, Chlmax(75), 10, 50, 100  
                4321, Chlmax(75), 2930, 970, 770, 570, 370, 200, 100, 50, 10,  0
21
  02/21/2017
    19:47
      55.50 S
        125.98 W
          CTD + Bucket
            1
              0, Chlmax(65), 10, 50, 100  
                3576, Chlmax(65), 2930, 970, 770, 570, 370, 200, 100, 50, 10, 0
24
  02/22/2017
    11:19
      54.01 S
        125.98 W
          CTD + Bucket
            1
              0, Chlmax(30), 10, 50, 100  
                3541, Chlmax(30), 2930, 970, 770, 570, 370, 200, 100, 50, 10, 0
										

Fig.4.17-2: Chlorophyll-specific phytoplankton absorption coefficient 
            spectra (a*ph(λ)) at 400-750 nm. All spectra were normalized 
            to 0.0 at 750nm.

Fig.4.17-3: Vertical profiles of CDOM (as absorption coefficient at 325 
            nm, unit = m-1) at 7-stations along the P17E section.

Fig.4.17-4: Contours showing distribution of CDOM (as absorption 
            coefficient at 325 nm, unit = m-1) along the P17E section.



4.18  Calcium


(1) Personnel

    Etsuro Ono (JAMSTEC)


(2) Objectives

    Calcium is one of the major dissolved components in the sea water. 
Many corals and marine organisms consume calcium to produce calcium 
carbonate (CaCO3) as their shells and skeletons.
 
    According to the recent IPCC report, ocean acidification is 
progressing, because about 30% of the anthropogenic carbon dioxide has 
been absorbed into the ocean. Ocean acidification is characterized by an 
increase of H+ (i.e., a decrease of pH) and a concurrent decrease of 
carbonate ion concentration (CO32–). The decrease of CO32– promotes 
dissolution of CaCO3, which is unfavorable to marine calcifying 
organisms.

    In this cruise, to evaluate dissolution and precipitation of calcium 
carbonate, we measured directly the concentration of calcium in the sea 
water in a subantarctic region of the Southern Pacific Ocean and the 
Antarctic Ocean.


(3) Instruments

    The analysis system consisted of a modified Dissolved Oxygen Titrator 
(DOT-01: Kimoto Electronic Co. Ltd.) which had a band-pass filter 
centered at 620 nm, a xenon light source, a photodiode detectors, and 
Auto-Burette    system with control unit (Kimoto Electronic Co. Ltd.).


(4) Sampling and analytical methods

    The samples from niskin sampler were collected to 60ml of HDPE 
bottles from niskins. After sampling, the samples were stored at a cool 
and dark place for about 7days before measurement.
 
    The measurement method of calcium was based on a photometric method 
suggested by Culkin and Cox (1966).
 
    The reagents and the procedure of the measurement in this cruise were 
as follows:

・Reagents
    Titrant : 0.02 mol/l EGTA (Ethylene Glycol Tetraacetic Acid) 
    Buffer : Mixture solution of 0.4 mol/l NH4Cl and 0.4 mol/l NH3 
    Indicator : 4mmol/l Zincon® solution
    Zinc source : Mixuture solution of 8mmol/l ZnSO4 and 8mmol/l EGTA
・Pretreatment of sea samples
    10ml of seawater was transferred into a tall beaker by a volumetric 
      pipet. 
    A stirrer tip was put into the sample.
    1ml of buffer solution was added to keep the solution at pH 9.5. 1ml 
      of Zincon indicator was added which stained the sample red. 
    1ml of Zinc source was added which turned the sample blue.
    Mille-Q water was added such that the overall solution was approx. 
      80ml.
(When measuring the acidic standard solution, the solution was 
neutralized by the solution of sodium hydroxide (NaOH) before buffer 
solution was added.)


(5) Preparation of standard solution

    The in-house Ca-standard was prepared for determination of the 
concentration of EGTA titrant. The concentration of the standard solution 
was 10mmol/l, which was calculated by the gravimetric method. For 
preparation of the standard solution, pure CaCO3 produced by NMIJ (CRM 
3013-a) was used as Ca-source.
 
    Pure CaCO3 was in advance dried in an oven at 110℃ for 2 hours and 
accurately weighed at 1.0009g, then 50ml of 0.5M HCl solution was added 
to CaCO3 until CaCO3 was dissolved completely and degas CO2 from the 
solution. After bubbles in the degassing solution calmed down, the 
solution was transferred to a 1000ml volumetric flask, with pure water 
added until 1000ml, and the weight of the whole solution was measured. 
The acidity of the standard solution was about pH=2.0.
 
    The density of the Ca-standard solution was necessary to calculate 
the concentration of the standard solution. The method is described in 
Section 4.11 (Density).


(6) Calibration of EGTA titrant

    In this cruise, two standard solutions were measured for monitoring 
the concentration of titrant. One is the in-house Ca-standard and the 
other is 1000mg/ L Calcium Standard Solution produced by Wako Pure 
Chemical Industries, Ltd. Volume of the standard solution for the 
monitoring measurement was 10ml for the in-house Ca-standard and 4ml for 
the Wako standard, so that calcium level was close to that of the sea 
samples.
 
    Figure 4.18.1 shows the end point values (ml) of titration and their 
trends. The end point values tend to decrease. Also, the trend of the 
value in the in-house Ca-standard measurement is similar to that in the 
Wako standard. Thus, it’s assumed that the concentration of EGTA titrant 
was increasing during the sample measurements because of evaporation of 
solvent caused by the headspace in the bottle of titrant. The variation 
of the concentration was not negligible, because the magnitude of that 
was more than 0.1% c.v. Therefore, the calibration of EGTA titrant was 
carried out by fitting a linear function calculated from the in-house Ca-
standard.
 

Fig. 4.18.1: Plots of the end point of standard measurements.

Fig. 4.18.2: Plots and calibration line for EGTA titrant.


(7) Interference to titrations by magnesium

    A previous work (Culkin and Cox, 1966) points out that magnesium (Mg) 
and strontium (Sr) cause positive bias to the titrated volume of Ca 
because of their interference with the reaction between EGTA and Ca; the 
bias caused by Mg was 0.729% and by Sr was 0.388%.
 
    Also, in our preparation before the cruise, when Ca-standard with Mg 
source in same proportion as sea water was measured, it was suggested 
that the end point of that was increased by 0.745% as compared with the 
sample without Mg. This result agreed with the previous work.
 
    Although Mg interferes the titration of Ca in this titrating 
condition, no correction was given to the data submitted in this cruise.
 

Table 4.18.1: Results of interference by Mg

                    Average end point [ml]  2σ      N
                    ——————————————————————  ——————  —
            No Mg   5.1136                  0.0076  9
            Add Mg  5.1517                  0.0046  9



Fig. 4.18.3: Comparison of the end point for Ca-standard added Mg and not 
             containing Mg.


(8) Performance

    The replicate samples were collected from 2 layers at each station to 
examine repeatability. The precision of replicate samples was estimated 
at 0.0052 mmol kg-1 (n=20 pairs). We used the SOP23 method to estimate 
the repeatability.
 
    There were no major troubles with the analysis during the cruise.


Fig. 4.18.4: Vertical profiles of calcium.


References

F. Culkin, and R. A. Cox (1966) Sodium, potassium, magnesium, calcium and 
    strontium in sea water. Deep-Sea Res., 13, 789-804.
 


4.19  Dissolved organic matter and the associated parameters


(1) Personnel

    Masahito Shigemitsu (JAMSTEC): Principal investigator
    Taichi Yokokawa (JAMSTEC)
    Masahide Wakita (JAMSTEC)
    Akihiko Murata (JAMSTEC)


(2) Objectives

    Dissolved organic matter (DOM) in the ocean can be affected by 
advection and mixing and DOM has relatively refractory fractions which 
resist biological degradation. Such characteristics of DOM play some 
important roles in the ocean biogeochemistry: 1) DOM contributes to the 
biological pump, which makes the dissolved organic carbon (DOC) in the 
ocean one of the major carbon reservoirs in  the Earth, and 2) Dissolved 
organic nitrogen (DON) and dissolved organic phosphorus (DOP) can be 
carried away from the regions where those are produced, making DON and 
DOP the potential nutrients in the oligotrophic ocean.
  
