CRUISE REPORT: I10 
(Updated SEP 2017) 






Highlights 








                           Cruise Summary Information

               Section Designation  I10 (AKA: MR15-05)  
Expedition designation (ExpoCodes)  49NZ20151223  
                  Chief Scientists  Katsuro Katsumata/JAMSTEC  
                             Dates  23 DEC 2015 - 11 JAN 2016  
                              Ship  R/V Marai  
                     Ports of call  Jakarta, Indonesia – Bali, Indonesia  

                                                    8° 14.84' S 
             Geographic Boundaries  105° 31.45' E                 115° 14.93' E 
                                                    24° 26.84 S  

                          Stations  53  
      Floats and drifters deployed  16 Argo floats  
    Moorings deployed or recovered  0  

                              Contact Information:

        Katsuro Katsumata, Phd • Senior Scientist • Ocean Climate Change
   Research Program Research and Development Centre for Global Change (RIGC)
         Japan Agency for Marine-Earth Science and Technology (JAMSTEC)
              2-15 Natsushima, Yokosuka, Kanagawa, Japan 237-0061
            Fax: +81-46-867-9835 • email: k.katsumata@jamstec.go.jp






















                            R/V Mirai Cruise Report

                                    MR15-05
























                    WOCE-revisit in the eastern Indian Ocean



                     23rd December 2015 – 25th January 2016



              Japan Agency for Marine-Earth Science and Technology

                                   (JAMSTEC)







                                    Content

                                I. Introduction

                                II. Observation


1. Cruise Information 

2. Underway Measurements 
   2.1 Navigation 
   2.2 Swath Bathymetry 
   2.3 Surface Meteorological Observation 
   2.4 Thermo-Salinograph and Related Measurements 
   2.5 Surface pCO2 
   2.6 Ceilometer 
   2.7 Surface CO2fluxes 
   2.8 Radars and Disdrometers 
   2.9 Aerosol optical characteristics measured by Ship-borne Sky radiometer 
   2.10 Aerosol and gases 
   2.11 Sea surface gravity 
   2.12 Sea Surface Magnetic Field 
   2.13 Satellite image acquisition 

3. Station Observation 
   3.1 CTDO2Measurements 
   3.2 Bottle Salinity 
   3.3 Density 
   3.4 Oxygen 
   3.5 Nutrients 
   3.6 Chlorofluorocarbons and Sulfurhexafluoride 
   3.7 Carbon items 
   3.8 Calcium and Total alkalinity 2 
   3.9 Dissolved organic carbon and total dissolved nitrogen 
   3.10 Chlorophyll-a 
   3.11 Absorption coefficients of particulate matter and colored dissolved 
        organic matter (CDOM) 
   3.12 Bio-sampling 
   3.13 Carbon isotopes 3.14 Radioactive Cesium 
   3.15 Stable Isotopes of Water 
   3.16 Primary productivity 
   3.17 Lowered Acoustic Doppler Current Profiler 
   3.18 XCTD 
   3.19 Micro Rider 
   
4. Floats, Drifters and Moorings 
   4.1 Argo floats 


                              III. Notice on Using




I. Introduction 

Indonesian Throughflow is a surface component of the global ocean circulation, 
which transports fresh Pacific upper water masses into the north Indian Ocean 
with strong modification from the air-sea interaction and tidal mixing. Paucity 
of observation data in this part of the world ocean has always been a 
restriction in understanding global climate change and air-sea coupling — a 
problem shared amongst emerging international programmes such as Eastern Indian 
Ocean Upwelling Research Initiative. The main purpose of this cruise is to 
measure the distribution of water properties (temperature, salinity, dissolved 
oxygen, carbon, nutrients, etc.) in this important ocean. This is a contribution 
to International Indian Ocean Expedition 2 and conducted under the Global Ocean 
Ship-based Hydrographic Investigation Programme (GO-SHIP http://www.go-
ship.org). 







































 
II. Observation 


1. Cruise Information 
     Katsuro Katsumata (JAMSTEC) 
     Akihiko Murata (JAMSTEC) 

1.1. Basic Information 

Title of the cruise       Research cruise on ocean decadal variability --Indian 
                          Ocean GO-SHIP (Global Ocean Ship-based Hydrographic 
                          Investigation Program)

Cruise track:             See Fig. 1.1.1 

Research area             The northeastern Indian Ocean and the western Pacific 
                          Ocean

Cruise code:              MR15-05

Expocode                  Leg 1: 49NZ20151223 
                          Leg 2: 49NZ20160113 

GHPO section designation: I10 

Ship name:                R/V Mirai 

Ports of call:            Leg 1, Jakarta, Indonesia – Bali, Indonesia 
                          Leg 2, Bali, Indonesia – Yokohama, Japan 

Cruise date:              Leg 1, 23 December 2015 – 11 January 2016
                          Leg 2, 13 January 2016 – 25 January 2016

Chief scientists:         Leg 1, Katsuro Katsumata (k.katsumata@jamstec.go.jp)
                          Leg 2, Akihiko Murata (murataa@jamstec.go.jp) 

                          Ocean Climate Change Research Program 
                          Research and Development Centre for Global Change 
(RIGC) 
                          Japan Agency for Marine-Earth Science and Technology 
(JAMSTEC) 
                          2-15 Natsushima, Yokosuka, Kanagawa, Japan 237-0061 
                          Fax: +81-46-867-9835 


Piggyback projects 

     (1) Aerosol optical characteristics measured by ship-borne Sky radiometer 
         (ToyamaUniversity) 

     (2) Geochemical and microbiological investigation from sea surface to sea 
         bottom at tropical eutrophic ocean (JAMSTEC, University of Tokyo, Tokyo 
         University of Agriculture and Technology, Rakuno Gakuen University, 
         etc.) 

     (3) Advanced measurements of aerosols in the marine atmosphere: Toward 
         elucidation of interactions with climate and ecosystem (JAMSTEC) 

     (4) Global distribution of drop size distribution of precipitating 
         particles over pure-oceanic background (JAMSTEC) 

     (5) Shipboard CO2 observations over the tropical Indo-Pacific Ocean for a 
         simple estimation of the carbon flux between the ocean and the 
         atmosphere from GOSAT data (JAXA) 


Principal investigators of the piggyback projects: Kazuma Aoki (University of 
Toyama)
                                                   Takuro Nunoura (JAMSTEC) 
                                                   Yugo Kanaya (JAMSTEC) 
                                                   Masaki Katsumata (JAMSTEC) 
                                                   Kei Shiomi (JAXA) 

Number of Stations:           Leg 1, 53 stations 
                              Leg 2, none 

Floats and drifters deployed: 16 Argo floats (Leg 1), 1 Argo float (Leg 2) 

Mooring recovery: none 


Fig. 1.1.1: MR15-05 cruise. Blue circles show the deployment position of Argo 
            floats. Red dots show CTD/bottle sampling stations.

Fig. 1.1.2: Water sampling positions.


1.2. Cruise Participants 

List of Participants for leg 1 

Katsuro Katsumata    Chief scientist                              RCGC/JAMSTEC 
Yuichiro Kumamoto    DO/Sampling chief                            RCGC/JAMSTEC 
Hiroshi Uchida       Thermosalinograph/Salinity                   RCGC/JAMSTEC 
Ken’ichi Sasaki      CFCs                                         MIO/JAMSTEC 
Kosei Sasaoka        Chlorophyll                                  RCGC/JAMSTEC 
Etsuro Ono           Calcium/total alkalinity                     RCGC/JAMSTEC 
Kazuhiko Matsumoto   Primary productivity                         DEGCR/JAMSTEC 
Taichi Yokokawa      Biological sampling                          RDCMB/JAMSTEC 
Chisato Yoshikawa    Biological sampling                          DB/JAMSTEC 
Shotoku Kotajima     Biological sampling                          TUAC 
Kanta Chida          Biological sampling                          Rakuno Gakuen 
                                                                  University 
Harun Idham Akbar    Water sampling                               BPPT 
Gentio Harusono      Security Officer                             Indonesian 
Navy 
Hiroshi Matsumaga    Chief technician/Sampling chief              MWJ 
Shinsuke Toyoda      CTD                                          MWJ 
Hiroki Ushiromura    Salinity                                     MWJ 
Syungo Oshitani      CTD                                          MWJ 
Sonoka Wakatsuki     Salinity                                     MWJ 
Keisuke Takeda       CTD                                          MWJ 
Minoru Kamata        Nutrients                                    MWJ 
Tomonori Watai       pH/total alkalinity                          MWJ 
Makoto Takada        DIC                                          MWJ 
Elena Hayashi        Nutrients                                    MWJ 
Atsushi Ono          DIC                                          MWJ 
Tomomi Sone          Nutrients                                    MWJ 
Katsunori Sagishima  CFCs                                         MWJ 
Hironori Sato        CFCs                                         MWJ 
Misato Kuwahara      DO                                           MWJ 
Masahiro Orui        DO                                           MWJ 
Keitaro Matsumoto    DO                                           MWJ 
Hiroshi Hoshino      CFCs                                         MWJ 
Haruka Tamada        DO                                           MWJ 
Hiroyuki Hayashi     CTD                                          MWJ 
Kanako Yoshida       pH/total alkalinity                          MWJ 
Kohei Miura          Nutrients                                    MWJ 
Seika Katayama       Water sampling                               MWJ 
Naoya Yokoi          Water sampling                               MWJ 
Kohei Kumagai        Water sampling                               MWJ 
Naoya Kudo           Water sampling                               MWJ 
Eri Yoshizawa        Water sampling                               MWJ 
Kei Takamiya         Water sampling                               MWJ 
Wataru Tokunaga      Chief technician/meterology/geophysics/XCTD  GODI 
Yutaro Murakami      Meteorlology/geophysics/XCTD                 GODI 
Tetsuya Kai          Meteorology/geophysics/XCTD                  GODI 
	
List of Participants for leg 2 
Akihiko Murata       Chief scientist                              RCGC/JAMSTEC  
Kousei Sasaoka       Engineer                                     RCGC/JAMSTEC  
Minoru Kamata        Chief marine technician                      MWJ  
Sinsuke Toyota       Marine technician                            MWJ  
Tomonori Watai       Marin technician                             MWJ  
Syungo Oshitani      Marine technician                            MWJ  
Sonoka Wakatsuki     Marine technician                            MWJ  
Tomonori Watai       Marine technician                            MWJ  
Makoto Takada        Marine technician                            MWJ  
Elena Hayashi        Maine technician                             MWJ  
Atsushi Ono          Maine technician                             MWJ  
Katsunori Sagishima  Marine technician                            MWJ  
Masahiro Oorui       Marine technician                            MWJ  
Keitaro Matsumoto    Marine technician                            MWJ  
Koichi Inagaki       Chief technician/meteorology/geophysics      GODI  
Yutaro Murakami      Meteorology/geophysics                       GODI  

    BPPT: Badan Pengkajian dan Penerapan Teknologi (Agency for the Assessment 
          and Application of Technology of the Republic ofIndonesia) 
    DB: Department of Biogeochemistry 
    DEGCR: Department of Environmental Geochemical Cycle Research 
    GODI: Global Ocean Development Inc. 
    MWJ: Marine Works Japan 
    MIO: Mutsu Institute for Oceanography 
    RCGC: Research and Development Center for Global Change 
    RDCMB: Research and Development Center for Marine Biosciences 
    TUAT: Tokyo University of Agriculture and Technology 




2. Underway Measurements 


2.1 Navigation  

(1)  Personnel  
     Katsuro Katsumata  JAMSTEC: Principal investigator        -leg1 - 
     Akihiko Murata     JAMSTEC: Principal investigator        -leg2 - 
     Wataru Tokunaga    Global Ocean Development Inc., (GODI)  -leg1 - 
     Tetsuya Kai        GODI                                   -leg1 - 
     Koichi Inagaki     GODI                                   -leg2 - 
     Yutaro Murakami    GODI                                   -leg1, leg2 - 
     Ryo Kimura         MIRAI crew                             -leg1 - 
     Masanori Murakami  MIRAI crew                             -leg2 - 

(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 (version 1), Differential GNSS system. 
      Antenna: Located on compass deck, starboard. 
   b) StarPack-D (version 1), 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 TS-2540 Time Server, synchronizing to GPS satellites every 1 second. 


(3) Cruise period (Times in UTC) 
    Leg1: 03:10, 23 Dec. 2015 to 00:50, 11 Jan. 2016 
    Leg2: 01:00, 13 Jan. 2016 to 23:50, 24 Jan. 2016 


Fig.2.1-1: Cruise track of MR15-05Leg1, Leg2 



2.2  Swath Bathymetry  

(1)  Personnel  
     Katsuro Katsumata  JAMSTEC: Principal investigator        -leg1 - 
     Akihiko Murata     JAMSTEC: Principal investigator        -leg2 - 
     Wataru Tokunaga    Global Ocean Development Inc., (GODI)  -leg1 - 
     Tetsuya Kai        GODI                                   -leg1 - 
     Koichi Inagaki     GODI                                   -leg2 - 
     Yutaro Murakami    GODI                                   -leg1, leg2 - 
     Ryo Kimura         MIRAI crew                             -leg1 - 
     Masanori Murakami  MIRAI crew                             -leg2 - 
                           
(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. 

(3) Data Acquisition 

The “SEABEAM 3012” on R/V MIRAI was used for bathymetry mapping during this 
cruise. 

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 this cruise. 

Table 2.2-1 shows system configuration and performance of SEABEAM 3012. 


Table 2.2-1: 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) 


(4) Data processing 

    i)  Sound velocity correction 
           Each 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 were carried out using the HIPS software version 
        8.1.8 (CARIS, Canada) 

    ii) Editing and Gridding 
           Editing for the bathymetry data were carried out using the HIPS. 
        Firstly, the bathymetry data during ship’s turning was basically 
        deleted, and spike noise of each 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 2.2-2: 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 
        Bathymetric data obtained during this cruise will be submitted to the 
    Data Management Group (DMG) of JAMSTEC, and will be archived there. 