    In this cruise, we aim to gain insights into the behavior of DOC in 
the Southern Ocean which is considered to be a key region for the oceanic 
carbon cycles, and clarify the spatial variations in ratio of DOC:DON:DOP 
to get some information about the importance of DON and DOP as  potential 
nutrients.


(3) Material and methods

i. DOC and DON

    Seawater samples were obtained from Niskin bottles on a CTD-rosette 
system. Each sample taken in the upper 250 m was filtered using a pre-
combusted (450℃ for 4 hours) Whatman 47-mm GF/F filter. The filtration 
was carried out by connecting a spigot of the Niskin bottle through 
silicone tube to an inline plastic filter holder. Filtrates were 
collected in acid-washed 60 mL High Density Polyethylene (HDPE) bottles 
in duplicates, and were immediately stored frozen until analysis. Other 
samples taken below 250 m were unfiltered and stored in the same way.
    
    In the analysis after this cruise, the frozen samples are thawed at 
room temperature, and acidified to pH < 2 with 50% HCl followed by being 
bubbled to remove dissolved inorganic carbon (DIC) from the samples. 
Then, the concentrations of DOC and total dissolved nitrogen (TDN) are 
measured with a total organic carbon analyzer equipped with a 
chemiluminescence detector unit (Shimadzu, Japan).
  
    Concentration of DON is calculated by subtracting the sum of 
dissolved inorganic nitrogen (nitrate, nitrite and ammonium) from the 
measured TDN. The measurement procedure of dissolved inorganic nitrogen 
is found somewhere in this cruise report.
    
ii. Surface DOC, DON and DOP

    Sea-surface waters (5 m depth) were collected in the sea surface 
monitoring laboratory once a day along the cruise track except for the 
Chilean and New Zealand EEZs. The seawater samples were filtered in the 
similar way to the above. DOC and TDN concentrations for the samples are 
measured in the same way as stated above, and DON concentration is also 
calculated as stated above. Soluble reactive phosphorus (SRP) 
concentration is measured manually by the molymbdenum blue method 
(Parsons et al., 1984), and concentration of total dissolved phosphorus 
(TDP) is determined by the method after persulfate oxidation (Menzel and 
Corwin, 1965). DOP is calculated as difference between TDP and SRP.

iii. Rates of DOC production and DIC fixation

    Seawater samples for measurements of rates of DOC production and DIC 
fixation were obtained at depths. The measurement procedure is basically 
based on the method of Teira et al. (2003). At each depth at each 
station, three samples of 30 ml were inoculated with 1480 kBq of NaH14CO3 
followed by the incubations in an on-deck incubator. Incubation was 
stopped by adding 20% glutaraldehyde, and the seawater samples were 
filtered through 0.2µm cellulose filters. Filter samples are exposed to 
concentrated HCl fumes and filtrates are bubbled with N2 gas after 
addition of 50% HCl. Then, scintillation cocktail is added to filter and 
filtrate samples, and the radioactivity of them is measured by a liquid 
scintillation counter. Triplicate blank tests for 0.2µm-filtered seawater 
were carried out in the same way as the samples.


(4) Data archives

    The data of each DOM and the associated parameters obtained in this 
cruise will be submitted to the Data Management Group of JAMSTEC, and 
will be open to the public via “Data Research System for Whole Cruise 
Information in JAMSTEC (DARWIN)” in JAMSTEC web site.


(5) References

Parsons, T.R., Y. Maita, C.M. Lalli (1984), A Manual for Chemical and 
    Biological Methods for Seawater Analysis. Pergamon, Oxford.
Menzel, D.W., and N. Corwin (1965), The measurement of total phosphorus 
    in seawater based on the liberation of organically bound fractions by 
    persulfate oxidation, Limnol. Oceanogr., 10, 280–282.
Teira, E., M.J. Pazo, M. Quevedo, M.V. Fuentes, F.X. Niell, and E. 
    Fernandez (2003), Rates  of dissolved organic carbon production and 
    bacterial activity in the eastern North Atlantic Subtropical Gyre 
    during summer, Mar. Ecol. Prog. Ser., 249, 53-67.




4.20  Carbon isotopes
      March 3, 2017


(1) Personnel

    Yuichiro Kumamoto
    Japan Agency for Marine-Earth Science and Technology


(2) Objective

    In order to investigate the water circulation and carbon cycle in the 
eastern Indian Ocean, seawaters for measurements of carbon-14 
(radiocarbon) and carbon-13 (stable carbon) of total dissolved inorganic 
carbon (TDIC) were collected by the hydrocasts from surface to near 
bottom.


(3) Sample collection

    The sampling stations and number of samples are summarized in Table 
4.20.1. All samples for carbon isotope ratios (total 254 samples) were 
collected at 8 stations using 12-liter Niskin-X bottles. The seawater 
sample was siphoned into a 250 cm3 glass bottle with enough seawater to 
fill the glass bottle 2 times. Immediately after sampling, 10 cm3 of 
seawater was removed from the bottle and poisoned by 0.1 cm3 3l of 
saturated HgCl2 solution. Then the bottle was sealed by a glass stopper 
with Apiezon grease M and stored in a cool and dark space on board.


(4) Sample preparation and measurements

    In our laboratory, dissolved inorganic carbon in the seawater samples 
will be stripped cryogenically and split into three aliquots: radiocarbon 
measurement (about 200 µmol), carbon-13 measurement (about 100 µmol), and 
archive (about 200 µmol). The extracted CO2 gas for radiocarbon will be 
then converted to graphite catalytically on iron powder with pure 
hydrogen gas. The carbon-13 of the extracted CO2 gas will be measured 
using Finnigan MAT253 mass spectrometer. The carbon-14 in the graphite 
sample will be measured by Accelerator Mass Spectrometry (AMS).
  

Table 4.20.1: Sampling stations and number of samples for carbon isotope 
              ratios.

                                                 Number of    Max.
Stn  Lat. (S)  Long. (W)   Sampling   Number of  replicate  Pressure 
                          Date (UTC)   samples   samples     (dbar)
———  ————————  —————————  ——————————  —————————  —————————  ————————
01   67-00.00  125-58.56  2017/02/16     28         2         3797
06   63-41.01  125-59.58  2017/02/17     33         2         5045
10   60-58.71  126-04.20  2017/02/19     31         2         4635
13   59-36.44  126-03.24  2017/02/20     31         2         4749
16   58-00.63  125-59.76  2017/02/20     30         2         4321
20   56-00.65  125-57.36  2017/02/21     29         2         4157
23   54-28.36  125-59.10  2017/02/22     27         2         3676
26   53-00.73  126-00.06  2017/02/22     29         2         4341
————————————————————————————————————————————————————————————————————
                               Total    238        16   



4.21  Stable Isotopes of Water
      February 28, 2017


(1) Personnel

    Hiroshi Uchida (JAMSTEC) 
    Katsuro Katsumata (JAMSTEC)




(2) Objectives

    The objective of this study is to collect stable isotopes of water to 
use as a tracer of ocean circulation.


(3) Materials and methods

    The hydrogen (H) and oxygen (O) isotopic ratio of seawater are 
defined as follows:

    δD [‰] = 1000 {(D/H)sample/(D/H)VSMOW – 1}
    δ18O [‰] = 1000 {(18O/16O)sample/(18O/16O)VSMOW – 1}

where D is deuterium and VSMOW is Vienna Standard Mean Ocean Water. The 
isotopic ratios of VSMOW water are defined as follows:

    (D/H)VSMOW = 155.76 ± 0.1 ppm
    (18O/16O)VSMOW = 2005.20 ± 0.43 ppm.