(6) Remarks (Times in UTC) 
    i)  The following periods, the observation were carried out. 
           Leg1: 19:35, 23 Dec. 2015 to 09:40, 24 Dec. 2015 
                 11:20, 24 Dec. 2015 to 22:05, 10 Jan. 2016 
           Leg2: 14:35, 17 Jan. 2016 to 06:26, 23 Jan. 2016 



2.3  Surface Meteorological Observations 

(1) Personnel 
    Katsuro Katsumata  JAMSTEC: Principal investigator          -leg1-
    Akihiko Murata     JAMSTEC: Principal investigator          -leg2-
    Wataru Tokunaga    Global Ocean Development Inc., (GODI)    -leg1-
    Tetsuya Kai        GODI                                     -leg1 -
    Koichi Inagaki     GODI                                     -leg2-
    Yutaro Murakami    GODI                                     -leg1, leg2-
    Ryo Kimura         MIRAI crew                               -leg1-
    Masanori Murakami  MIRAI crew                               -leg2-

(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 during this cruise, 
    except for the Republic of Indonesia territorial waters and Republic of 
    Philippine EEZ. In this cruise, we used two systems for the observation. 

    i)  MIRAI Surface Meteorological observation (SMet) system 
           Instruments of SMet system are listed in Table 2.3-1 and measured 
        parameters are listed in Table 2.3-2. 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) and UV (Ultraviolet 
           Irradiance) 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 2.3-3 and measured parameters are listed in Table 
        2.3-4. 

        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. 2.3-1 shows the time series of the following parameters; 
        Wind (SOAR) 
        Air temperature (SMet) 
        Relative humidity (SMet) 
        Precipitation (SOAR, rain gauge) 
        Short/long wave radiation (SMet and SOAR) 
              SMet: 18:51, 23 Dec. 2015 to 00:49, 28 Dec. 2015 
              SOAR: 00:50, 28 Dec. 2015 to end of cruise 
        Pressure (SMet) Sea surface 
        temperature (SMet) 
        Significant wave height (SMet) 

(5) Data archives 
        These meteorological data will be submitted to the Data Management Group 
    (DMG) of JAMSTEC just after the cruise. 

(6) Remarks (Times in UTC) 

    i)   The following periods, the observation were carried out. 
         Leg1: 18:51, 23 Dec. 2015 to 22:40, 10 Jan. 2016 
         Leg2: 13:35, 17 Jan. 2016 to 00:00, 25 Jan. 2016 
    ii)  The following periods, sea surface temperature of SMet data were 
         available. 
         Leg1: 18:51, 23 Dec. 2015 to 22:03, 10 Jan. 2016 
         Leg2: 13:35, 17 Jan. 2016 to 06:30, 23 Jan. 2016 
    iii) The following periods, PRP data were invalid due to system trouble.    
         18:51, 23 Dec. 2015 to 00:49, 28 Dec. 2015 
         16:42, 21 Jan. 2016 to 20:54, 21 Jan. 2016 
    iv)  The following periods, PRP data acquisition were suspended due to 
         maintenance. 
         07:27, 24 Jan. 2016 to 07:30, 24 Jan. 2016 
    v)   The following time, increasing of SMet capacitive rain gauge data were 
         invalid due to transmitting for MF/HF or VHF radio. 
         06:37, 06 Jan. 2016 
         23:57, 20 Jan. 2016 
         01:01, 21 Jan. 2016 
         20:31, 24 Jan. 2016 
         22:07, 24 Jan. 2016 


Table 2.3-1: 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 aspi-               R.M. Young, USA       Compass deck (21 m) 
rated radiation shield   
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 2.3-2: 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  sec./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 2.3-3 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                      R.M. Young, USA  Foremast (23 m) 
pressure port   
Capacitive rain gauge     50202      R.M. Young, USA  Foremast (24 m)  
Tair/RH                   HMP155     Vaisala, Finland  
with 43408 Gill aspi-                R.M. Young, USA  Foremast (23 m) 
rated radiation shield   
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             Yankee, USA      Foremast (25 m)  
  radiometer  

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

Table 2.3-4: 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 
16 UV305nm                                microW/ cm2/nm 
17 UV320nm                                microW/ cm2/nm 
18 UV340nm                                microW/ cm2/nm 
19 UV380nm                                microW/ cm2/nm 
 

Fig. 2.3-1: Time series of surface meteorological parameters during this cruise 
            (Leg1).



2.4  Thermo-Salinograph and Related Measurements 
       February 22, 2016 

(1) Personnel 
       Hiroshi Uchida (JAMSTEC) 
       Kosei Sasaoka (JAMSTEC) 
       Masahiro Orui (MWJ) 
       Misato Kuwahara (MWJ) 
       Keitaro Matsumoto (MWJ) 
       Haruka Tamada (MWJ) 

(2) Objectives 

The objective is to collect sea surface salinity, temperature, dissolved oxygen, 
fluorescence, turbidity, and nitrate 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 
2.4.1. 

A chemical-free nitrate sensor was also used with the Continuous Sea Surface 
Water Monitoring System. The nitrate sensor was attached using a flow cell next 
to the thermo-salinograph. 

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:          4552788-0264 
              Pre-cruise calibration: 30 August 2014, Sea-Bird Electronics, Inc. 
       Bottom of ship thermometer 
              Model:                  SBE 38, Sea-Bird Electronics, Inc. 
              Serial number:          3852788-0457 
              Pre-cruise calibration: 31 October 2014, Sea-Bird Electronics, Inc. 
       Dissolved oxygen sensor 
              Model:                  RINKO-II, JFE Adantech Co. Ltd. 
              Serial number:          0013 
              Pre-cruise calibration: 10 May 2015, JAMSTEC 
              Model:                  OPTODE 3835, Aanderaa Data Instruments, AS. 
              Serial number:          1519 
              Pre-cruise calibration: 13 May 2015, JAMSTEC 
       Fluorometer and turbidity sensor 
              Model:                  C3, Turner Designs, Inc. 
              Serial number:          2300384 
       Nitrate sensor 
              Model:                  Deep SUNA, Satlantic, LP. 
              Serial number:          0385 


Table 2.4.1. Events of the Continuous Sea Surface Water Monitoring System 
             operation. 

       System Date  System Time  Event  
          [UTC]        [UTC]  
       ———————————  ———————————  ——————————————————————————————————
       2015/12/23      19:00     Logging for leg 1 start  
       2015/12/24   05:23–06:07  Flow rate for a line of RINKO and 
                                 Optode would be small, though both 
                                 data seem to be normal.  
       2015/12/29      10:11     Logging stop for C3/filter cleaning  
       2015/12/29      11:23     Logging restart  
       2016/01/05      11:27     Logging stop for C3/filter cleaning  
       2016/01/05      13:05     Logging restart  
       2016/01/05   13:05–13:25  Optode was unstable.  
       2016/01/11      22:00     Logging for leg 1 end  
       2016/01/17      13:35     Logging for leg 2 start  
       2016/01/23      06:23     Logging for leg 2 end  
      

(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) = {1000xc(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 (µmol/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 = 5.048509438066593e-03 
                    C1 = 2.212851808960770e-04 
                    C2 = 3.735982971782336e-06 
                    C3 = -7.847113805097885e-04 
                    C4 = 3.011495646664952e-02 
                    C5 = 0.1926948014214438 
                    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. Data from the nitrate sensor were obtained at 2 minute 
intervals and linearly interpolated 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. Fluorometer 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, turbidity and 
nitrate data were low-pass filtered using a Hamming filter with a window of 15 
scans (15minutes). 

A slope correction was applied to the nitrate sensor before post-cruise 
calibration. RMNS (Reference Material for Nutrients in Seawater, Kanso Technos 
Co., Ltd., Osaka, Japan) lot BU and CA were measured by the nitrate sensor 
during the cruise (Fig. 2.4.1 and Table 2.4.2) and a slope (a1) for the 
correction was estimated to be 0.897966 on average from the following equation: 

                    NRA [µmol/kg] = a0 + a1 NRAorg 

where NRA is corrected nitrate concentration, NRAorg is raw data, and a0 is the 
offset at the time of RMNS measurement. 

Salinity (S [PSU]), dissolved oxygen (O [µmol/kg]), fluorescence (Fl [RFU]), and 
nitrate (NRA [µmol/kg]) data were corrected using the water sampled data. 
Details of the measurement methods are described in Sections 3.2, 3.4, 3.5, and 
3.10 for salinity, dissolved oxygen, nitrate and chlorophyll-a, respectively. 
Corrected salinity (Scor), dissolved oxygen (Ocor), estimated chlorophyll-a 
(Chl-a), and nitrate (NRAcor) were calculated from following equations 

                 Scor [PSU] = c0 + c1 S + c2 t 
                 Ocor [µmol/kg] = c0 + c1 O + c2 T + c3 t 
                 Chl-a [µg/L] = c0 + c1 Fl 
                 NRAcor [µmol/kg] = a1 NRAorg + c0 + c1 t 

where S is practical salinity, t is days from a reference time (2015/12/23 19:00 
[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 
2.4.2. Comparisons between the Continuous Sea Surface Water Monitoring System 
data and water sampled data are shown in Figs. 2.4.2, and 2.4.3. 

For fluorometer data, water sampled data obtained at night [PAR 
(Photosynthetically Available Radiation) < 50 µE/(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, 
slope (c1) of the calibration coefficients will be changed between legs 1 and 2. 

Post-cruise calibration of the nitrate sensor will be carried out after quality 
control of the water sampled nitrate data is finished. 


(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 2.4.2. Nitrate concentration measured by the nitrate sensor for RMNS lot 
             BU (3.888±0.063 [k=2] µmol/kg) and lot CA (19.66±0.15 [k = 2] 
             µmol/kg). Offset (a0) of the correction equation (see text for 
             detail) at the time of measurement was also shown. 

          Date                    RMNS lot BU  RMNS lot CA    a0 
          ——————————————————————  ———————————  ———————————  ——————
          2016/01/05 11:40-11:47  –17.71±0.58  –0.20±0.88   19.815 
          2016/01/05 12:02-12:09    8.70±0.16  26.46±0.17   –4.012 
          2016/01/10 00:06-00:11  –11.08±0.38   6.11±0.29   14.005 
          2016/01/17 05:51-05:58    9.65±0.18  27.84±0.20   –5.058 
          2016/01/23 06:54-07:01  –17.82±0.64  –0.61±0.45   20.049 
  

Table 2.4.3. Calibration coefficients for the salinity, dissolved oxygen, 
             chlorophyll-a, and nitrate. 

——————————————————————————————————————————————————————————————————————
                      c0           c1          c2              c3 
————————————————  ————————————  —————————  ————————————  —————————————
Salinity 
                  9.031385e-02  0.9976929  1.379279e-04 
Dissolved oxygen 
                  9.417670      0.9360383  0.0           -8.925093e-03 
Chlorophyll-a 

Nitrate 
——————————————————————————————————————————————————————————————————————


Figure 2.4.1. Results of RMNS measurements by the nitrate sensor. Differences 
              between measured value and certified value are shown. Error bar 
              shows the standard deviation of the measurements. 

Figure 2.4.2. Comparison between TSG salinity (red: before correction, green: 
              after correction) and sampled salinity. 


2.5. Surface pCO2 

(1) Personnel 
       Akihiko Murata (JAMSTEC) 
       Atsushi Ono (NIO) 
       Makoto Takada (MWJ) 
       Tomonori Watai (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 were aimed at quantifying how much anthropogenic CO2 absorbed 
in the surface ocean in the eastern part of the Indian Ocean and in the western 
North Pacific. For the purpose, we measured pCO2 (partial pressure of CO2) in 
the atmosphere and surface seawater along the observationline. 

(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 270, 330, 359 
and 419 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. 2.5.1, together with SST. 


Fig. 2.5.1: Preliminary results of concentrations of CO2 (xCO2) in atmosphere 
            (upper panel) and surface seawater (lower panel) observed during 
            MR15-05.



2.6  Ceilometer observation 

(1) Personnel 
       Katsuro Katsumata  JAMSTEC: Principal investigator       -leg1-
       Akihiko Murata     JAMSTEC: Principal investigator       -leg2-
       Wataru Tokunaga    Global Ocean Development Inc., (GODI) -leg1-
       Tetsuya Kai        GODI                                  -leg1-
       Koichi Inagaki     GODI                                  -leg2-
       Yutaro Murakami    GODI                                  -leg1, leg2-
       Ryo Kimura         MIRAI crew                            -leg1-
       Masanori Murakami  MIRAI crew                            -leg2-

(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 ConditionAlgorithm. 

(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 2.6-1; 


Table 2.6-1: 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, and 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.2.6-1 shows the time series of 1st, 2nd and 3rd lowest cloud base height 
during the cruise. 


Fig. 2.6-1: 1st, 2nd and 3rd lowest cloud base height during this cruise.


(6) Data archives 

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

(7) Remarks (Times in UTC) 
    i)  The following periods, the observation were carried out. 
        Leg1: 18:51, 23 Dec. 2015 to 22:40, 10 Jan. 2016 
        Leg2: 13:35, 17 Jan. 2016 to 23:50, 24 Jan. 2016 
    ii) The following time, the window was cleaned. 
        01:27, 27 Dec. 2015 
        01:10, 03 Jan. 2016 
        01:30, 21 Jan. 2016 


Fig. 2.6-1: 1st, 2nd and 3rd lowest cloud base height during this cruise (Leg1).
Fig. 2.6-1: Continued (Leg 2).



2.7  Surface CO2 fluxes 

Kei Shiomi (JAXA) 
Shuji KAWAKAMI (JAXA) 
Masakatsu NAKAJIMA (JAXA) 
Yoshiyuki NAKANO (JAMSTEC) 


(1) Objective 

Greenhouse gases Observing SATellite (GOSAT) was launched on 23 January 2009 in 
order to observe the global distributions of atmospheric greenhouse gas 
concentrations: column-averaged dry-air mole fractions of carbon dioxide (CO2) 
and methane (CH4). A network of ground-based high-resolution Fourier transform 
spectrometers provides essential validation data for GOSAT. Vertical CO2 
profiles obtained during ascents and descents of commercial airliners equipped 
with the in-situ CO2 measuring instrument are also used for the GOSAT 
validation. Because such validation data are obtained mainly over land, there 
are very few data available for the validation of the over-sea GOSAT products. 
The objectives of our research are to acquire the validation data over the 
Indian Ocean and the tropical Pacific Ocean using an automated compact 
instrument, to compare the acquired data with the over-sea GOSAT products, and 
to develop a simple estimation of the carbon flux between the ocean and the 
atmosphere from GOSAT data. 


Figure 1: Solar tracker and telescope. The sunlight collected into optical fiber 
          was introduced into the OSA that was installed in an observation room 
          in the MIRAI.


(2) Description of instruments deployed 

The column-averaged dry-air mole fractions of CO2 and CH4 can be estimated from 
absorption by atmospheric CO2 and CH4 that is observed in a solar spectrum. An 
optical spectrum analyzer (OSA, Yokogawa M&I co., AQ6370) was used for measuring 
the solar absorption spectra in the near-infrared spectral region. A solar 
tracker (PREDE co., ltd.) and a small telescope (Figure 1) collected the 
sunlight into the optical fiber that was connected to the OSA. The solar tracker 
searches the sun every one minute until the sunlight with a defined intensity. 
The measurements of the solar spectra were performed during solar zenith angles 
less than 80°. 


Figure 2. 1.6: μm CO2 absorption spectrum measured with the OSA.


(3) Analysis method 

The CO2 absorption spectrum at the 1.6 µm band measured with the OSA is shown in 
Figure 2. The absorption spectrum can be simulated based on radiative transfer 
theory using assumed atmospheric profiles of pressure, temperature, and trace 
gas concentrations. The column abundance of CO2 (CH4) was retrieved by adjusting 
the assumed CO2 (CH4) profile to minimize the differences between the measured 
and simulated spectra. 

Figure 3 shows an example of spectral fit performed for the spectral region with 
the CO2 absorption lines. The column-averaged dry-air mole fraction of CO2 (CH4) 
was obtained by taking the ratio of the CO2 (CH4) column to the dry-air column. 


Figure 3: Spectral fit performed for the 6297–6382 cm−1 region using an OSA 
          spectrum. Open diamonds denote the measured spectrum, and the solid 
          line denotes the spectrum calculated from the retrieval result. The 
          residual between the measured and calculated spectra is also shown.


(4) Preliminary results 

The observations were made from December 24, 2015 to January 24, 2016 
continuously in daytime (Table 1 and Figure 2). 
 
   
Table 1: Period of CO2 observations 

                            CO2 observations
                     ————————————————————————————————
                     Date        Start Time  End Time
                                   (JST)      (JST)
                     ——————————  ——————————  ————————
                     2015/12/24    09:14      19:34
                     2015/12/25    08:14      19:36
                     2015/12/26    08:14      19:44
                     2015/12/27    08:09      18:43
                     2015/12/28    07:44      19:31
                     2015/12/29    07:39      19:37
                     2015/12/30    07:55      19:49
                     2015/12/31    07:47      19:29
                     2016/01/01    07:50      19:45
                     2016/01/02    07:53      19:38
                     2016/01/03    07:56      18:11
                     2016/01/04    07:58      16:37
                     2016/01/05    08:00      19:03
                     2016/01/06    08:05      18:54
                     2016/01/07    08:04      19:15
                     2016/01/08    08:06      19:06
                     2016/01/09    08:08      19:10
                     2016/01/18    07:32      17:15
                     2016/01/19    07:38      13:16
                     2016/01/20    07:38      16:38
                     2016/01/21    07:38      16:38
                     2016/01/24    09:15      16:10


Figure 2: Locations of CO2 observations 


(5) Data archive 

The column-averaged dry-air mole fractions of CO2 and CH4 retrieved from the OSA 
spectra will be submitted to JAMSTEC Data Management Group (DMG). 



2.8. Radars and Disdrometers 

(1) Personnel 
       Masaki Katsumata (JAMSTEC) 
       Yuki Kaneko (JAXA) 
       Kazuhide Yamamoto (JAXA) (not on board) 


(2) Objectives 

Accurate measurement of the precipitating particle on its amount, phase and 
their spatiotemporal distributions is crucial to understand the climate system, 
thru evaluating the latent heating of the atmosphere, radiative heating of the 
atmosphere and ocean, fresh water flux into the ocean, etc. To better measure 
and understand the global precipitation, we deployed various instruments to 
measure the various characteristics of the precipitation on R/V Mirai which 
deployed globally. The objective of this observation is (a) to reveal various 
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) Apparatus 

(3-1) Disdrometers 

Four different types of disdrometers are utilized to obtain better reasonable 
and accurate value on the moving vessel. Three of the disdrometers and one 
optical rain gauge are installed in one place, the starboard side on the roof of 
the anti-rolling system of R/V Mirai, as in Fig. 2.8-1. One of the disdrometers 
named “micro rain radar” is installed at the starboard side of the anti-rolling 
systems (see Fig. 2.8-2). 

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


Fig. 2.8-1: The three disdrometers (Parsivel, LPM and Joss-Waldvogel 
            disdrometer) and an optical rain gauge, installed on the roof of the 
            anti-rolling tank. 


(3-1-1) Joss-Waldvogel type disdrometer 

The “Joss-Waldvogel-type” disdrometer system (RD-80, Disdromet Inc.) (hereafter 
JW) equipped a microphone on the top of the sensor unit. When a raindrop hit the 
microphone, the magnitude of induced sound is converted to the size of 
raindrops. The logging program “DISDRODATA” determines the size as one of the 20 
categories as in Table 2.8-1, and accumulates the number of raindrops at each 
category. The rainfall amount could be also retrieved from the obtained drop 
size distribution. The number of raindrops in each category, and converted 
rainfall amount, are recorded every one minute. 

(3-1-2) 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) × 228 mm (D) × 0.75 mm (H). 

The number of particles are categorized by the detected size and fall speed and 
counted every minute. The categories are shown in Table 2.8-2. 

(3-1-3) “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) × 180 mm (D). The categories are shown in Table 2.8-3. 

(3-1-4) Optical rain gauge 

The optical rain gauge, which detect scintillation of the laser by falling 
raindrops, is installed beside the above three disdrometers to measure the exact 
rainfall. The ORG-815DR (Optical Scientific Inc.) is utilized with the 
controlling and recording software (manufactured by Sankosha Co.). 


Table 2.8-1: Category number and corresponding size of the raindrop for JW 
             disdrometer. 

                 Category  Corresponding size range [mm]
                 ————————  —————————————————————————————  
                    1             0.313 - 0.405  
                    2             0.405 - 0.505  
                    3             0.505 - 0.696  
                    4             0.696 - 0.715  
                    5             0.715 - 0.827  
                    6             0.827 - 0.999  
                    7             0.999 - 1.232  
                    8             1.232 - 1.429  
                    9             1.429 - 1.582  
                   10             1.582 - 1.748  
                   11             1.748 - 2.077  
                   12             2.077 - 2.441  
                   13             2.441 - 2.727  
                   14             2.727 - 3.011  
                   15             3.011 - 3.385  
                   16             3.385 - 3.704  
                   17             3.704 - 4.127  
                   18             4.127 - 4.573  
                   19             4.573 - 5.145  
                   20             5.145 or larger  


Table 2.8-2: 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 2.8-3: Categories of the size and the fall speed for Parsivel. 

               Particle Size               Fall Speed
          ———————————————————————    ——————————————————————
          Class  Average   Class     Class  Average  Class     
                 Diameter  spread            Speed   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  

  
(3-2) Micro rain radar 

The MRR-2 (METEK GmbH) was utilized. The specifications are in Table 2.8-4. The 
antenna unit was installed at the starboard side of the anti-rolling systems 
(see Fig. 2.8-2), 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. 

Fig. 2.8-2: The micro rain radar, installed on the starboard side of the anti-
            rolling tank. 

Fig. 2.8-3: The Ka-band radar system. (left) Antenna part,  at the right-side of 
            the stern of the upper deck. (right) Signal processer part, in the 
            “dry labo.”


Table 2.8-4: 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  


(3-3) Ka-band radar 

The Ka-band radar (Manufactured by Mitsubishi Electric Co.) was utilized. The 
specifications are in Table 2.8-5. The antenna unit was installed at the stern 
(starboard side) of the vessel (see Fig. 2.8-x), and wired to the signal 
processing unit inside the vessel (so-called “dry labo”). Antenna direction is 
fixed to zenith relative to the ship. 


Table 2.8-5: Specifications of the Ka-band radar 

Frequency                 35.25 GHz (Ka-band)  
Modulation Principle      FMCW  
Minimum Detect Zm         -20 dBZ at 10 km  
Minimum Range Resolution  12.5 m  
Minimum Time Resolution   10 sec  
Niquist Velocity          ±10.6 m/s  
Observable range          From 500 m to 30 km (Depends on the observation mode)  
Antenna beam width        0.6 deg  
Antenna sidelobe          < 25 dBZ  
Radar Variables           Radar reflectivity and Doppler spectrum  


(3-3) C-band radar 

The C-band polarimetric weather radar in R/V Mirai was utilized. The basic 
specifications are in Table 2.4-4. 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 laser gyro. 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) mean output power, (3) pulse width, and (4) 
PRF (pulse repetition frequency). 

During the cruise, parameters in Table 2.x-x were obtained. Scan strategies are 
shown in Table 2.x-x. The radar is operated to repeat the cycle every 6 minutes 
basically, while every 30 minutes to obtain surveillance PPI. A dual PRF mode is 
used for a volume scan. For vertical pointing scan and surveillance PPI scans, a 
single PRF mode is used. 


Table 5.3-1: Scan settings of the C-band radar in the cruise. 

                                                                      Vertical 
                       Surveillance           Volume Scan              Point 
                         PPI Scan                                      Scan  
—————————————————————  ————————————  ———————————————————————————————  ————————
Repeated Cycle (min.)      30                     6                      6  
—————————————————————  ————————————  ———————————————————————————————  ————————
Times in One Cycle          1                     1                      3  
—————————————————————  ————————————  ———————————————————————————————  ————————
Pulse Width (long /       200/2       64/1       32/1        32/1      32/1  
short, in microsec)
—————————————————————  ————————————  ———————————————————————————————  ————————
Scan Speed (deg/sec)       36          18         24          36        36  
—————————————————————  ————————————  ———————————————————————————————  ————————
PRF(s) (Hz)               400           dual PRF (ray alternative)     2000  
                                     667  833  938  1250  1333  2000  
—————————————————————  ————————————  ———————————————————————————————  ————————
Pulses / Ray               8          26   33   27   34    37    55     64  
—————————————————————  ————————————  ———————————————————————————————  ————————
Ray Spacing (deg.)        0.7          0.7       0.7          1.0       1.0  
—————————————————————  ————————————  ———————————————————————————————  ————————
Azimuth (deg)                                Full Circle  
—————————————————————  ————————————  ———————————————————————————————  ————————
Bin Spacing (m)                                  150  
—————————————————————  ————————————  ———————————————————————————————  ————————
Max. Range (km)           300        150         100           60       60  
—————————————————————  ————————————  ———————————————————————————————  ————————
Elevation Angle(s)        0.5        0.5      1.0, 1.8,   18.7, 23.0,   90
(deg.)                                        2.6, 3.4,   27.9, 33.5,
                                              4.2, 5.1,      40.0 
                                              6.2, 7.6, 
                                              9.7, 12.2, 
                                              15.2  

(4) Results 

The data were obtained continuously thru the cruise from Dec.23, 2015 to Jan.23, 
2016, except the period when Mirai was in the area where the observation is not 
permitted. The further analyses will be done after the cruise. 

(5) Data Archive 

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




2.9.  Aerosol optical characteristics measured by Ship-borne Sky radiometer 

(1) Personnel 
       Kazuma Aoki (University of Toyama) -Principal Investigator (not on board)
       Tadahiro Hayasaka (Tohoku University) -Co-Investigator (not onboard) 
       (Sky radiometer operation was supported by Global Ocean Development Inc.) 

(2) Objectives 

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

(3) Methods and Instruments 

The sky radiometer measures the direct solar irradiance and the solar aureole 
radiance distribution with seven interference filters (0.34, 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. 


@ Measured 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) Preliminary results 

Only data collection were performed onboard. At the time of writing, the data 
obtained in this cruise are under post-cruise processing at University of 
Toyama. 

(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. 



2.10. Aerosol and gases 

(1) Personnel 
       Yugo Kanaya (JAMSTEC) not on board 
       Kazuhiko Matsumoto (JAMSTEC) on board (Leg 1) 
       Fumikazu Taketani (JAMSTEC) not on board 
       Takuma Miyakawa (JAMSTEC) not on board 
       Hisahiro Takashima (JAMSTEC) not on board 
       Yuichi Komazaki (JAMSTEC) not on board 
       Hitoshi Matsui (JAMSTEC) not on board 
       Operation was supported by Global Ocean Development Inc. 

(2) Objectives 

The major objective is to investigate processes of biogeochemical cycles between 
the atmosphere and the ocean. Particularly, we characterize the atmospheric 
aerosol particles by fluorescence techniques (autofluorescence and stained 
fluorescence) to observe biologically-produced particles. To study the 
possibility that those particles are ejected from the ocean surface as sea 
spray, relationship with the density/types of plankton in seawater is studied. 
Also, we investigate roles of atmospheric aerosols and gases, including black 
carbon and ozone, in the marine atmosphere in relation to climate change. 

(3) Methods and Instruments 

 i. Parameters continuously observed species and parameters 

   - Number density of autofluorescent atmospheric aerosol particles 
   - Mass concentrations of black carbon (BC) particles 
   - Surface ozone (O3), and carbon monoxide (CO) mixing ratios 
   - Aerosol optical depth (AOD) and aerosol extinction coefficient (AEC) 

Online observations fluorescent particles and black carbon (BC) particles were 
made by the instruments based on flash.lamp-induced fluorescence (WIBS-4A, 
Droplet Measurement Technologies) and laser-induced incandescence (SP2, Droplet 
Measurement Technologies). Ambient air was continuously sampled from the flying 
bridge and drawn through a ~3-m-long conductive tube and introduced to the 
instruments after dried. In WIBS-4A, two pulsed xenon lamps emitting UV light 
(280 nm and 370 nm) were used for excitation and fluorescence emitted from a 
single particle within 310.400 nm and 420.650 nm wavelength windows was 
recorded. 