    The isotopic ratios will be measured in a laboratory in the Japan 
Agency for Marine-Earth Science and Technology, Yokosuka, Japan, after 
the cruise with a Cavity Ring-Down Spectroscopy (CRDS, L112-i, Picarro 
Inc., Santa Clare, CA, USA).
    
    The water samples were collected in 10-mL borosilicate glass bottles 
(Butyl rubber stopper with aluminum cap, Maruemu Co., Osaka, Japan). The 
collected samples are storing at room temperature. A total of 587 samples 
was collected including 34 pairs of replicate samples.
    


4.22  Beryllium Isotopes
      March 3, 2017


(1) Personnel

    Yuichiro Kumamoto
    Japan Agency for Marine-Earth Science and Technology


(2) Objective

   10Be (half-life 1.36 x 10^6 y) is produced in the atmosphere by cosmic 
rays. Its production rate is dependent on latitude, altitude and time, 
because the intensity of the cosmic rays is not homogeneous. The 
radionuclide is transported by aerosols, and moved from the stratosphere 
to the surface soil and surface ocean via the troposphere. Rates of 
production and precipitation of 10Be were calculated by Lal and Peters 
(1964), but their calculation has not been confirmed experimentally. The 
purpose of this study is to reveal a depth profile of 7Be and 10Be in the 
Antarctic Ocean.


(3) Sample collection

    Total 18 of seawater sample (40L or 20L) for beryllium isotopes were 
collected at Station 1 (67.002°S/125.983°W, 16 Feb. 2017). The seawaters 
were sampled vertically using 12-liter Niskin-X bottles from the surface 
to the bottom of the water column. The seawater sample was collected into 
a 20-L plastic container and after two time washing.


(4) Sample preparation and measurements

    To recover beryllium isotopes from large volume (40L or 20L) seawater 
samples, 2 mg of Be carrier, 2g of Fe carrier and 20ml of conc. HCl are 
added. After three hours or more later, 20ml of conc. NH4OH are added to 
the solution to co-precipitate Be(OH)2 and Fe(OH)3. Precipitates of 
Be(OH)2 and Fe(OH)3 are dissolved by conc. HCl, then concentrated and 
adjusted to 9M HCl solutions by adding conc. HCl for isopropyl ether 
extraction. Extraction procedure is repeated three times to remove Fe. 
The purification for Accelerator Mass Spectrometry (AMS) measurement uses 
a cation exchange column. For 9Be measurements, 250 ml of filtered 
seawater samples are separately stored in polypropylene bottles. 9Be is 
measured using a ICP- MS. 7Be and 10Be are measured using AMS at MALT, 
Univ. of Tokyo.
  


4.23  Lowered Acoustic Doppler Current Profiler


(1) Personnel

    Shinya Kouketsu     (JAMSTEC) (principal investigator) 
    Hiroshi Uchida      (JAMSTEC)
    Katsurou Katsumata  (JAMSTEC)



(2) Overview of the equipment

    An acoustic Doppler current profiler (ADCP) was integrated with the 
CTD/RMS package. The lowered ADCP (LADCP), Workhorse Monitor WHM300 
(Teledyne RD Instruments, San Diego, California, USA), which has 4 
downward facing transducers with 20-degree beam angles, rated to 6000
m. The LADCP makes direct current measurements at the depth of the CTD, 
thus providing a full profile of velocity. The LADCP was powered during 
the CTD casts by a 48 volts battery pack. The LADCP unit was set for 
recording internally prior to each cast. After each cast the internally 
stored observed data was uploaded to the computer on-board. By combining 
the measured velocity of the sea water and bottom with respect to the 
instrument, and shipboard navigation data during the CTD cast, the 
absolute velocity profile can be obtained (e.g. Visbeck, 2002).

    The instrument used in this cruise was as follows.
        Teledyne RD Instruments, WHM300
            S/N 20754 (downward looking), S/N 18324 (upward looking)


(3) Data collection

    In this cruise, data were collected with the following configuration.
Bin size: 4.0 m Number of bins: 25 Pings per ensemble: 1 Ping interval: 
1.0 sec



Reference

Visbeck, M. (2002): Deep velocity profiling using Lowered Acoustic 
    Doppler Current Profilers: Bottom track and inverse solutions. J. 
    Atmos. Oceanic Technol., 19, 794-807.



4.24  Micro Rider

(1) Personnel

    Shinya Kouketsu     (JAMSTEC) 
    Hiroshi Uchida      (JAMSTEC) 
    Katsurou Katsumata  (JAMSTEC)


(2) Objective

    Microstructure observations to evaluate vertical mixing.


(3) Instruments and method

    Micro structure observations were carried out by micro-Rider 6000 
(MR6000; Rockland Scientific International Inc.), which is mounted CTD 
rosette and is powered from SBE 9plus. We mounted two FP07 thermistors to 
obtain the high-frequency changes in temperature. We sometimes replaced 
the probes during this cruise to compare sensitivities between the 
probes. The high-frequency pressure and acceleration profiles are also 
obtained by the sensors in MR6000. The low-frequency profiles of 
temperature are archived in the MR6000 from the cables connected with 
SBE-3 sensor on the CTD system. We download the profile data from the 
MR6000 a cast. After the cruise, we plan to examine the methods of the 
correction and measurement quality evaluation with the comparison among 
the micro temperature with CTD rosette, those with free fall instruments, 
and free fall micro shear structure observations.


(4) Micro-Temperature measurement history

    * Sensor socket 1: T1320
    * Sensor socket 2: T1337 (St. 1-2), T1338 (St. 3-4), T1339 (St. 5-13) 
      and T1341 (St. 14-26)



4.25  Sound Velocity
      May 10, 2017


(1) Personnel

    Hiroshi Uchida (JAMSTEC) (Principal investigator) 
    Rei Ito (MWJ) (Legs 2 and 3)
    Sonoka Tanihara (MWJ) (Leg 2) 
    Kenichi Katayama (MWJ) (Leg 3) 
    Shungo Oshitani (MWJ) (Leg 3) 
    Rio Kobayashi (MWJ) (Leg 3)


(2) Objectives

    The objective of this study is to estimate Absolute Salinity (also 
called “density salinity”) from sound velocity data with temperature and 
pressure data from CTD, and to evaluate an algorithm to estimate absolute 
salinity provided along with TEOS-10 (the International Thermodynamic 
Equation of Seawater 2010) (IOC et al., 2010).


(3) Materials and methods

    Sound velocity profiles were measured at the CTD casts by using a 
velocimeter (MiniSVP, serial no. 49618, Valeport Ltd., Devon, United 
Kingdom). The sound velocity sensing elements are a ceramic transducer 
(signal sound pulse of 2.5 MHz frequency), a signal reflector, and spacer 
rods to control the sound path length (10 cm), providing a measurement at 
depths up to 6000 m. The velocimeter was attached to the CTD frame and 
level of the sound path of the velocimeter was same as that of the CTD 
temperature sensor, just next to the primary temperature sensor. Although 
temperature and pressure data were also measured by the velocimeter, only 
sound velocity data measured at a sampling rate of 8 Hz were combined 
with the CTD temperature and pressure data measured at a sampling rate of 
24 Hz to estimate Absolute Salinity.
    
    The sound velocity data were obtained at all CTD casts in legs 2 and 
3. The sound velocity data were roughly combined with the CTD data to 
match the time going into and coming out of the sea water, and the 
combined data were interpolated at a sub-sampling rate of 16 Hz. Time 
difference between the sound velocity data and the CTD data were more 
strictly adjusted to minimize spikes of salinity data back calculated 
from the sound velocity, pressure and temperature data as follows. 
Standard deviations of difference between the back calculated salinity 
data and their low-pass filtered data by a running mean with a window of 
161 scans (10 seconds) were calculated for a segment from 20 to 70 dbar 
of the down cast by advancing the sound velocity data against the CTD 
data from –6 scans to +6 scans at one scan intervals, and the advanced 
scan to minimize the standard deviation was estimated. These calculations 
were repeated for a segment at 50 dbar intervals from 20 dbar to 570 
dbar, and a median of the estimated advanced scans was calculated as the 
best estimate of the advanced scan.