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 multiple elevation angles, 1.5, 3, 5, 10, 20, 30, 90 degrees, were scanned 
repeatedly (every ~15-min) using a movable prism. 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. Using derived aerosol 
information, retrievals of the tropospheric vertical column/profile of NO2 and 
other gases were made. 

For ozone and CO measurements, 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. 

ii. Sampling and offline analysis 

During Leg 1, atmospheric aerosol particles and surface seawater samples were 
manually collected for the offline measurements of stained fluorescence from 
particles. The collected timing and locations are listed in Table 2.10.1. The 
stained fluorescence observations were made with Bioplorer KB-VKH01 (Koyo Sangyo 
Co.,Ltd ). Double staining with DAPI and PI was utilized, for the detection of 
total and dead biological particles upon fluorescence signal from individual 
particles induced by the UV and green light excitation. The atmospheric aerosol 
particles were directly collected onto membrane filters to be used in the 
Bioplorer. The seawater samples were filtrated by the membrane filter and then 
the filter was set in the Bioplorer for the stained fluorescence measurements. 
For reference, autofluorescence was also analyzed by the Bioplorer before 
staining. 

During Leg 1 and 2, ambient aerosol particles were collected along cruise track 
using a high-volume air sampler (HV.525PM, SIBATA) located on the flying bridge 
operated at a flow rate of 500 L min-1. To avoid collecting particles emitted 
from the funnel of the own vessel, the sampling period was controlled 
automatically by using a “wind-direction selection system”. Coarse and fine 
particles separated at the diameter of 2.5 µm were collected. The filter samples 
obtained during the cruise are subject to chemical analysis of aerosol 
composition, including water-soluble ions and trace metals. 

(4) Preliminary results 

N/A (Data analysis is to be conducted.) 

(5) 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 


Table 2.10.1. Timing and locations of atmospheric aerosol and seawater samples 
              for stained fluorescence analysis 

No.  Sample ID     Type       Collection timing     Latitude    Longitude    Depth 
                                     (UTC)          (deg-min)   (deg-min)     (m)  
——  ————————————  ————————  ——————————————————————  ——————————  ———————————  ————
 1  MR15-05_001a  aerosol   Dec 26, 2015 6:50 UTC   17-11.7 S   109-22.09 E  
 2  MR15-05_002a  aerosol   Dec 29, 2015 7:10 UTC   24-22.56 S  110-35.73 E  
 3  MR15-05_003s  seawater  Dec 29, 2015 4:30 UTC   24-22.59 S  110-35.41 E  0  
 4  MR15-05_004a  aerosol   Dec 30, 2015 9:20 UTC   22-51.57 S  110-43.98 E  
 5  MR15-05_005s  seawater  Dec 29, 2015 23:31 UTC  23-23.8 S   110-40.52 E  0  
 6  MR15-05_006a  aerosol   Dec 31, 2015 7:20 UTC   20-57.96 S  110-53.24 E  
 7  MR15-05_007a  aerosol   Jan 3, 2016 8:05 UTC    15-36.15 S  111-20.07 E  
 8  MR15-05_008a  aerosol   Jan 5, 2016 5:15 UTC    13-10.18 S  111-32.49 E  
 9  MR15-05_009a  aerosol   Jan 7, 2016 4:40 UTC    10-42.94 S  111-45.81 E  
10  MR15-05_010a  aerosol   Jan 7, 2016 23:40 UTC   10-2.79 S   111-49.87 E  
11  MR15-05_011s  seawater  Jan 8, 2016 5:03 UTC    9-28.97 S   111-52.94 E  0  
12  MR15-05_012a  aerosol   Jan 9, 2016 2:00 UTC    8-38.38 S   111-57.36 E  
13  MR15-05_013a  aerosol   Jan 10, 2016 7:15 UTC   9-11.8 S    113-44.21 E  


2.11  Sea Surface Gravity 

(1) Personnel 
    Katsuro Katsumata  JAMSTEC: Principal investigator          -leg1-
    Akihiko Murata     JAMSTEC: Principal investigator          -leg2-
    Wataru Tokunaga    Global Ocean Development Inc., (GODI)    -leg1-
    Tetsuya Kai        GODI -leg1 -Koichi Inagaki GODI          -leg2-
    Yutaro Murakami    GODI -leg1, leg2 -Ryo Kimura MIRAI crew  -leg1-
    Masanori Murakami  MIRAI crew                               -leg2-

(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] 

(4) Data Acquisition 

We measured relative gravity using LaCoste and Romberg air-sea gravity meter S-
116 (Micro-G LaCoste, LLC) during this cruise. 

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

(5) Preliminary Results 

Absolute gravity table is shown in Table 2.11-1. 


Table 2.11-1. Absolute gravity table of the MR15-05 cruise 

                              Absolute     Sea   Ship   Gravity at   S-116 
No. Date    UTC     Port       Gravity    Level  Draft   Sensor *   Gravity 
    mm/dd                       [mGal]    [cm]   [cm]     [mGal]     [mGal] 
——  —————  —————  ——————————  ——————————  —————  —————  ——————————  ————————
#1  11/05  01:07  Sekinehama  980,371.87   251   607    980,372.81  12662.42 
#2  01/25  06:38  Yokohama    979,741.75   196   625    979,742.56  12035.96 
————————————————————————————————————————————————————————————————————————————
*: Gravity at Sensor = Absolute Gravity + Sea Level*0.3086/100 + 
   (Draft-530)/100*0.2222 


(6) Data Archive 

Surface gravity data obtained during this cruise will be submitted to the Data 
Management Group (DMG) in JAMSTEC, and will be archived there. 

(7) Remarks (Times in UTC) 
     i) The following periods, the observation was carried out. 
        Leg1: 18:51, 23 Dec. 2015 to 22:40, 10 Jan. 2016 
        Leg2: 13:47, 17 Jan 2016 to 00:00, 25 Jan. 2016 
    ii) The following periods, depth data were available 
        Leg1: 19:35, 23 Dec. 2015 to 22:05, 10 Jan. 2016 
        Leg2: 13:47, 17 Jan 2016 to 06:26, 23 Jan. 2016 

2.12  Sea Surface Magnetic Field 

(1) Personnel  
    Katsuro Katsumata  JAMSTEC: Principal investigator        -leg1- 
    Akihiko Murata     JAMSTEC: Principal investigator        -leg2- 
    Wataru Tokunaga    Global Ocean Development Inc., (GODI)  -leg1- 
    Tetsuya Kai        GODI                                   -leg1- 
    Koichi Inagaki     GODI                                   -leg2- 
    Yutaro Murakami    GODI                                   -leg1, leg2- 
    Ryo Kimura         MIRAI crew                             -leg1- 
    Masanori Murakami  MIRAI crew                             -leg2- 

(2) Introduction 

Measurement of magnetic force on the sea is required for the geophysical 
investigations of marine magnetic anomaly caused by magnetization in upper 
crustal structure. We measured geomagnetic field using a three-component 
magnetometer during this cruise. 

(3) Principle of ship-board geomagnetic vector measurement 

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 × 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 
       R Hob + Hbp = R P Y F (b) 
where R = A-1, and Hbp = -R Hp. The magnetic field, F, can be obtained by 
measuring R, P, Y and Hob, if R and Hbp are known. Twelve constants in R 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. 

(4) Instruments on R/V MIRAI 

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. 

(5) Data Archive 

Sea surface magnetic data obtained during this cruise will be submitted to the 
Data Management Group (DMG) in JAMSTEC, and will be archived there. 

(6) Remarks (Times in UTC) 
 
      i) The following periods, the observation were carried out. 
         Leg1: 18:51, 23 Dec. 2015 to 22:40, 10 Jan. 2016 
         Leg2: 13:47, 17 Jan 2016 to 23:50, 24 Jan. 2016 

     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: 03:28 -03:54, 28 Dec. 2015 around 24-44S, 122-36E 
               09:42 -10:05, 01 Jan. 2016 around 18-32S, 110-05E 
               14:30 -14:56, 04 Jan. 2016 around 14-08S, 111-28E 
               22:08 -22:29, 09 Jan. 2016 around 09-10S, 113-45E 
         Leg2: 01:15 -01:41, 18 Jan. 2016 around 13-07N, 130-39E 
               01:29 -01:53, 23 Jan. 2016 around 31-10N, 138-35E 

    iii) The following periods, depth data was available 
         Leg1: 19:35, 23 Dec. 2015 to 22:05, 10 Jan. 2016 
         Leg2: 13:47, 17 Jan 2016 to 06:26, 23 Jan. 2016 


2.13.  Satellite image acquisition 

(1)  Personnel  
     Katsuro Katsumata  JAMSTEC: Principal investigator        -leg1- 
     Akihiko Murata     JAMSTEC: Principal investigator        -leg2- 
     Wataru Tokunaga    Global Ocean Development Inc., (GODI)  -leg1-
     Tetsuya Kai        GODI                                   -leg1-
     Koichi Inagaki     GODI                                   -leg2-
     Yutaro Murakami    GODI                                   -leg1, leg2- 
     Ryo Kimura         MIRAI crew                             -leg1- 
     Masanori Murakami  MIRAI crew                             -leg2-  

(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 throughout this cruise. 

(4) Data archives 

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



3. Station Observation 

3.1 CTDO2 Measurements 
       February 17, 2016 

(1) Personnel 
       Hiroshi Uchida (JAMSTEC) 
       Shinsuke Toyoda (MWJ) 
       Hiroyuki Hayashi (MWJ) 
       Shungo Oshitani (MWJ) 
       Keisuke Takeda (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). 

To minimize attitude motion of the CTD package (rotation, pitching and rolling) 
and twist of the armored cable, a slip ring swivel was introduced between the 
armored cable and the CTD package. 


Fig. 3.1.1: A photo of the slip ring swivel attached between the armored cable 
            and the CTD.


(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 (SBE 43) 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 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 09P38273_74766 (pressure sensor S/N: 0786) 
Temperature sensor: 
       SBE 3plus, S/N 03P4815 (primary) 
       SBE 3, S/N 031525 (secondary) 
Conductivity sensor: 
       SBE 4, S/N 042435 (primary) 
       SBE 4, S/N 042854 (secondary) 
Oxygen sensor: 
       SBE 43, S/N 430330 
       JFE Advantech RINKO-III, S/N 0024 (foil batch no. 144002A) 
Pump: 
       SBE 5T, S/N 054595 (primary) 
       SBE 5T, S/N 054598 (secondary) 
Altimeter: 
       PSA-916T, S/N 1157 
Deep Ocean Standards Thermometer: 
       SBE 35, S/N 0022 Fluorometer: 
       Seapoint Sensors, Inc., S/N 3497 (measurement range: 0-10 µg/L) 
Transmissometer: 
       C-Star, S/N CST-1363DR 
PAR: 
       Satlantic LP, S/N 0049 
CDOM: ECO FL CDOM, S/N FLCDRTD-2014 (measurement range: 0-500 ppb) 
Carousel Water Sampler: 
       SBE 32, S/N 0924 
Water sample bottle: 
       12-litre Niskin-X model 1010X (no TEFLON coating) 


(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 a dead-weight piston gauge (Model 480DA, S/N 23906; Piston 
unit, S/N 079K; Weight set, S/N 3070; Bundenberg Gauge Co. Ltd., Irlam, 
Manchester, UK). 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 0786, 13 July 2015 
              slope = 0.99980434 
              offset = –0.13013 


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 03P4815, 16 April 2015 
       S/N 031525, 28 July 2015 

Pressure sensitivities of SBE 3s were corrected according to a method by Uchida 
et al. (2007), for the following sensors. 
       S/N 03P4815, –3.4597e–7 [°C/dbar] 


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, 1 May 2015 
              S/N 042854, 1 May 2014 

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 430330, 10 May 2015 

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 0022, 4 March 2009 

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). 

       S/N 0022, 4 February 2015 (slope and offset correction) 
              Slope = 1.000007 
              Offset = 0.000246 

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. 


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 (µmol/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) 

The calibration coefficients were determined by using the data obtained in the 
R/V Mirai MR15-03 cruise. 

x. 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 0049, 22 January 2009 

xi. 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 30 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. At station 001_1, 012_1, 
022_1, 022_2, 030_1 and 037_1, specially washed Niskin-X bottles were used for 
#2 and #3, since samples for incubation were collected from the bottles. 
       Data acquisition software 
              SEASAVE-Win32, version 7.23.2 

ii. Data collection problems 
(a) Miss trip, miss fire, and remarkable leak 
       Niskin bottles did not trip correctly at the following stations. 
       Miss trip  Miss fire  Leak  
         none       none     007_1 #14 stopcock: O-ring of the stopcock replaced  
                             025_1 #30 stopcock: O-ring of the end closure replaced  
                             033_3 #27 end closure: O-ring of the end closure replaced  

(b) Failure of the slip ring swivel 

The slip ring swivel failed by sea water immersion from the nipple joints at 
beginning of station 011_1. Therefore, the slip ring swivel was detached from 
the CTD cast. 

(d) Cable replacement 

Cables for sensors were replaced after the following stations. 
       900_1: noise of the secondary temperature 
       010_2: noise of fluorometer 
       035_1: noise of transmissometer at station 034_1 and 035_1 

(e) Noise in down cast data 

Secondary conductivity data were noisy at station 043_1 from 698 dbar of down 
cast due to a jellyfish. Transmissometer data were noisy at station 016_1 (from 
1484 to 2556 dbar), 034_1 (from 539 to 544 dbar), and the data were removed and 
linearly interpolated. CDOM data were flagged as 4 (bad measurement) for depths 
deeper than about 4500 m due to noise and large shift of the data 

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. 

TCORP (original module, version 1.1) corrected the pressure sensitivity of the 
SBE 3 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, 
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. 

The pre-and the post-casts deck pressure data showed temperature dependency for 
the pressure sensor (Fig. 3.1.2). To correct the temperature dependency, the 
manufacturer’s calibration coefficients were slightly modified on board as 
follows: 

       T1 = 29.88499 
       T2 = –2.565740e–4 
       T3 = 4.799030e–6 
       Offset = 0.0 

Time series of the CTD deck pressure is shown in Fig. 3.1.3. 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 (–0.01 dbar) from the pre-cruise calibration. The post-cruise correction 
of the pressure data is not deemed necessary for the pressure sensor. 


Fig. 3.1.2: Pre- and post-casts CTD deck pressure. Atmospheric pressure 
            deviation from a standard atmospheric pressure was subtracted from 
            the CTD deck pressure. Black dots show the original data and red 
            dots show the data corrected for the temperature dependency of the 
            sensor.

Fig. 3.1.3: Time series of the CTD deck pressure. 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. 


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 SBE, Inc in 
2016 

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 
3.1.1. The results of the post-cruise calibration for the CTD temperature are 
summarized in Table 3.1.2 and shown in Fig. 3.1.4. 


Table 3.1.1: Calibration coefficients for the CTD temperature sensors. 

          ===================================================       
          Serial number  c0 (°C/dbar)  c1 (°C/day)  c2 (°C)     
          —————————————  ————————————  ———————————  ———————    
             3P4815      –4.79962e–8      0.0       –0.0007 


Table 3.1.2: 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  ————————————————————    ———————————————————————————
               Number  Mean  Sdev      Number  Mean Sdev 
                       (mK)  (mK)              (mK) (mK) 
       3P4815   467    0.0   0.2        854   –0.0  6.8 


Fig. 3.1.4: Difference between the CTD temperature (primary) and the SBE 35. 
            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.


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 = c0 × C + c1 × P + c2 × C × P + c3 × C2 + c4 × t + c5 

where C is CTD conductivity in S/m, P is pressure in dbar, t is time in days, 
and c0, c1, c2, c3, c4 and c5 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 
coefficient c4 was set to zero for this cruise. 

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 3.1.3. The results of the post-cruise 
calibration for the CTD salinity are summarized in Table 3.1.4 and shown in Fig. 
3.1.5. 


Table 3.1.3: Calibration coefficients for the CTD conductivity sensors. 

  =======================================================================
  Serial       c0           c1           c2          c3            c4 
  Number               [S/(m dbar)]    (1/dbar)    [1/(S/m)]     (S/m) 
  ———————————————————————————————————————————————————————————————————————
  042435  –1.51687e–4   1.09232e–7   –3.67361e–8  4.72348e–12  5.09192e–4 


Table 3.1.4: 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 1950 dbar. Number 
             of data used is also shown. 

             =================================================== 
             Serial  Pressure ≥ 1950 dbar   Pressure < 1950 dbar
             Number  ————————————————————   ————————————————————
                      Number  Mean  Sdev     Number  Mean  Sdev 
             042435    493    –0.0  0.4       861     0.2   4.5 


Fig. 3.1.5: Difference between the CTD salinity (primary) and the bottle 
            salinity. Blue and red dots indicate before and after the post-
            cruise calibration, respectively. Lower two panels show histogram of 
            the difference after the calibration.


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 byUchida 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 exciting 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 3.1.5. The results 
of the post-cruise calibration for the RINKO oxygen are summarized in Table 
3.1.6 and shown in Fig. 3.1.6. 


Table 3.1.5: Calibration coefficients for the RINKO oxygen sensors. 

                     ======================== 
                     Coefficient    S/N 0024 
                     ———————————  ———————————
                     c0            5.56160e–3  
                     c1            2.16834e–4  
                     c2            2.72251e–6  
                     c3           –1.03972e–3  
                     c4           –2.07308e–2  
                     c5            0.326691  
                     c6            1.52604e–4  
                     c7            1.29920e–5  
                     Cp            0.015  


Table 3.1.6: 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 1950 dbar. Number of data 
             used is also shown. 

             =================================================== 
             Serial  Pressure ≥ 1950 dbar   Pressure < 1950 dbar
             Number  ————————————————————   ————————————————————
                      Number  Mean  Sdev     Number  Mean  Sdev 
                               [µmol/kg]             [µmol/kg] 
             ——————  ———————  ————  ————     ——————  ————  ————
             0024      502    0.11  0.39      859    0.02  0.57 


Fig. 3.1.6: Difference between the CTD oxygen and the bottle oxygen. Blue and 
            red dots indicate before and after the post-cruise calibration, 
            respectively. Lower two panels show histogram of the difference 
            after the calibration.


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 
µE/(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) (Fig. 3.1.7). The calibration coefficients are listed in Table 3.1.7. 
The results of the post-cruise calibration for the fluorometer are summarized in 
Table 3.1.8 and shown in Fig. 3.1.8. 

Fig. 3.1.7: Comparison of the CTD fluorometer and the bottle sampled 
            chlorophyll-a. The regression lines are also shown. 


Table 3.1.7: Calibration coefficients for the CTD fluorometer.

                      ===========================
                          c0          c1     Note
                      ———————————  ————————  ————
                      –2.35932e–3  0.689112 


Table 3.1.8: 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 
                      ——————  ——————————  —————————
                       156    –0.00 µg/L  0.07 µg/L 


Fig. 3.1.8: Comparison of the CTD fluorometer and the bottle sampled 
            chlorophyll-a. Blue and red dots indicate before and after the post-
            cruise calibration, respectively. Lower panel shows histogram of the 
            difference after the calibration. Data obtained at daytime are also 
            shown in this figure. 


vi. Transmissometer 

The transmissometer (Tr in %) is calibrated as 

       Tr = (V–Vd) / (Vr–Vd) × 100 

where 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 
(0.0012) 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. 
3.1.9), Vr is expressed as 

       Vr = c0 + c1×t + c2×t2 

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

Maximum signal was extracted for each cast (Fig. 3.1.9). Data whose depth of the 
maximum signal was shallower than 200 dbar were not used to estimate Vr (black 
dots in Fig. 3.1.9). Fits were made iteratively, removing negatively deviated 
outliers (red dots in Fig. 3.1.9) greater than 2 standard deviations until no 
more outliers remain. The calibration coefficients thus determined are listed in 
Table 3.1.9. The coefficient c2 was set to zero for this cruise. 


Fig. 3.1.9: Time series of an output signal (voltage) from transmissometer at 
            deep ocean (Vdeep). The black solid line indicates the modeled 
            signal in the deep clear ocean. Black and red dots were not used to 
            estimate the final calibration coefficients (see text for detail). 


Table 3.1.9: Calibration coefficients for the CTD transmissometer. 

                      ================================= 
                      Leg     c0        c1         Vd 
                      ———  ———————  ———————————  ——————
                       1   4.61740  –2.94693e–3  0.0012 


vii. 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 – 0.046. 


vii. CDOM 

The CDOM sensor wasn’t calibrated, since the reference data (see Section 3.9) 
was not adequate for the in-situ calibration. 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. 

(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. 



3.2 Bottle Salinity 
       January 27, 2016 

(1) Personnel 
       Hiroshi Uchida (JAMSTEC) 
       Sonoka Wakatsuki (MWJ) 
       Hiroki Ushiromura (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. 

ii. Instruments and Methods 

Salinity of water samples was measured with a salinometer (Autosal model 8400B; 
Guildline Instruments Ltd., Ontario, Canada; S/N 62556), which was modified by 
adding an peristaltic-type intake pump (Ocean Scientific International Ltd., 
Hampshire, UK) and two platinum 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 this 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 were measured during the cruise. 

(4) Results 

i. Standard Seawater 

Standardization control was set to 715. The value of STANDBY was 5216±0001 and 
that of ZERO was 0.00000 or ±0.00001. We used IAPSO Standard Seawater batch P157 
whose conductivity ratio is 0.99985 (double conductivity ratio is 1.99970) as 
the standard for salinity measurement. We measured 66 bottles of the Standard 
Seawater during the cruise. History of double conductivity ratio measurement of 
the Standard Seawater is shown in Fig. 3.2.1. 

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 by using the least square method (thin black line 
in Fig. 3.2.1). No remarkable time drift was estimated from the Standard 
Seawater measurement. The average of double conductivity ratio was 1.99968 and 
the standard deviation was 0.00001, which is equivalent to 0.0002 in salinity. 


Fig. 3.2.1: History of double conductivity ratio measurement of the Standard 
            Seawater (P157). 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 µm 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 in order 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 257 pairs of replicate samples collected from the same Niskin bottle. 
Histogram of the absolute difference between replicate samples is shown in Fig. 
3.2.2. The root-mean-square for 256 pairs of replicate samples which are 
acceptable-quality data was 0.0002. 


Fig. 3.2.2: 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, we took 36 samples collected from the different Niskin bottles 
at same depth (2000 dbar) of station 900, instead of taking duplicate samples. 
The average of salinity with the standard deviation was 34.7300 ± 0.0002. 

(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. 


3.3 Density 
       February 18, 2016 

(1) Personnel 
       Hiroshi Uchida (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, 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 kg m–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 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) 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 
(20 ºC) with TEOS-10. 

(4) Results 

Results of density measurements of the Reference Material for Density in 
Seawater (Dn-RM1) were shown in Table 3.3.1. 

A total of 32 pairs of replicate samples were measured. The root-mean square of 
the absolute difference of replicate samples was 0.0009 g/kg. 

The measured density salinity anomalies (δSA) are shown in Fig. 3.3.1. The 
measured .SA well agree with 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 3.3.1: Result of density measurements of the Reference Material for 
             Density in Seawater (prototype Dn-RM1). 

             =============================================== 
             Date        Stations      Mean density of  Note 
                                        Dn-RM1 (kg/m3) 
             ——————————  ————————————  ———————————————  ————
             2015/12/29  1,2,3,4,6,10    1024.2631 
             2015/12/31  14              1024.2637 
             2016/01/01  18              1024.2628 
             2016/01/02  22              1024.2627 
             2016/01/03  26              1024.2631 
             2016/01/04  31              1024.2619 
                         33              1024.2622 
             2016/01/06  37              1024.2638 
             2016/01/07  41              1024.2634 
                         42              1024.2624 
             2016/01/08  43              1024.2597 
                         45              1024.2601 
             2016/01/08  46,47           1024.2609 
                         48,50           1024.2602 
             2016/01/09  51,52           1024.2640 

             Average:                    1024.2623 ± 0.0014 


Figure 3.3.1: 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.



3.4 Oxygen 

                                                                January 27, 2016 
                                                               Yuichiro Kumamoto 
                            Japan Agency for Marine-Earth Science and Technology 

(1) Personnel 
    Yuichiro Kumamoto 1), Misato Kuwahara 2), Keitaro Matsumoto 2), 
    Masahiro Orui 2), and Haruka Tamada 2) 
      1) Japan Agency for Marine-Earth Science and Technology 
      2) Marine Works Japan Co. Ltd 

(2) Objectives 

Dissolved oxygen is one of good tracers for the ocean circulation. Climate 
models predict a decline in oceanic dissolved oxygen concentration and a 
consequent expansion of the oxygen minimum layers under global warming 
conditions, which results mainly from decreased interior advection and ongoing 
oxygen consumption by remineralization. The mechanism of the decrease, however, 
is still unknown. During MR15-05 cruise, we measured dissolved oxygen 
concentration from surface to bottom layers at all the hydrocast stations in the 
eastern Indian Ocean. All the stations reoccupied the WOCE Hydrographic Program 
I10 stations in 1995. Our purpose is to evaluate temporal change in dissolved 
oxygen concentration in the North Pacific Ocean during the pastdecades. 

(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): NMIJ CRM 3006-a No.028, 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. / 10 cm3 of 
      titration vessel 
    Detector; 
      Automatic photometric titrator, DOT-01X manufactured by Kimoto Electronic 
      Co. Ltd. 

(5) Seawater sampling 

Following procedure is based on a determination method in the WHP Operations 
Manual (Dickson, 1996). Seawater samples were collected from 12-liters Niskin 
sampler bottles attached to the CTD-system. Seawater for bottle oxygen 
measurement was transferred from the Niskin sampler bottle to a volume 
calibrated glass flask (ca. 100 cm3). Three times volume of the flask of 
seawater was overflowed. Sample temperature was measured using a thermometer. 
Then two reagent solutions (Reagent I, II) of 0.5 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 a 
laboratory until they were titrated. 

(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 two sets of the titration 
apparatus, named DOT-6 and DOT-8. Dissolved oxygen concentration (µmol kg-1) was 
calculated by the sample temperature during the sampling, CTD 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. Pure 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 0.5 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 3.4.1 shows result of the standardization 
during this cruise. Coefficient of variation (C.V.) for the standardizations was 
0.016 ± 0.005 % (standard deviation, n = 16), c.a. 0.05 µmol kg-1 . 

(8) Determination of the blank 

The oxygen in the pickling reagents I (0.5 cm3) and II (0.5 cm3) was assumed to 
be 3.8 × 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 0.5 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 3.4.1). 
The averaged blank values for DOT-6 and DOT.8 were 0.002 ± 0.002 (standard 
deviation, n=8) and 0.000 ± 0.002 (standard deviation, n=8) cm3, respectively. 


Table 3.4.1: Results of the standardization (End point, E.P.) and the blank 
             determinations (cm3). 

       Date               Na2S2O3      DOT-6         DOT-8     Stations  
       (UTC)    KIO3 No.    No.     E.P.  blank   E.P.  blank  
    ——————————  ————————  ———————  —————  —————  —————  —————  ————————
    2015/12/27  K1504E02  T1505A   3.962  0.002  3.963  0.000  001-015  
    2015/12/30  K1504E03  T1505A   3.965  0.003  3.965  0.001  016-026  
    2016/01/03  K1504E04  T1505B   3.957  0.000  3.959  0.001  027-041  
    2016/01/06  K1504E05  T1505B   3.957  0.002  3.958  0.000  042-052  


(9) Replicate sample measurement 

From a routine CTD cast at all the stations, a pair of replicate samples was 
collected at four layers of 50, 400, 1800, and 3500 dbars. The total number of 
the replicate sample pairs in good measurement (flagged 2) was 170 (Fig. 3.4.1). 
The standard deviation of the replicate measurement was 0.60 µmol kg-1 
calculated by a procedure (SOP23) in DOE (1994). 