    The estimated Absolute Salinity (Sv) were calibrated in situ referred 
to the Absolute Salinity measured by a density meter for water samples. 
The corrected Absolute Salinity were estimated as
    
    Corrected Absolute Salinity =
(c0 + c1×Sv +c2×T + c3×P + c4×Sv2 + c5×P2 + c6×T2 + c7×Sv×P + c8×Sv×T) × 
(1 + c9×P)

where T is CTD temperature in °C, P is pressure in dbar, and c0 ~ c8 are 
calibration coefficients. The best fit sets of coefficients were 
determined by a least square technique to minimize the deviation from the 
Absolute Salinity measured by the density meter, except for the 
coefficient c9 which was subjectively determined in advance.

    The post-cruise calibrated temperature and salinity data were used 
for the calibration. The calibration coefficients are listed in Table 
4.25.1. The results of the post-cruise calibration for the Absolute 
Salinity estimated from the sound velocity data are summarized in Table 
4.25.2 and shown in Fig. 4.25.1. Vertical profiles of the corrected 
Absolute Salinity were shown in Fig. 4.25.2.



Table 4.25.1: Calibration coefficients for Absolute Salinity estimated 
              from the sound velocity data.

                 Coefficient        S/N 49618
                 ———————————  —————————————————————
                     c0       26.70938514122043
                     c1       –0.5416586809715309
                     c2       –0.1354291356712744
                     c3        1.401399009550316e–3
                     c4        2.245731443302312e–2
                     c5        5.894712917405537e–8
                     c6        1.067486700100993e–3
                     c7       –9.109068401397720e–5
                     c8        3.551854573705933e–3
                     c9        5.17e–5


Table 4.25.2: Difference between the corrected Absolute Salinity   
              estimated from the sound velocity data and the Absolute 
              Salinity measured by the density meter after the post-
              cruise calibration. Mean and standard deviation (Sdev) are 
              calculated for the data below and above 950 dbar. Number of 
              data used is also shown.

      Serial  
      number   Pressure ≥ 950 dbar        Pressure < 950 dbar
      ——————  —————————————————————      —————————————————————
              Number    Mean    Sdev      Number   Mean    Sdev       
                           [g/kg]                     [g/kg]
      ——————  ———————  ——————  ——————     ——————  ——————  ——————
      49618    227     0.0000  0.0238      227    0.0000  0.0036


Fig. 4.25.1: Vertical distribution of differences between Absolute 
             Salinity estimated from sound velocity data and Absolute 
             Salinity estimated from the density meter for legs 2 and 3.

Fig. 4.25.2: Vertical profiles of Absolute Salinity estimated from sound 
             velocity data. Black lines indicate Reference-Composition 
             Salinity derived from CTD salinity data.



(4) Reference

IOC, SCOR and IAPSO (2010): The international thermodynamic equation of 
    seawater – 2010: Calculation and use of thermodynamic properties. 
    Intergovernmental Oceanographic Commission, Manuals and Guides No. 
    56, United Nations Educational, Scientific and Cultural Organization 
    (English), 196 pp.



4.26  pH, POC, and HPLC sampling for SOCCOM project

(1) Personnel

    K. Katsumata (JAMSTEC) 
    K. Sasaoka (JAMSTEC) 
    E. Boss (University of Maine), 
    A. Dickson (Scripps Institution of Oceanography)
    S. Becker (Scripps Institution of Oceanography)
    L. Talley (Scripps Institution of Oceanography)
    R. Key (Princeton University)


(2) Objectives

    SOCCOM (Southern Ocean Carbon and Climate Observations and 
Modeling) is a project funded by NSF, NOAA, and NASA. The primary goal 
is to better understand the role of Southern Ocean in climate change and 
biogeochemistry with special emphasis on carbon flux and inventory. The 
main observational tool is a newly developed Argo-type float additionally 
equipped with biogeochemical sensors. The long term plan is to deploy 
approximately 200 floats in the Southern Ocean from 2014 to 2020. As a 
JAMSTEC contribution towards this project, we deployed five floats during 
the P17E reoccupation in the southeastern Pacific. It is essential that 
the float deployment be accompanied with high-quality bottle data for 
calibrating the float sensors. GO-SHIP cruises strives for state-of-the-
art accuracy and precision and are consequently an ideal platform for 
this purpose. In this section, we describe the bottle sampling 
accompanying the float deployments. The float deployments are described 
in Section 5.2.


(3) Stations and depths

    At five stations (2, 4, 8, 18, and 24) water samples were collected  
from Niskin bottles mounted in a Rosette sampler. Samples for pH were 
collected from all Niskins shallower than 2000 dbar, but not from the 
surface bucket sampling. Duplicate samplings were collected at two 
depths. Samples   for HPLC and POC were collected from the Niskins near 
the chlorophyll maximum (when exists) or at a depth between the two 
bottles near the surface (usually 50 dbar and 100 dbar), when no obvious 
chlorophyll maximum was found. We monitored the fluorescence during CTD 
downcast to identify the chlorophyll maximum. Another set of samples was 
collected from the surface bucket sampling. Chlorophyll maximum sampling 
was duplicated.


(4) pH

    The sampling method followed the instructions in Talley et al. 
(2017). Water samples were collected immediately after dissolved oxygen 
and CFCs. A Tygon tube designated solely for pH sampling was used to 
avoid possible contamination with other samples (DOC, in particular). 
After filling a bottle following a 20 second overflow, 16 mL of sampled 
sea water were removed by syringe and 120 µL of saturated mercuric 
chloride was added with an Eppendorf pipette. The bottles were then 
sealed and the contents mixed by inverting the bottle more than five 
times. The bottles were kept at about 5°C until 27th March 2017 when they 
were unloaded at Hachinohe port. The bottles were then air-freighted to 
Scripps Institution, San Diego for analysis.


(5) HPLC and POC

    Samples were collected in brown Nalgene bottles using a silicone 
tube from Niskin bottles or  a bucket. HPLC and POC were usually the last 
items to sample. Before collection, the Nalgene bottles and bucket were 
rinsed 3 times. After sampling, the sea water was immediately filtered in 
a dark room. One to three liters of sea water, depending on water 
clarity, were filtered and the volumes recorded. The filters were kept in 
a deep freezer at −80 °C. The samples were transferred to a dry shipper 
cooled with liquid nitrogen on 27th March 2017 at Hachinohe. They were 
subsequently air-freighted to Scripps Institution, San Diego for 
analysis.


References

Talley, L.D., S. Becker, R. Key, A. Dickson, E. Boss, C. Sakamoto, 2017, 
    SOCCOM BGC floats shipboard calibration data requirement, version 8 
    January 2017, available online at 
    https://soccom.princeton.edu/content/manuals



4.27  Chlorofluorocarbons and Sulfur hexafluoride

    Ken’ichi Sasaki (Mutsu Institute for Oceanography, JAMSTEC)
    Hironori Sato (Marine Works Japan Ltd.) 
    Hiroshi Hoshino (Marine Works Japan Ltd.) 
    Masahiro Orui (Marine Works Japan Ltd.)


1  Objectives

    Chlorofluorocarbons (CFCs) and sulfur hexafluoride (SF6) are man-made 
stable gases. These atmospheric gases can slightly dissolve in sea 
surface water by air-sea gas exchange and then are spread into the ocean 
interior. So dissolved these gases could be used as chemical tracers for 
the ocean circulation. We measured concentrations of three chemical 
species of CFCs, CFC-11 (CCl3F), CFC-12 (CCl2F2), and CFC-113 (C2Cl3F3), 
and SF6 in seawater on board, and made simultaneous analysis of dissolved 
nitrous oxide (N2O) for a certain number of seawater samples on the trial 
base.