Figure 3.4.1: Oxygen difference between measurements of a replicate pair against 
              oxygen concentration. 


Table 3.4.2 Results of duplicate sample measurements. 

                  Duplicated          Pres.    Oxygen 
                   Niskin #   Niskin  (db)   (µmol kg-1)  
                  ——————————  ——————  —————  ———————————
                      1       X12J01  2000     139.67  
                      2       X12J02  2000     139.74  
                      3       X12J03  2001     139.73  
                      4       X12104  2001     139.91  
                      5       X12J05  2000     139.78  
                      6       X12J06  2000     139.91  
                      7       X12J07  2000     139.85  
                      8       X12J08  2000     139.93  
                      9       X12J09  2000     139.87  
                     10       X12J10  2000     139.85  
                     11       X12J11  2001     139.96  
                     12       X12J12  2001     139.87  
                     13       X12J13  2001     140.02  
                     14       X12J14  2001     139.86  
                     15       X12J15  2001     139.89  
                     16       X12J16  2001     139.92  
                     17       X12J17  2000     139.97  
                     18       X12J18  1999     139.86  
                     19       X12J19  2000     139.97  
                     20       X12J20  1999     139.99  
                     21       X12J21  2000     139.94  
                     22       X12J22  2001     139.90  
                     23       X12J23  2001     139.97  
                     24       X12J24  2001     139.98  
                     25       X12J25  2000     139.91  
                     26       X12J26  2001     139.94  
                     27       X12J27  2000     139.93  
                     28       X12J28  2001     139.70  
                     29       X12J29  2001     139.89  
                     30       X12J30  2001     139.78  
                     31       X12J31  2001     139.88  
                     32       X12J32  2001     139.79  
                     33       X12J33  2001     140.02  
                     34       X12J34  2001     139.92  
                     35       X12J35  2000     139.77  
                     36       X12J36  2000     139.85  


(10) Duplicate sample measurement 

At Station 900 (test), duplicate sampling were taken at 2000 dbar for all the 
Niskin bottles (36 bottles, Table 3.4.2). The standard deviation of the 
duplicate measurements were calculated to be 0.09 µmol kg-1, which were nearly 
equivalent with that of the replicate measurements (0.06 µmol 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 standard solution (Lot K1504E01) as samples before the 
cruise on 25 Dec. 2016. Concentration of the CSK solution against that of our 
KIO3 solution was calculated to be 0.010006 ± 0.000002 N and 0.010006 ± 0.000002 
N for DOT-6 and DOT-8, respectively. 

(12) Quality control flag assignment 

Quality flag values were assigned to oxygen measurements using the code defined 
in Table 0.2 of WHP Office Report WHPO 91-1 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 3.4.3). 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 CTD oxygen 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 flagged4. 

  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. 


Table 3.4.3: Summary of assigned quality control flags. 

                Flag  Definition              Number*  
                ————  ——————————————————————  ———————
                  2   Good                       1363  
                  3   Questionable                  0  
                  4   Bad                           0  
                  5   Not report (missing)          0  
                                          Total  1363  

                *Replicate samples (n = 170) 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. 

DOE (1994) Handbook of methods for the analysis of the various parameters of the 
    carbon dioxide system in sea water; version 2. A.G. Dickson and C. Goyet 
    (eds), ORNL/CDIAC-74. 

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 



3.5 Nutrients 

(1) Personnel 

Michio AOYAMA( JAMSTEC/Fukushima Univ. , Principal Investigator) 

LEG 1 
Elena HAYASHI (Department of Marine & Earth Science, Marine Works Japan Ltd.) 
Tomomi SONE (Department of Marine & Earth Science, Marine Works Japan Ltd.) 
Kohei MIURA (Department of Marine& Earth Science, Marine Works Japan Ltd.) 
Minoru KAMATA (Department of Marine & Earth Science, Marine Works Japan Ltd.) 

LEG 2 
Elena HAYASHI (Department of Marine & Earth Science, Marine Works Japan Ltd.) 
Minoru KAMATA (Department of Marine & Earth Science, Marine Works Japan Ltd.) 

(2) Objectives 

The objectives of nutrients analyses during the R/V Mirai MR1505 cruise, GO-SHIP 
I10 repeat cruise in 2015-2016, in the Eastern Indian Ocean are as follows; 
-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 
 the previous high quality experiments data of WOCE previous I10 cruises in 
1995, GEOSECS, IGY and so on. -Study of temporal and spatial variation of 
nitrate: phosphate ratio, so called Redfield ratio. -Obtain more accurate 
estimation of total amount of nitrate, silicate and phosphate 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 50 QuAAtro 2-HR runs for the samples at 56 casts, 52 stations in MR1505. 
The total amount of layers of the seawater sample reached up to 2484 for MR1505. 
We made duplicate measurement at all layers at all stations. 

(4) Instrument and Method 

(4.1) Analytical detail using QuAAtro2-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 3.5.1 to 3.5.5. 

(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 3.5.1: 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 3.5.2: 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 3.5.3: 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 3.5.4: 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 3 days. 

Alkaline phenol 

Dissolve 10 g phenol, C6H5OH, 5 g sodium hydroxide and citric acid, C6H8O7, in 
200 mL DIW. Stored in a dark bottle and prepared at a week about. 

NaClO solution 

Mix 3 mL sodium hypochlorite solution, NaClO, in 47 mL DIW. Stored in a dark 
bottle and fleshly prepared before every measurement. This reagent is prepared 
0.3% available chlorine. 


Figure 3.5.5: 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, 23 ± 2 deg. C, in about 30 minutes before use to stabilize 
the temperature of samples in MR1505. 

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, while in 
 case of bio-cast we used surface CTD data. 
-Calibration curves to get nutrients concentration were assumed second order 
 equations. 


(5) Nutrients standards 

(5.1) Volumetriclaboratory ware ofin-house standards 

All volumetric glass ware and polymethylpentene (PMP) ware were gravimetrically 
calibrated. These volumetric flasks were gravimetrically calibrated at the 
temperature of using in the laboratory within 0 to 4 K. 

Volumetricflasks 

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. High quality plastic (polymethylpentene, PMP, or 
polypropylene) volumetric flasks were gravimetrically calibrated and used only 
within 0 to 4 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 0 to 4 K. The weights obtained in the 
calibration weightings were corrected for the density of water and air buoyancy. 

Pipettes and pipettors 

All pipettes have nominal calibration tolerances of 0.1 % or better. These were 
gravimetrically calibrated in order to verify and improve upon this nominal 
tolerance. 

(5.2) 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, nitrite ion standard solution of JCSS (NO2 1000mg/L) 
provided by Wako, Lot. ECP4122, CAS No. 7632-00-0, was used. The nitrite 
concentration was assigned by ion chromatography method using secondary standard 
solution of nitrite ion. ECP4122 was certified as 999mg L-1 (± 0.7 % k=2). 

For phosphate standard, “potassium dihydrogen phosphate anhydrous 99.995 
suprapur®” provided by Merck, Lot. B0691108204, 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 
HC41358736 are used. The silicate concentration is certified by NIST-SRM3150. 
HC41358736 was certified as 982 mg kg-1 with the expanded uncertainty of ± 5 mg 
kg-1 (k=2). In the previous cruises, we assigned correction factor of merck 
solutions are shown in table 3.5.1 to ensure internal comparability among 
WOCE/CLIVAR cruises, we however used merck certified concentration to keep 
traceability to SI for silicate concentration throughout MR1505 and in the 
future cruises. 

For ammonium standard, we use certified reference material of “ammonium 
chloride” provided by NMIJ, CAS No. 12125-02-9, of which lot number is NMIJ CRM 
3011-a with the expanded uncertainty of ± 0.065 mass fraction % (k=2). 


Table 3.5.1: A history of assigned factor of Merck solutions 

     Lot        Factor     Date     Reference  
——————————————  ——————  ——————————  ——————————————————————————
Merck OC551722  1.001   2006/5/24
Merck HC623465  1.000
Merck HC751838  0.998   2007/4/13
Merck HC814662  0.999   2008/8/27
Merck HC074650  0.975   2010/11/5  
Merck HC097572  0.976   2011/06/20  RM Lot. BA, AY, BD, BE, BF  
Merck HC382250  0.973   2013/9/14   RM Lot. BS, BU, BT, BD  


          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. 

          Ultrapure 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 µm pore size capsule cartridge filter. This water was stored in 20 liter 
cubitainer with paper box. After stored for 5 month, a 1000 liter bag were 
filled with this LNSW filtering once more using 0.20 µm pore size capsule 
cartridge filter and irradiating by ultraviolet light in August 2015. After 
circulation of filtering and irradiating for 24 hours, LNSW was drawn into 20 
liter cubitainer with paper box. The concentrations of nutrients of this LNSW 
were measured carefully in September 2015. 

Although LNSW was sterilized by filtration and UV irradiation, in-house standard 
solution prepared with this LNSW showed that concentrations of nitrate, nitrite 
and phosphate decreased about 2 % after 2 days in November 2015. This should be 
caused by micro-organismal activity. 

Therefore, LNSW was pasteurized at low temperature with 75 deg. C more than 12 
hours to suspend micro-organismal activity in December 2015 on board. The 
concentrations of nutrients of in-house standard solution using pasteurized LNSW 
became not to decrease after 2 days of preparation as expected. The 
concentrations of nutrients of pasteurized LNSW were measured again in December 
2015. 

(5.3) 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 3.5.2. The C standard is prepared according recipes as shown in Table 
3.5.3. All volumetric laboratory tools were calibrated prior the cruise as 
stated in chapter (5.1). 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 3.5.2: Nominal concentrations of nutrients for A, B and C standards. 

                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   BU   CA   BW   BZ    54   -    - 
     NO2(µM)  21700    26  865  BY   BU   CA   BW   BZ   1.0   -    - 
     SiO2(µM) 35000  2760       BY   BU   CA   BW   BZ   172   -    - 
     PO4(µM)   3000    60       BY   BU   CA   BW   BZ   3.7   -    - 
     NH4(µM)   4000   200       -    -    -    -    -    6.0  2.0   0  


Table3.5.3: Working calibration standard recipes. 

                    C std.  B-1 std.  B-2 std.  B-3 std
                    ——————  ————————  ————————  ———————
                     C-6     30 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 


(5.4) Renewal of in-house standard solutions. 

In-house standard solutions as stated in paragraph (5.2) were renewed as shown 
in Table 3.5.4 (a) to (c). 


Table 3.5.4(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 3.5.4(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) 


Table3.5.4(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. (870 µM NO2)            maximum 8 days 
                  36 µM                   NO3 when C Std. renewed 
                  34 µM                   NO2 when C Std. renewed 


(6) CRM 

To get the more accurate and high quality nutrients data to achieve the 
objectives stated above, huge numbers of the bottles of the reference material 
of nutrients in seawater were prepared and used during the previous cruises 
(Aoyama et al., 2006, 2007, 2008, 2009, 2012, 2014). In the previous worldwide 
expeditions, such as WOCE cruises, the higher reproducibility and precision of 
nutrients measurements were required (Joyce and Corry, 1994). Since no standards 
were available for the measurement of nutrients in seawater at that time, the 
requirements were described in term of reproducibility. The required 
reproducibility was 1%, 1 to 2%, 1 to 3% for nitrate, phosphate and silicate, 
respectively. Although nutrient data from the WOCE one-time survey was of 
unprecedented quality and coverage due to much care in sampling and 
measurements, the differences of nutrients concentration at crossover points are 
still found among the expeditions (Aoyama and Joyce, 1996, Mordy et al., 2000, 
Gouretski and Jancke, 2001). For instance, the mean offset of nitrate 
concentration at deep waters was 0.5 µmol kg-1 for 345 crossovers at world 
oceans, though the maximum was 1.7 µmol kg-1 (Gouretski and Jancke, 2001). At 
the 31 crossover points in the Pacific WHP one-time lines, the WOCE standard of 
reproducibility for nitrate of 1 % was fulfilled at about half of the crossover 
points and the maximum difference was 7 % at deeper layers below 1.6 deg. C in 
potential temperature (Aoyama and Joyce,1996). 

During the period from 2003 to 2014, RMNS were used to keep comparability of 
nutrients measurement among the 8 cruises of CLIVAR project (Sato et al., 2010), 
MR1005 cruise for Arctic research (Aoyama et al., 2010) and MR1006 cruise for 
“Change in material cycles and ecosystem by the climate change and its feedback” 
(Aoyama et al., 2011). 

In this MR1505 cruises, we used 6 lots of CRM (Lot BY, BU, CA, BW, BV, BZ) to 
ensure comparability and traceability to SI. 




(6.1) CRMs for this cruise 

5 lot of CRMs were used as calibration standards together with the C-6. 
Certified concentrations of these lots as shown in table 3.5.4 were used. These 
bottles were stored at a room in the ship, REAGENT STORE, where the temperature 
was maintained around 16 -25 deg. C. 

(6.2) Certified concentration for CRMs 

The concentrations for CRM lots BY, BU, CA, BW, BZ, and BV are shown in Table 
3.5.4. 


Table 3.5.4: Certified concentration and uncertainty(k=2) of CRMs. 

                                                  unit: µmol kg-1 
       ——————————————————————————————————————————————————————————
              Nitrate      Phosphate      Silicate      Nitrite  
           ————————————  —————————————  ————————————  ———————————
       BY   0.02 ± 0.02  0.039 ± 0.010   1.76 ± 0.06  0.02 ± 0.01  
       BU   3.94 ± 0.05  0.345 ± 0.009  20.92 ± 0.49  0.07 ± 0.01  
       CA  19.66 ± 0.15  1.407 ± 0.014  36.58 ± 0.22  0.06 ± 0.01  
       BW  24.59 ± 0.20  1.541 ± 0.014  60.01 ± 0.42  0.07 ± 0.01  
       BZ  43.35 ± 0.33  3.056 ± 0.033  161.0 ± 0.93  0.22 ± 0.01  
       BV  35.36 ± 0.35  2.498 ± 0.023  102.2 ± 1.10  0.05 ± 0.01  


(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 3.5.5 and 
Figures 3.5.6 to 3.5.8, the precisions for each parameter are generally good 
considering the analytical precisions during the R/V Mirai cruses conducted in 
2009 .2014. During this cruise, analytical precisions were 0.11% for nitrate, 
0.11% for phosphate and 0.10% for silicate in terms of median of precision, 
respectively. 


Table 3.5.5: Summary of precision based on the replicate analyses for all unit. 

                       Nitrate  Nitrite  Silicate  Phosphate  Ammonium  
                         CV%      CV%       CV%       CV %      CV %  
     ————————————————  ———————  ———————  ————————  —————————  ————————
 
     Median             0.11     0.17      0.10       0.11      0.36  
     Mean               0.11     0.18      0.10       0.11      0.39  
     Maximum            0.19     0.34      0.20       0.21      0.83  
     Minimum            0.03     0.07      0.03       0.04      0.12  
     N                   49       49        49         49        11  



Table 3.5.5a: Summary of precision based on the replicate analyses for unit 1. 

                       Nitrate  Nitrite  Silicate  Phosphate  Ammonium  
                         CV%      CV%       CV%       CV %      CV %  
     ————————————————  ———————  ———————  ————————  —————————  ————————
 
     Median             0.10     0.17      0.10       0.09      0.42 
     Mean               0.11     0.17      0.10       0.10      0.41 
     Maximum            0.17     0.27      0.20       0.14      0.83 
     Minimum            0.03     0.07      0.03       0.05      0.12 
     N                   24       24        24         24        9  


Table 3.5.5b: Summary of precision based on the replicate analyses for unit 2. 

                       Nitrate  Nitrite  Silicate  Phosphate  Ammonium  
                         CV%      CV%       CV%       CV %      CV %  
     ————————————————  ———————  ———————  ————————  —————————  ————————
 
     Median             0.11     0.18      0.10       0.13      0.27
     Mean               0.12     0.18      0.10       0.13      0.27
     Maximum            0.19     0.34      0.15       0.21      0.27
     Minimum            0.07     0.07      0.07       0.04      0.26
     N                   25       25        25         25        2  


Figure 3.5.6: Time series of precision of nitrate in MR1505.
Figure 3.5.7: Time series of precision of phosphate in MR1505.
Figure 3.5.8: Time series of precision of silicate in MR1505.


(7.2) CRMlot.BV measurement during this cruise 

CRM lot. BV was measured every run to monitor the comparability among runs. The 
results of lot. BV during this cruise are shown as Figures 3.5.9 to 3.5.11. 
Error bars represent analytical precision in figure 3.5.6 to 3.5.8. 


Figure 3.5.9: Time series of CRM-BV of nitrate in MR1505.
Figure 3.5.10: Time series of CRM-BV of phosphate in MR1505.
Figure 3.5.11: Time series of CRM-BV of silicate in MR1505.


(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 3.5.8 and Figures 
3.5.12 to 3.5.14. The carryover in nitrate and silicate had a bias by 
equipments. It was 0.06% and 0.05%, mean value, at Unit 2. The other hand, it 
was 0.17% and 0.13 %, mean value, at Unit 1. We carried out the maintenance for 
Unit 1 by changing for new glass coils and new transmission tube before the stn. 
22. The bias was clearly solved by the maintenance. 


Table 3.5.6: Summary of carry over throughout MR1505. 

                       Nitrate  Nitrite  Silicate  Phosphate  Ammonium  
                         CV%      CV%       CV%       CV %      CV %  
     ————————————————  ———————  ———————  ————————  —————————  ————————
 
     Median             0.10     0.11      0.07       0.10      0.42
     Mean               0.12     0.10      0.09       0.11      0.39
     Maximum            0.28     0.40      0.23       0.17      0.67
     Minimum            0.03     0.00      0.03       0.05      0.08
     N                   49       49        49         49        11 


Figure 3.5.12: Time series of carryover of nitrate in MR1505. 
Figure 3.5.13: Time series of carryover of phosphate in MR1505.
Figure 3.5.14: Time series of carryover of silicate in MR1505.


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

Empirical equations, eq. (1), (2) and (3) to estimate uncertainty of measurement 
of phosphate, nitrate and silicate are used based on measurements of 24 sets of 
CRMs during this cruise. Empirical equations, eq. (4) and (5) to estimate 
uncertainty of measurement of nitrite and ammonium are used 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 (%) = 
0.142 +0.136 * (1 /Cp)+0.005 * (1 /Cp)* (1 /Cp) ---(1) 
where Cp is phosphate concentration of sample. 

Nitrate Concentration Cno3 in µmol kg-1: 
Uncertainty of measurement of nitrate (%) = 
0.08 + 1.49 * (1 / Cno3) + 0.02 * (1 / Cno3) *(1 / Cno3) ---(2) 
where Cno3 is nitrate concentration of sample. 

Silicate Concentration Cs in µmol kg-1: 
Uncertainty of measurement of silicate (%) = 
0.11 + 0.96 * (1 / Cs) + 3.74 * (1 / Cs) * (1 / Cs)  ---(3)
where Cs is silicate concentration of sample.   

Nitrite Concentration Cno2 in µmol kg-1: 
Uncertainty of measurement of nitrite (%) = 
-0.10 + 0.18 * (1 / Cno2) + 0.000022 * (1 / Cno2) * (1 / Cno2)  ---(4)
where Ca is ammonium concentration of sample.   

Ammonium Concentration Ca in µmol kg-1: 
Uncertainty of measurement of ammonium (%) = 
10.8 + 0.9 * (1 / Ca) + 0.003 * (1 / Ca) * (1 / Ca)  ---(5)
where Ca is ammonium concentration of sample.   


Figure 3.5.15: Estimation of uncertainty for phosphate in MR1505. 
Figure 3.5.16: Estimation of uncertainty for nitrate in MR1505.
Figure 3.5.17: Estimation of uncertainty for silicate in MR1505.
Figure 3.5.18: Estimation of uncertainty for nitrite in MR1505.
Figure 3.5.19: Estimation of uncertainty for ammonium in MR1505. 



(8) Problems/improvements occurred and solutions 

(8.1) squashed air tube 

We found that peak shape at 1ch became broad in the middle of run for stn. 50. 
And segment air into inlet were too small. Then we found air tube to inlet was 
squashed by manifold cover. Because samples concentration of broad peak shape 
were lower than same samples of normal peak shape, we analysed again all samples 
of stn. 50. We accepted NO3 data of second run and others of first run for stn. 
50. 

(8.2) Phosphate channel 

Phosphate channel we observe slightly higher concentration of 0.015 µmol kg-1 
for lot BZ in terms of average of 49 runs, and slightly lower concentration of 
0.006 µmol kg-1 for lot BV in terms of average of 50 runs respectively. Most 
likely reason of these differences we found state above is optics/electronics 
malfunction of this channel of these analyzers. 

(8.3) Improvement of reduction rate at nitrate measurement 

Because of decrease of absorbance of maximum concentration of in-house standard 
solution, we changed a kind of pumptube of sample line at 1ch from ORG/WHT to 
ORG/YEL. In using ORG/WHT pumptube, absorbance of maximum concentration of In-
house standard solution was nearly 0.2. after changed, absorbance was 1.2. As 
flow rate of sample became more slowly, we achieved a good stable and high 
reduction rate which was 99.7% (+ 0.4% -0.7%) in terms of mean of 50 runs during 
this cruise. 


Figure 3.5.20: Time series of reduction of nitrate in MR1505.


(9) Data archive 

All data will be submitted to Data Management Group of JAMSTEC (DMG) and is 
currently under its control. 



References 

Aminot, A. and Kerouel, R. 1991. Autoclaved seawater as a reference material for 
    the determination of nitrate and phosphate in seawater. Anal. Chim. Acta, 
    248: 277-283. 

Aminot, A. and Kirkwood, D.S. 1995. Report on the results of the fifth ICES 
    intercomparison exercise for nutrients in sea water, ICES coop. Res. Rep. 
    Ser., 213. 

Aminot, A. and Kerouel, R. 1995. Reference material for nutrients in seawater: 
    stability of nitrate, nitrite, ammonia and phosphate in autoclaved samples. 
    Mar. Chem., 49: 221-232. 

Aoyama M., and Joyce T.M. 1996, WHP property comparisons from crossing lines in 
    North Pacific. In Abstracts, 1996 WOCE Pacific Workshop, Newport Beach, 
    California. 

Aoyama, M., 2006: 2003 Intercomparison Exercise for Reference Material for 
    Nutrients in Seawater in a Seawater Matrix, Technical Reports of the 
    Meteorological Research Institute No.50, 91pp, Tsukuba, Japan. 

Aoyama, M., Susan B., Minhan, D., Hideshi, D., Louis, I. G., Kasai, H., Roger, 
    K., Nurit, K., Doug, M., Murata, A., Nagai, N., Ogawa, H., Ota, H., Saito, 
    H., Saito, K., Shimizu, T., Takano, H., Tsuda, A., Yokouchi, K., and Agnes, 
    Y. 2007. Recent Comparability of Oceanographic Nutrients Data: Results of a 
    2003 Intercomparison Exercise Using Reference Materials. Analytical 
    Sciences, 23: 1151-1154. 

Aoyama M., J. Barwell-Clarke, S. Becker, M. Blum, Braga E. S., S. C. Coverly,E. 
    Czobik, I. Dahllof, M. H. Dai, G. O. Donnell, C. Engelke, G. C. Gong, Gi-
    Hoon Hong, D. J. Hydes, M. M. Jin, H. Kasai, R. Kerouel, Y. Kiyomono, M. 
    Knockaert, N. Kress, K. A. Krogslund, M. Kumagai, S. Leterme, Yarong Li, S. 
    Masuda, T. Miyao, T. Moutin, A. Murata, N. Nagai, G.Nausch, M. K. 
    Ngirchechol, A. Nybakk, H. Ogawa, J. van Ooijen, H. Ota, J. M. Pan, C. 
    Payne, O. Pierre-Duplessix, M. Pujo-Pay, T. Raabe, K. Saito, K. Sato, C. 
    Schmidt, M. Schuett, T. M. Shammon, J. Sun, T. Tanhua, L. White, E.M.S. 
    Woodward, P. Worsfold, P. Yeats, T. Yoshimura, A.Youenou, J. Z. Zhang, 2008: 
    2006 Intercomparison Exercise for Reference Material for Nutrients in 
    Seawater in a Seawater Matrix, Technical Reports of the Meteorological 
    Research Institute No. 58, 104pp. 

Aoyama, M., Nishino, S., Nishijima, K., Matsushita, J., Takano, A., Sato, K., 
    2010a. Nutrients, In: R/V Mirai Cruise Report MR10-05. JAMSTEC, Yokosuka, 
    pp. 103-122. 

Aoyama, M., Matsushita, J., Takano, A., 2010b. Nutrients, In: MR10-06 
    preliminary cruise report. JAMSTEC, Yokosuka, pp. 69-83 

Gouretski, V.V. and Jancke, K. 2001. Systematic errors as the cause for an 
    apparent deep water property variability: global analysis of the WOCE and 
    historical hydrographic data. REVIEW ARTICLE, Progress In Oceanography, 48: 
    Issue 4, 337-402. 

Grasshoff, K., Ehrhardt, M., Kremling K. et al. 1983. Methods of seawater 
    anylysis. 2nd rev. Weinheim: VerlagChemie, Germany, West. 

Hydes, D.J., Aoyama, M., Aminot, A., Bakker, K., Becker, S., Coverly, S., 
    Daniel, A., Dickson, A.G., Grosso, O., Kerouel, R., Ooijen, J. van, Sato, 
    K., Tanhua, T., Woodward, E.M.S., Zhang, J.Z., 2010. Determination of 
    Dissolved Nutrients (N, P, Si) in Seawater with High Precision and Inter-
    Comparability Using Gas-Segmented Continuous Flow Analysers, In: GO-SHIP 
    Repeat Hydrography Manual: A Collection of Expert Reports and Guidelines. 
    IOCCP Report No. 14, ICPO Publication Series No 134. 

Joyce, T. and Corry, C. 1994. Requirements for WOCE hydrographic programmed data 
    reporting. WHPO Publication, 90-1, Revision 2, WOCE Report No. 67/91. 

Kawano, T., Uchida, H. and Doi, T. WHP P01, P14 REVISIT DATA BOOK, (Ryoin Co., 
    Ltd., Yokohama, 2009). 

Kimura, 2000. Determination of ammonia in seawater using a vaporization 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). 



3.6  Chlorofluorocarbons and Sulfur hexafluoride 

Ken’ichi Sasaki 1), Hironori Sato 2), Katsunori Sagishima 2), 
and Hiroshi Hoshino 2) 

1) Mutsu Institute for Oceanography, Japan Agency for Marine Earth Science and 
   Technology 
2) Marine Works Japan Ltd. 


3.6.1  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. 

3.6.2  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 3-5-1: 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&2:    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 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.  




3.6.3  Procedures 

3.6.3.1  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 water bath 
controlled 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. 

3.6.3.2  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 170 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 rapidly 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 3-5-2 Analytical conditions 

SF6/CFCs(/N2O) simultaneous analyses 
————————————————————————————————————
Temperature  
  Analytical Column:      95 ºC  
  Detector (ECD):         300 ºC  
  Trap column:            -80 ºC (at adsorbing) & 170 ºC (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:      95 ºC 
  Detector (ECD):         240 ºC 
  Trap column:            -50 ºC (at adsorbing) & 140 ºC (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 gas  CFC-11  CFC-12  CFC113   SF6   N2O   remarks  
                         ppt     ppt     ppt     ppt   ppm  
———————————   ————————  ——————  ——————  ——————  —————  ————  ———————————
 CPB28497     N2          901    485     78.8   10.10  14.9  for SF6/CFC  
 CPB26840     N2          889    481     81.4    9.98  14.9  for SF6/CFC  
 CPB16993     N2          300    160     29.9    0.0    0.0  for CFC  
 CPB15651     N2          300    161     29.8    0.0    0.0  Reference  


3.6.4  Performance 

The analytical precisions are estimated from replicate sample analyses. The 
estimated preliminary precisions were ± 0.005 pmol/kg (n = 143), ± 0.007 pmol/kg 
(n = 143), ± 0.003 pmol/kg (n = 121), and ± 0.021 fmol/kg (n = 96) for CFC-11, 
CFC-12, CFC-113, and SF6, respectively. Analyses of N2O had serious problems 
probably caused by error of standard gas composition. Evaluating the standard 
gas composition, we may report the N2O data later (but as bad data). 