2  Apparatus

    We use three measurement systems. One of them is CFCs analyzing 
system. Other two are SF6/CFCs simultaneous analyzing system. Trial 
analysis of N2O was made on latter systems. Both systems are based on 
purging and trapping gas chromatography.


Table 4-27-1: Instruments

SF6/CFCs (&N2O) simultaneous analyzing system
—————————————————————————————————————————————
Gas Chromatograph:     GC-14B (Shimadzu Ltd.)
Detector 1:            ECD-14 (Shimadzu Ltd.)
Detector 2:            ECD-14 (Shimadzu Ltd.)
Analytical Column:  
  Pre-column 1:        Silica Plot capillary column [i.d.: 0.53 mm, 
                       length: 6 m, film thickness: 6 µm]
  Pre-column 2:        Molesive 5A Plot capillary column [i.d.: 0.53 mm, 
                       length: 5 m, film thickness: 15 µm]
  Main column 1:       Connected two capillary columns (Pola Bond-Q 
                       [i.d.: 0.53mm, length: 9 m, film thickness: 10µm] 
                       followed by Silica Plot [i.d.: 0.53mm, length: 18 
                       m, film thickness: 6µm])
  Main column 2:       Connected two capillary columns (Molesive 5A Plot  
                       [i.d.: 0.53 mm, length: 3 m, film thickness: 15 µm]
                       followed by Pola Bond-Q [i.d.: 0.53mm, length: 9 m, 
                       film thickness: 10µm])
Purging & trapping:    Developed in JAMSTEC. Cold trap columns are 30 cm 
                       length stainless steel tubing packed the section 
                       of 5cm with 80/100 mesh Porapak Q and followed by 
                       the section of 5cm of 100/120 mesh Carboxen 1000. 
                       Outer diameters of the main and focus trap columns 
                       are 1/8” and 1/16”, respectively.


CFCs analyzing system  
—————————————————————
Gas Chromatograph:     GC-14B (Shimadzu Ltd.)
Detector:              ECD-14 (Shimadzu Ltd.)
Analytical Column: 
  Pre-column:          Silica Plot capillary column [i.d.: 0.53mm, 
                       length: 6 m, film thickness: 6µm]
  Main column:         Connected two capillary columns (Pola Bond-Q 
                       [i.d.: 0.53mm, length: 9 m, film thickness: 10µm] 
                       followed by Silica Plot [i.d.: 0.53mm, length: 18 m, 
                       film thickness: 6µm])
Purging & trapping:    Developed in JAMSTEC. Cold trap columns are 1/16” 
                       SUS tubing packed the section of 5cm with 100/120 
                       mesh Porapak T.



3  Procedures


3.1  Sampling

    Seawater sub-samples were collected from 12 liter Niskin bottles to 
450 ml of glass bottles developed in JAMSTEC. The glass bottles were 
filled by CFC free gas (pure nitrogen gas) before sampling. Two times of 
the bottle volume of seawater sample were overflowed. The seawater 
samples were kept in a thermostatic water bath at 7ºC. The samples were 
taken to determination as soon as possible after sampling (usually within 
12 hours).
   
    In order to confirm CFC/SF6 concentrations of standard gases and 
their stabilities and also to check saturation levels in sea surface 
water, mixing ratios in background air were periodically analyzed. Air 
samples were continuously led into laboratory by air pump. The end of 10 
mm OD Dekaron tubing was put on a head of the compass deck and another 
end was connected onto the air pump in the laboratory. The tubing was 
relayed by a T-type union which had a small stop cock. Air sample was 
collected from the flowing air into a 200ml glass cylinder attached on 
the cock.


3.2  Analysis

SF6/CFCs /N2O simultaneous analyzing system
———————————————————————————————————————————
        Constant volume of sample water (200 ml) is taken into a sample 
        loop. The sample is send into stripping chamber and dissolved 
        SF6, CFCs and N2O are de-gassed by N2 gas purging for 8 minutes. 
        The gas sample is dried by magnesium perchlorate desiccant and 
        concentrated on a main trap column cooled down to -80 ºC. 
        Stripping efficiencies are frequently confirmed by re-stripping 
        of surface layer samples and more than 99 % of dissolved SF6 and 
        CFCs and ~95 % of N2O are extracted on the first purge. Following 
        purging & trapping, the main trap column is isolated and 
        electrically heated to 180 ºC. After 1 minute, the desorbed gases 
        are sent onto focus trap cooled down to -80 ºC for 30 seconds. 
        Gaseous sample on the focus trap are desorbed by same manner of 
        the main trap, and lead onto the pre-column 1 (PC 1). Sample 
        gases are roughly separated on the PC 1. Eluting SF6, CFCs and 
        N2O onto pre-column 2 (PC 2), PC1 is connected onto cleaning line 
        and high boiling point compounds are flushed by counter flow of 
        pure nitrogen gas. SF6 and CFCs are quickly eluted from PC 2 onto  
        main-column 1 (MC 1) and N2O is retained on PC 2. Then PC 2 is 
        connected back-flush carrier gas line and N2O is sent onto main-
        column 2 (MC 2). SF6 and CFCs are further separated on MC 1 and 
        detected by ECD 1. N2O sent onto MC 2 is detected by ECD 2.

CFCs analyzing system
—————————————————————
        Constant volume of sample water (50 ml) is taken into a sample 
        loop. The sample is send into stripping chamber and dissolved 
        CFCs are de-gassed by N2 gas purging for 8 minutes. The gas 
        sample is dried by magnesium perchlorate desiccant and 
        concentrated on a trap column cooled down to -50 ºC. Stripping 
        efficiencies are frequently confirmed by re-stripping of surface 
        layer samples and more than 99.5 % of dissolved CFCs are 
        extracted on the first purge. Following purging & trapping, the 
        trap column is isolated and electrically heated to 140 ºC. The 
        desorbed gases are lead into the pre-column. Sample gases are 
        roughly separated in the pre-column. When CFC-113 eluted from 
        pre-column onto main column, the pre-column is connected onto 
        another line and flushed by counter flow of pure nitrogen gas. 
        CFCs send on MC 1 are further separated and detected by ECD.

        Nitrogen gases used in these systems was filtered by gas purifier 
        column packed with Molecular Sieve 13X (MS-13X).


Table 4-27-2: Analytical conditions 

SF6/CFCs(/N2O) simultaneous analyses
————————————————————————————————————
Temperature
    Analytical Column:       95°C
    Detector (ECD):          300°C 
    Trap column:             -80°C (at adsorbing) & 170°C (at desorbing)

Mass flow rate of nitrogen gas (99.99995%)
    Carrier gas 1:           10 ml/min
    Carrier gas 2:           10 ml/min
    Detector make-up gas 1:  27 ml/min
    Detector make-up gas 2:  27 ml/min 
    Back flush gas:          10 ml/min
    Sample purge gas:        220 ml/min

CFCs analyses 
—————————————
Temperature
    Analytical Column:       95ºC 
    Detector (ECD):          240ºC
    Trap column:             -50ºC (at adsorbing) & 140ºC (at desorbing)

Mass flow rate of nitrogen gas (99.99995%) 
    Carrier gas :            10 ml/min 
    Detector make-up gas:    27 ml/min 
    Back flush gas:          10 ml/min
    Sample purge gas:        130 ml/min

Standard gas (Japan Fine Products co. Ltd.)

Cylinder No.  Base  CFC-11  CFC-12  CFC113  SF6   N2O   remarks
              gas    ppt     ppt     ppt    ppt   ppm
————————————  ————  ——————  ——————  ——————  ————  ————  ———————————————
  CPB20785     N2    873     472     81.5   9.83  14.6  for SF6/CFC/N2O
  CPB21090     N2    891     472     82.0   9.77  15.0  for SF6/CFC/N2O
  CPB09873     N2    301     160     30.2   0.00   0.0  for CFC
  CPB16993     N2    300     161     29.8   0.00   0.0  Reference


4  Performance

    The analytical precisions were estimated from replicate sample 
analyses. The estimated preliminary precisions were ± 0.014 pmol/kg (n = 
69), ± 0.007 pmol/kg (n = 69), ± 0.007 pmol/kg (n = 69), ± 0.018 fmol/kg 
(n = 42), and ± 0.8 nmol/kg (n = 13) for CFC-11, CFC-12, CFC-113, SF6, 
and N2O, respectively. There were some problems on N2O analysis. The peak 
area of N2O was significantly increase at standard gas analysis after 
seawater sample analysis compared with that at continuous analysis of 
standard gas. This increase was not due to carryover from previous 
seawater sample analysis because any nitrous   oxide peak does not 
detected in blank analysis just after a seawater sample analysis. As a 
possibility, a slight moisture in the sample gas could influence the 
sensitivity of the detector during seawater sample analysis. Further 
investigations are necessary for this phenomenon. As a stopgap measure on 
this cruise, calibration curves for nitrous oxide were prepared as 
following procedure. Standard gas was introduced into the system (and 
concentrated on cold trap) in the usual gas analysis sequence and 
immediately the N2 gas flow path was switched to the sea water line 
containing the blank seawater. This method can analyze the standard gas 
under almost same condition as the seawater analysis. In order to take a 
priority in the accuracy of CFCs and SF6, this procedure was not applied 
to the frequent standard gas analysis for sensitivity correction during 
sea water sample analysis. So accurate sensitivity correction would be 
difficult for N2O analyses. A peak area of N2O always became unusually 
small at the first seawater analysis after the standard gas analysis by 
the usual gas analysis sequence. This also seems to be the same cause 
that could be a lack of moisture. In this case, N2O measurement was not 
reported (flag "5" was given) because the correction methods for such 
measurement has not been found at the present time.


5  Data archive

    All data will be submitted to Data Management Group (DMG) of JAMSTEC.


5  Floats, Drifters and Moorings


5.1  Argo floats


(1) Personnel

    Shuhei Masuda    (JAMSTEC/RCGC): Principal Investigator (not on board) 
    Shigeki Hosoda   (JAMSTEC/ RCGC): not on board
    Kanako Sato      (JAMSTEC/ RCGC): not on board
    Mizue Hirano     (JAMSTEC/ RCGC): not on board
    Shingo Oshitani  (MWJ): Technical Staff (Operation Leader)


(2) Objectives

    The purpose of this study is to clarify the mechanisms of climate and 
oceanic environment variability for understanding changes of earth system 
through estimations of heat and material transports, by sustainably 
monitoring in the global ocean. To get knowledge of those changes in the 
ocean, it is crucial to obtain well-quality controlled observational 
data.

    As the Southern Ocean is one of the area where the number of active 
Argo float is unsatisfied to the target spatial density, which had been 
defined by the International Argo program, oceanic change is not well-
understood although the Southern Ocean is one of the key region for 
climate changes. Especially physical process of the oceanic change below 
2000m depth and biogeochemical process associated with global carbon 
cycle etc. are not yet recognized because of less amount of long-term 
ocean observations. To obtain physical and biogeochemical data in the 
Southern Ocean, we launched three Argo floats for measurements of 
temperature and salinity above 2000m depth, one deep Argo (Deep NINJA) 
for measurements temperature and salinity above 4000m depth and one 
deep/biogeochemical Argo (DO-Deep APEX) for measurements temperature, 
salinity and dissolved oxygen above 6000m depth at station points where 
shipboard CTD cast was conducted.

    The continuously obtaining data form those floats will be opened as 
contribution of the Argo program, after conducting real-time quality 
control within 24 hours by Argo data assembly center and delayed mode 
quality controls within one year by JAMSTEC as Argo PI. Based on the Argo 
and deep/biogeochemical Argo data, we will investigate spatial and 
temporal variability of water mass such as Antarctic Intermediate Water 
and amount of carbon uptake and transport, adapting those data to data 
assimilation systems such as JAMSTEC’s 4D-VAR data synthesis system 
(ESTOC). Further, we will evaluate accuracy of CTD and DO sensors mounted 
on the floats in comparison with the high accuracy shipboard CTD data at 
the station points, which makes Argo and deep/biogeochemical Argo data 
quality improve and then largely contributes to the International Argo 
program.


(3) Parameters

    Water temperature, salinity, pressure, and dissolved oxygen


(4) Methods

i. Profiling float deployment of Argo
  
    We launched one Navis float with SBE41 CTD sensor and two Arvor 
floats with SBE41 CTD sensor. The floats usually drift at a depth of 1000 
dbar (parking depth), then dive to a depth of 2000 dbar (profiling depth) 
and rise up to the sea surface by changing its buoyancy every ten days. 
The floats measure temperature, salinity, and pressure when they rise to 
the sea surface. During staying at the sea surface within a few ten 
minutes ~ several hours, observed data are transmitted to the base 
station via telecommunication satellites in real-time. The specifications 
of floats and launching points are shown in Table 5.1.1.


Table 5.1.1: Specification of Navis/Arvor floats and launching point

  Float Type             Navis EBR                      Arvor
(manufacturer)  (Sea-Bird Electronics Inc.)     (nke instrumentation)

CTD sensor       SBE41 (Sea-Bird Electro-    SBE41 (Sea-Bird Electro
                        nics Inc.)	                  nics Inc.)

Cycle                    10 days                     10 days

Iridium         Router-Based Unrestricted          Argos system
transmit        Digital Internetworking
type             Connectivity Solutions 
                        (RUDICS)	

Target                 2000 dbar                    2000 dbar
Profiling 
Pressure	

Target                 1000 dbar                    1000 dbar
Parking 
Pressure	

Sampling                2 dbar                      5~20 dbar 
interval       (approximately 1000 levels)  (approximately 115 levels)

Mission control       Available                   Not available
after launching	


                             Launching point

   Float S/N       WMOID    Date and Time       Location      CTD St. 
                            of Launch(UTC)      of Launch       No.
————————————————  ———————  ———————————————  ————————————————  ———————
F0415             5905051  2017/2/20 22:52   58° 0.828' [S]   P17E16
(NAVIS)                                     125° 59.688' [W]
        
OIN 13JAP-ARL-78  7900692  2017/2/19 14:47   60° 57.888' [S]  P17E10
(Arvor)                                     125° 59.772' [W]

OIN 13JAP-ARL-79  5905052  2017/2/21 21:24   55° 30.69[S]
(Arvor)                                     125° 57.09[W]     P17E21


ii. Profiling float deployment for biogeochemical/deep Argo

    We also launched one deep/biogeochemical Argo float (DO-Deep APEX) 
and one deep Argo float (Deep NINJA). The Deep NINJA equipped with SBE41 
for deep CTD sensor, and the DO-Deep APEX equipped with SBE61 CTD sensor 
and Optode4831 dissolved oxygen sensor. The floats measure using above 
sensors when they go up to the sea surface. During staying at the sea 
surface within a few ten minutes, observed data are transmitted as the 
same style as for the Argo floats shown in (4) i. Specifications and 
their launching points are shown in Table 5.1.2.


Table 5.1.2: Specification of Deep NINJA/DO-Deep APEX and launching point

   Float Type           Deep NINJA                    Deep APEX
(manufacturer)    (Tsurumi Seiki Co.,Ltd)     (Teleedyne Webb Research)

  CTD sensor          SBE41 for Deep                    SBE61
                (Sea-Bird Electronics Inc.)  (Sea-Bird Electronics Inc.)

  Dissolved                 N/A                      Optode4831
Oxygen Sensor                                (Aanderaa Data Instruments)

   Cycle                  5 days                       5 days

   Iridium       Short Burst Data Service   Router-Based Unrestricted Digital
transmit type              (SBD)              Internetworking Connectivity 
                                                  Solutions (RUDICS)

Target Parking           2000 dbar                   2000 dbar
   Pressure

Target Profil-           4000 dbar                   6000 dbar
ing Pressure

Sampling                 5 dbar                      5 dbar
interval        (approximately 800 levels)   (approximately 1200 levels)
 
Mission control         Available                   Available
after launching

Ice detection           Included                    Included




Launching point

Float  WMO ID    Date and Time      Location of     CTD St. No.
 S/N             of Launch(UTC)       Launch
—————  ———————  ————————————————  ————————————————  ———————————
 20    7900691  2017/02/19 14:41   60° 58.008' [S]  P17E-10
                                  125° 59.982' [W]

 45    Not yet  2017/02/19 14:34   60° 58.140 [S]   P17E-10
       obtained                   126° 0.258' [W]



(5) Data archive

    With regard to NAVIS, Arvor and Deep NINJA, observed data are 
delivered to  meteorological organizations, research institutes, and 
universities etc. via Global Data Assembly Center (GDAC: 
http://www.usgodae.org/argo/argo.html, http://www.coriolis.eu.org/) 
andGlobal Telecommunication System (GTS). Real-time and delayed mode 
quality controls are conducted within 24 hours and one year after 
receiving the data, respectively. Both data are provided from GDACs 
following procedure decided by the International Argo program. With 
regard to SBE61 on DO-Deep APEX, the data will not delivered via GDACs 
for a while because quality control method is not yet fixed in the Argo 
Data Management Team. Instead, we will provide the data from Argo JAMSTEC 
HP conducting quality checks.

Fig. 5.1.1: First profiles of vertical temperature and salinity 
            distribution from NAVIS (WMOID: 5905051), Arvor (WMOID: 
            7900692 and 5905052) and Deep NINJA (WMOID: 7900691 but only 
            above 2000m depth).



5.2  SOCCOM biogeochemical floats

(1) Personnel
      
    K. Katsumata (JAMSTEC), S. Riser, D. Swift (University of 
Washington), K. Johnson (Monterey Bay Aquarium Research Institute), E. 
Boss (U. Maine), L. Talley (Scripps Institution of Oceanography)


(2) Objectives
 
    SOCCOM (Southern Ocean Carbon and Climate Observations and 
Modeling) is a project funded by NSF, NOAA, and NASA aiming at 
understanding the roles of Southern Ocean in climate change and 
biogeochemistry of the Earth system. Their main observational tool is a 
newly developed float with biogeochemical measurements. The project 
envisages deploying approximately 200 such floats within the Southern 
Ocean from 2014 to 2020. As a JAMSTEC contribution towards the project, 
we have deployed five floats during the P17E reoccupation. It is 
essential that the float deployment be accompanied with high-quality 
bottle data for calibrating the float sensors. GO-SHIP cruises, which 
strive for state-of-the-art accuracy and precision in CTD and chemistry 
analyses are a good platform for this purpose. In this section, we 
describe the float deployments. The accompanying bottle sampling is 
described in Section 4.26 of this report.


(4) SOCCOM BGC float

    In addition to the usual temperature and salinity measurements, a 
SOCCOM biogeochemical Argo-type float carries sensors to measure acidity 
(pH), nutrient (nitrate), and oxygen. The APEX floats that were deployed 
in this cruise also carried a bio-optic sensor to measure ocean 
fluorescence and backscatter. Further references for the float 
specifications are available at SOCCOM (2017).


(5) Deployments

    Five floats were deployed at five different CTD stations right 
after the CTD cast. After cleaning the FLBB and ISUS sensors with pre-
moistened lens cleaning wipe and deionized water following Riser et al. 
(2017), the floats were deployed from the stern deck of R/V Mirai with a 
rope. The details of deployments are shown below. The year is 2017.

Stn   Latitude    Longitude   Depth     Time (UT)   Float Serial Num.
———  ——————————  ———————————  ——————  ————————————  —————————————————
 2   66-21.55°S  126- 1.47°W  4445 m  16 Feb 17:33       12371
 4   65-1.00°S   125-56.51°W  4872 m  17 Feb 07:42       12379
 8   62-20.59°S  126- 6.90°W  5055 m  19 Feb 00:43       12366
18   57-1.60°S   126- 0.12°W  4115 m  21 Feb 07:26       12386
24   54-0.00°S   125-58.42°W  3543 m  22 Feb 13:01       12542


References

Riser, S., R. Rupan, D. Swift, K. Johnson, C. Sakamoto, L. Talley, 2017, 
    SOCCOM BGC Floats: Deployment and Cleaning Procedures, version 8 
    January 2017, available online at 
    https://soccom.princeton.edu/content/manuals
    SOCCOM, 2017, https://soccom.princeton.edu/content/float-
    specifications



5.3  CO2 buoys


(1) Personnel

    Akihiko Murata (JAMSTEC) 
    Kosei Sasaoka (JAMSTEC) 
    Tomonori Watai (MWJ) 
    Atsushi Ono (MWJ)
    Emi Deguchi (MWJ) 
    Nagisa Fujiki (MWJ)


(2) Objective
 
    It is said that the ocean takes up approx. 30% of CO2 emitted into 
the atmosphere by human   activities such as fossil fuel burning, 
deforestation, cement production, etc. Thus, accurate estimation of CO2 
uptake by the ocean is an important task in predicting global warming and 
related climate changes, because the ocean tends to moderate the warming 
by absorbing anthropogenic CO2 from the atmosphere. Calculation of air-
sea fluxes of CO2 is one of straightforward methods to estimate the CO2 
uptake. Data for surface seawater partial pressure of CO2 (pCO2) are 
necessary for the calculation. Surface seawater pCO2 data covering the 
world ocean have been collected by such an international activity as 
Surface Ocean Carbon Dioxide Atlas (SOCAT). However, in spite of the 
long-term effort over 40 years, a large data gap is still found in the 
Southern Hemisphere oceans, especially in the South Pacific. This is 
because the ocean is far away from pCO2 observations-leading countries, 
i.e., difficult to do observations by research vessels due to high cost, 
and because there scarcely exist regular lines of cargo ships, along  
which pCO2 observations have been conducted. Drifting buoys with pCO2 
sensor are free from the limitation. Therefore, we intend to deploy 
drifting buoys in the South Pacific during the MR16-09 cruise.


(3) Apparatus

    The drifting pCO2 buoy was constructed by NiGK Corporation. The 
specification of drifting CO2 buoy is as Table 5.3.1.
    

Table 5.3.1: Specification of drifting CO2 buoy.

             Items                    Specification
        ———————————————  ———————————————————————————————————————
             Size        Diameter: 315 mm (max.), Height: 575 mm
            Weight                       8.6 kg
        Pressure proof                    5 m
         Positioning                      GPS
           Battery                Primary lithium battery
          CO2 range                   150 111000 ppm
        CO2 resolution                  < 1 ppm
          Accuracy                      < 1.5%


(5) Results
        
    We injected 7 drifting CO2 buoys into the South Pacific, where a 
large data gap exists. We injected them during the cruise of R/V Mirai 
(legs 1 and 3 of MR16-09) (Figs. 5.3.1 and 5.3.2), and started data 
acquisition through a satellite communication system. In addition, we 
introduced a server in order to stock, control and analyze data from 
drifting CO2 buoys.


Fig. 5.3.1: Positions (circles) of drifting CO2 buoys injected during the 
            R/V Mirai cruise and the

Fig. 5.3.2: Drifting CO2 buoys on the deck of the R/V Mirai (left), and 
            appearance of injection in the MR16-09 cruise (right).













DATA HISTORY


•  File Merge Carolina Berys
Cruise_Report_MR16-09_20170725.pdf (download) #64290
Date: 2018-04-25
Current Status: merged

•  File Merge Jerry Kappa
49NZ20170208_do.pdf (download) #38917
Date: 2018-04-25
Current Status: dataset

•  File Submission Jerry Kappa
49NZ20170208_do.pdf (download) #38917
Date: 2018-04-25
Current Status: dataset
Notes
The pdf version of the P17E_2017 cruise report is merged.  It contains all 
the PI-provided data reports, CCHDO summary pages and CCHDO data processing 
notes.


•  File Merge CCHSIO
49NZ20170208_ct1.zip (download) #4454c
Date: 2018-02-15
Current Status: merged

•  Update CTD exchange and netcdf files CCHSIO 
Date: 2018-02-15
Data Type: CTD
Action: Website Update
Note: 
    2017 49NZ20170208 processing - CTD/merge - 
CTDPRS,CTDTMP,CTDSAL,CTDSVLSAL,CTDOXY,CTDFLUOR,CTDXMISS,CTDXMISSCP,CTDTURB,
CTDPAR,CTDCDOMF

2018-02-15

CCHSIO


Submission

filename             submitted for         date       id  
-------------------- -------------         ---------- -----
49NZ20170208_ct1.zip K.Katsumata           2017-04-04 12688

Changes
-------

49NZ20170208_ct1.zip
        -  added units comments
        -  added cruise information as commented header
        -  changed file name to match CCHDO format
        -  SECT_ID: changed header SECT to SECT_ID
        -  XMISSCP: XMISSCP_FLAG_W not submitted, CCHDO copied XMISS_FLAG_W 
           to XMISSCP_FLAG_W
        -  CTDCDOMF: Changed parameter name from CDOM to CTDCDOMF
        -  CTDCDOMF_FLAG_W: Changed parameter name from CDOM_FLAG_W to 
           CTDCDOMF_FLAG_W
        -  CTDFLUOR: Changed parameter name from FLUOR to CTDFLUOR
        -  CTDFLUOR_FLAG_W: Changed parameter name from FLUOR_FLAG_W to 
           CTDFLUOR_FLAG_W
        -  CTDPAR: Changed parameter name from PAR to CTDPAR
        -  CTDPAR_FLAG_W: Changed parameter name from PAR_FLAG_W to 
           CTDPAR_FLAG_W
        -  CTDSVLSAL: Changed parameter name from SVLSAL to CTDSVLSAL
        -  CTDSVLSAL_FLAG_W: Changed parameter name from SVLSAL_FLAG_W to 
           CTDSVLSAL_FLAG_W
        -  CTDTURB: Changed parameter name from TURB to CTDTURB
        -  CTDTURB_FLAG_W: Changed parameter name from TURB_FLAG_W to 
           CTDTURB_FLAG_W
        -  CTDXMISS: Changed parameter name from XMISS to CTDXMISS
        -  CTDXMISSCP: Changed parameter name from XMISSCP to CTDXMISSCP
        -  CTDXMISS_FLAG_W: Changed parameter name from XMISS_FLAG_W to 
           CTDXMISS_FLAG_W
        -  CTDCDOMF: Changed units from MG/CUM to MG/M^3
        -  CTDFLUOR: Changed units from MG/CUM to MG/M^3
        -  CTDXMISSCP_FLAG_W not submitted, copied CTDXMISS_FLAG_W to 
           CTDXMISSCP_FLAG_W
        -  CTDTURB, CTDCDOMF, CTDXMISSCP, and SVLSAL are not defined in 
           Exchange format. 
        -  PAR unit UE/SQM/S is not a defined unit for PAR in Exchange 
           format
        -  CTDSVLSAL_FLAG_W: changed all flags from 1 to 9 because all 
           CTDSVLSAL values are -999


Conversion
----------

file                    converted from       software               
----------------------- -------------------- -----------------------
49NZ20170208_nc_ctd.zip 49NZ20170208_ct1.zip hydro 0.8.2-48-g594e1cb


Updated Files Manifest
----------------------

file                    stamp            
----------------------- --------------
49NZ20170208_ct1.zip    20180215CCHSIO
49NZ20170208_nc_ctd.zip 20180215CCHSIO

:Updated parameters: 
CTDPRS,CTDTMP,CTDSAL,CTDSVLSAL,CTDOXY,CTDFLUOR,CTDXMISS,CTDXMISSCP,CTDTURB,
CTDPAR,CTDCDOMF

opened in JOA with no apparent problems for the netcdf file 
49NZ20170208_nc_ctd.zip.
JOA did not properly display the full depth for the file 
49NZ20170208_ct1.zip, probably becuase CTDPRS_FLAG_W is present.

opened in ODV with no apparent problems:
     49NZ20170208_ct1.zip


					
•  File Online Carolina Berys
AL5400_POC_P17E.xlsx (download) #fbde0
Date: 2017-11-01
Current Status: unprocessed

•  File Online Carolina Berys
Boss 06-22 report.xlsx (download) #a95fc
Date: 2017-11-01
Current Status: unprocessed

•  File Online Carolina Berys
MR16-09Leg3_recal_post_pco2_cal_v511.csv (download) #a775b
Date: 2017-11-01
Current Status: unprocessed

•  File Online Carolina Berys
mr2016_20160120.map.jpg (download) #e4fd9
Date: 2017-11-01
Current Status: unprocessed

•  File Online Carolina Berys
sfcmet.zip (download) #8fff5
Date: 2017-11-01
Current Status: unprocessed

•  File Submission Carolina for Robert Key
sfcmet.zip (download) #8fff5
Date: 2017-11-01
Current Status: unprocessed
Notes
Downloaded 2017-10-25 from 
http://www.jamstec.go.jp/iorgc/ocorp/data/p17erev_2017/index.html


•  File Submission Carolina for Robert Key
mr2016_20160120.map.jpg (download) #e4fd9
Date: 2017-11-01
Current Status: unprocessed
Notes
Downloaded 2017-10-25 from 
http://www.jamstec.go.jp/iorgc/ocorp/data/p17erev_2017/index.html


•  File Submission Carolina for Robert Key
MR16-09Leg3_recal_post_pco2_cal_v511.csv (download) #a775b
Date: 2017-11-01
Current Status: unprocessed
Notes
Downloaded 2017-10-25 from 
http://www.jamstec.go.jp/iorgc/ocorp/data/p17erev_2017/index.html


•  File Submission Carolina for Robert Key
Boss 06-22 report.xlsx (download) #a95fc
Date: 2017-11-01
Current Status: unprocessed
Notes
Downloaded 2017-10-25 from 
http://www.jamstec.go.jp/iorgc/ocorp/data/p17erev_2017/index.html


•  File Submission Carolina for Robert Key
AL5400_POC_P17E.xlsx (download) #fbde0
Date: 2017-11-01
Current Status: unprocessed
Notes
Downloaded 2017-10-25 from 
http://www.jamstec.go.jp/iorgc/ocorp/data/p17erev_2017/index.html


•  File Online Carolina Berys
Cruise_Report_MR16-09_20170725.pdf (download) #64290
Date: 2017-11-01
Current Status: merged

•  File Submission Robert Key
Cruise_Report_MR16-09_20170725.pdf (download) #64290
Date: 2017-10-25
Current Status: merged
Notes
Cruise Report here. Other files sent here and to Alex at NCEI via e-mail. 
See details in that message


•  File Online Carolina Berys
49NZ20170208_ct1.zip (download) #4454c
Date: 2017-04-12
Current Status: merged

•  File Online Carolina Berys
49NZ20170208_sum.txt (download) #bbf13
Date: 2017-04-12
Current Status: unprocessed

•  File Submission see
49NZ20170208_sum.txt (download) #bbf13
Date: 2017-04-04
Current Status: unprocessed
Notes
Submitted for Katsuro Katsumata at JAMSTEC
Final SUM and CTD files

Dates: Feb 8 - Mar 5 2017
SHIP:  Marai
ChSci:  Hiroshi Uchida
Lines:  P17E, P17S
Collections:  Pacific, SOCCOM, Southern?
aliases MR16-09
Expocode 49NZ20170208


•  File Submission see
49NZ20170208_ct1.zip (download) #4454c
Date: 2017-04-04
Current Status: merged
Notes
Submitted for Katsuro Katsumata at JAMSTEC
Final SUM and CTD files

Dates: Feb 8 - Mar 5 2017
SHIP:  Marai
ChSci:  Hiroshi Uchida
Lines:  P17E, P17S
Collections:  Pacific, SOCCOM, Southern?
aliases MR16-09
Expocode 49NZ20170208