3.6.5  Data archive 

All data will be submitted to Data Management Group of JAMSTEC (DMG) and under 
its control.


 
3.7.  Carbon items 

(1) Personnel 

       Akihiko Murata (JAMSTEC) 
       Tomonori Watai (MWJ) 
       Makoto Takada (MWJ) 
       Atsushi Ono (MWJ) 
       Kanako Yoshida (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 eastern part of the Indian Ocean is one of the regions where uncertainty of 
uptake of anthropogenic CO2 is large. In this cruise, therefore, we were aimed 
at quantifying how much anthropogenic CO2 was absorbed in the ocean interior of 
the eastern part of the Indian Ocean. For the purpose, we measured CO2-system 
parameters such as dissolved inorganic carbon (CT), total alkalinity (AT) and pH 
along the WHP I10 in the region. 

(3) Apparatus 

i. CT 

Measurement of CT was made with a total CO2 measuring system (called as System 
D, Nippon ANS, Inc.). The system comprised of a seawater dispensing system, a 
CO2 extraction system and a coulometer. In this cruise, we used a coulometer 
Model 3000, which was constructed by Nippon ANS. The systems had a specification 
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 
       rate 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), 1.865 % 
CO2 gas in a nitrogen base, sea water samples (6) is programmed to repeat. The 
measurement of 1.865 % CO2 gas is made to monitor response of coulometer 
solutions purchased from UIC. 

ii. AT 

Measurement of AT was made based on spectrophotometry using a custom-made system 
(Nippon ANS, Inc.). The system comprises of a water dispensing unit, a HCl 
titration unit (Hamilton No.2), and a detection unit of a spectrophotometer (TM-
UV/VIS C10082CAH, Hamamatsu Photonics, Japan) and an optical source (Mikropack, 
Germany). The system was automatically controlled by a PC. The water dispensing 
unit had a water-jacketed pipette and a water-jacketed glass titration cell. 

A seawater of approx. 42 ml was transferred from a sample bottle (borosilicate 
glass bottle; 130 ml) into the water-jacketed (25 ºC) pipette by pressurizing 
the sample bottle (nitrogen gas), and was introduced into the water-jacketed (25 
ºC) glass titration cell. The introduced seawater was used to rinse the 
titration cell. After dumping the seawater used for rinse, Milli-Q water was 
introduced into the titration cell to rinse it. This is repeated twice. Next, a 
seawater of approx. 42 ml was weighted again by the pipette, and was transferred 
into the titration cell. Then, for seawater blank, absorbances were measured at 
three wavelengths (750, 616 and 444 nm). After the measurement, an acid titrant, 
which was a mixture of approx. 0.05 M HCl in 0.65 M NaCl and bromocresol green 
(BCG), was added into the titration cell. The volume of acid titrant solution 
was changed according to expected values of AT from approx. 2.2 ml to 2.0 ml. 
The seawater and acid titrant were mixed for 5 minutes by a stirring tip and 
bubbling by nitrogen gas in the titration cell. Then, absorbances at the three 
wavelengths were measured again. 

Calculation of AT was 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): 

             + 
   pH =-log[H ] = 4.2699 + 0.002578(35-S)+log((R-0.00131)/(2.3148-0.1299R)-
     T         T

       log(1-0.001005S), 


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


                 R = (A   -A   ) (A   -A   ) , 
                       616  750    444  750


where Ai is the absorbance at wavelength i nm. 

The HCl in the acid titrant was standardized on land. The concentrations of BCG 
were estimated to be approx. 2.0 × 10-6 M in the sample seawater, respectively. 

iii. pH 

Measurement of pH was made by a pH measuring system (Nippon ANS, Inc.). For the 
detection of pH, spectrophotometry was adopted. The system comprises of a water 
dispensing unit and a spectrophotometer (Bio 50 Scan, Varian). For an indicator, 
m-cresol purple (2 mM) was used. 

Seawater is transferred from borosilicate glass bottle (300 ml) to a sample cell 
in the spectrophotometer. The length and volume of the cell are 8 cm and 13 ml, 
respectively, and the sample cell is kept at 25.00 ± 0.05 ºC in a thermostated 
compartment. First, absorbance of seawater only is measured at three wavelengths 
(730, 578 and 434 nm). Then the indicator is injected and circulated for about 4 
minutes to mix the indicator and seawater sufficiently. After the pump is 
stopped, the absorbance of seawater + indicator is measured at the same 
wavelengths. The pH is calculated based on the following equation (Clayton and 
Byrne, 1993): 

                                  A / A  - 0.00691
                                   1   2
                pH = pK  + log ——————————————————————— ,
                       2       2.2220 - 0.1331(A / A )  
                                                1   2. 


where A1 and A2 indicate absorbance at 578 and 434 nm, respectively, and pK2 is 
calculated as a function of water temperature and salinity. 


(4) Results 

Cross sections of CT, pH, and AT along WOCE I10 line are illustrated in Figs. 
3.7.1, 3.7.2 and 3.7.3, respectively. 


Fig. 3.7.1: Distributions of CT along the I10 section. 
Fig. 3.7.2: Distributions of AT along the I10 section.
Fig. 3.7.3: Distributions of pH along the I10 section.


References 

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



3.8  Calcium and Total alkalinity 2 

Calcium 

(1) Personnel 

       Etsuro Ono (JAMSTEC) 

(2) Objectives 

According to the recent IPCC report, concentrations of CO2 in the atmosphere 
have increased by 40% since pre-industrial times, primarily from fossil fuel 
emissions and secondarily from net land use change. The ocean has absorbed about 
30% of the emitted anthropogenic carbon dioxide, causing ocean acidification. 
Ocean acidification is characterized by an increase of H+ (i.e., a decrease of 
pH) and a 
  
concurrent decrease of carbonate ion concentration (CO3^(2–)). The decrease of 
CO3^(2–) is unfavorable to marine calcifying organisms, which utilize CO3^(2-), 
together with Ca^(2+), to produce their calcium carbonate (CaCO(3)) shells and 
skeletons. To evaluate dissolution and precipitation of calcium carbonate, we 
measured directly the concentration of calcium in the sea water in the 
subtropical region of the eastern part of the Indian Ocean. 

(3) Apparatus 

Measurement of calcium was made by a modified Dissolved Oxygen Titrator DOT-01 
(Kimoto Electronic Co. Ltd.). Bandpass filter was replaced to f0=620nm. 

Added reagents are as follows. 

    NH3/NH4buffer: 0.4 mol/l NH4Cl/ 0.4 mol/l NH3 buffer 
    Masking agent: 0.05 mol/l 2,2’,2”-nitrotriethanol solution 
    Zincon solution: 
       0.004 mol/l Zincon, 0.0925g Zincon was dissolved 0.8 ml 1M NaOH and was 
       diluted to 50 ml 
   Zn/EGTA solution: 0.004 mol/l ZnSO4/ 0.004 mol/l EGTA 
   EGTA titrant: 0.02 mol/l EGTA 

The system comprises of a light source, photodiode detectors, auto-burette and 
control unit. Seawater of accurate 10ml was transferred from a sample bottle 
(60ml HDPE bottle) into 100 ml tall beaker by volumetric pipet. A magnetic 
stirrer bar was added into beaker. 1ml NH3/NH4buffer, 1ml masking agent, 1ml 
Zincon solution, 1ml Zn/EGTA solution and about 60ml H2O were added into the 
beaker. The seawater samples were titrated by the EGTA titrant. The EGTA titrant 
was calibrated by 1000mg/l Ca standard solution (produced by Wako Pure Chemical 
Industries, Ltd.). 

(4) Performances 

The system worked well no troubles. The repeatability was estimated to be 
0.0088±0.0080 (n=17 pairs) mmol kg-1. 


Fig.3.8.1: Vertical profiles of calcium. 



Total alkalinity 2 

(1) Personnel 

       Etsuro Ono (JAMSTEC) 

(2) Objectives 

Same as in “Carbon Items” 

(3)Apparatus 

Measurement of AT was made based on potentiometry with Total Alkalinity Titrator 
ATT-05 (Kimoto Electronic Co. Ltd.). The system comprises of an auto-burette, 
combination electrode (pHC2001-8 S/N:13242-F17, S/N:13282-F11, Radiometer 
analytical) and control unit. 

The in-house acid solution (approx.0.1 M HCl in 0.6 M NaCl) was prepared as a 
titrant in advance of cruise. 

(4)Analysis 

All measurements were carried out with open cell method. 

Open cell method 

Seawater of accurate 50ml was transferred from a sample bottle (glass bottle) 
into 100 ml tall beaker by volumetric pipet. A magnetic stirrer bar was added 
into beaker. The combination electrode and temperature sensor were immersed in 
sample. The seawater samples were titrated by the acid titrant. The acid titrant 
was calibrated by measuring Dickson’s CRM (Batch 149). First, the acid titrant 
was added until pH of sample under 3.8 and stirred for 300 seconds. Second, the 
acid titrant was added by 20 µl at intervals of 15 seconds until reaching pH of 
2.8. Values of AT were computed with a program incorporated in the equipment. 

The electrode of S/N:13242-17, at first, was used at station 06, 12, 16 and 24. 
However, S/N:13242.17 was replaced with S/N:13282-F11 after the measurements at 
station 24, because S/N:13242-17 showed such slow a response that some measured 
values were not computed accurate. The measurements worked well with S/N:13282-
F11 at station 28, 33, 36, 45 and 51. 



3.9.  Dissolved organic carbon and total dissolved nitrogen 

(1) Personnel  

    Masahito Shigemitsu  (JAMSTEC): Principal investigator  
    Chisato Yoshikawa    (JAMSTEC)  
    Masahide Wakita      (JAMSTEC)  
    Akihiko Murata       (JAMSTEC)  

(2) Objectives 

Dissolved organic carbon (DOC) and total dissolved nitrogen (TDN) are considered 
to be important reservoirs of carbon and nitrogen in the ocean. They can also be 
substrates for heterotrophic microbial communities and TDN can serve as a source 
of nitrogen to autotrophs in nitrogen-deficient regions. 

In this cruise, we aimed to gain insights into the amount of DOC and TDN 
transported via the Indonesian throughflow from the Pacific to the Indian ocean, 
and interactions between dissolved organic materials like DOC and TDN and 
heterotrophic micro-organisms in the Indian Ocean. 

(3) Material and methods 

Seawater samples were obtained from Niskin bottles on a CTD-rosette system. Each 
sample taken in the upper 500 m was filtered using a pre-combusted (450°C 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 or triplicates, and were immediately stored frozen 
until analysis. Other samples taken below 500 m were unfiltered and stored in 
the same way. 

In the analysis after the cruise, the frozen samples are thawed at room 
temperature, and acidified to pH < 2 with hydrochloric acid followed by being 
bubbled to remove dissolved inorganic carbon from the samples. Concentrations of 
DOC and TDN are, then, measured by using a total organic carbon analyzer 
equipped with a chemiluminescence detector unit (Shimadzu, Japan). 


(4) Data archives 

The data of DOC and TDN 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. 



3.10  Chlorophyll-a 

(1) Personnel 

       Kosei Sasaoka (JAMSTEC) 
       Keitaro Matsumoto (MWJ) 
       Misato Kuwahara (MWJ) 
       Masahiro Orui (MWJ) 
       Haruka Tamada (MWJ) 

(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 along the I10 section in the Eastern 
Indian 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 250 ml brown Nalgene bottles without head-
space. 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) (Fig. 3.10-1). To estimate the chlorophyll-a concentrations, 
we applied to the fluorometric “Non-acidification method” (Welschmeyer, 1994). 

(4) Results 

Cross section of chlorophyll-a concentrations along the I10 line during the 
cruise is shown in Fig. 3.10-2. To estimate the measurement precision, 48-pairs 
of replicate samples were obtained from hydrographic casts. All pairs of the 
replicate samples were collected in 250 ml bottles. Standard deviation 
calculated from 48-pairs of the replicate samples was 0.078 µg/L, although 
absolute difference values between 45-pairs of the replicate samples were 
smaller than 0.01 µg/L. 



(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 3.10-1: Relationships between pure chlorophyll-a concentrations and 
               fluorescence light intensity.

Figure 3.10-2: Cross section of chlorophyll-a concentrations along the I10-line 
               obtained from hydrographic casts. 



3.11  Absorption coefficients of particulate matter and colored dissolved 
      organic matter (CDOM) 

(1) Personnel 

    Kosei Sasaoka (JAMSTEC) 

(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 
I10 section in the Indian 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 along the I10 
section (Fig. 3.11-1, Table 3.11-1). 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(.) (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. 
3.11-1, Table 3.11-1). 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-2400 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 

Some examples of chl-a normalized specific absorption spectra (a*ph) were shown 
in Fig.3.11-2. Cross section of CDOM (as absorption coefficient at 325 nm, unit 
= m-1) along the I10 section were shown in Fig. 3.11-3. 

(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. 


Table 3.11-1: List of sampling stations for absorption coefficients of 
              phytoplankton (Ap) and CDOM during MR15-05. 

                                                                         Sampling depth (db)
                                                            ———————————————————————————————————————————————————
                  Time  Lati-    Longi-     Sampling  Cast  Particle           CDOM
Stn.  Date (UTC)  (UTC) tude     tude         type     No.  absorbance         absorbance
———  ——————————  —————  ———————  ————————  —————————— ————  —————————————————  ————————————————————————————————
 1   12/28/2015   0:12  24.78 S  112.77 E  CTD+Bucket  1    0, 10, 50, 71      0, 10, 50, 71
 2   12/28/2015   3:06  24.74 S  112.62 E  CTD+Bucket  1         none          93, 50, 10, 0
 3   12/28/2015   5:38  24.73 S  112.47 E  CTD+Bucket  1         none          138, 100, 50, 10, 0
 4   12/28/2015   8:08  24.70 S  112.31 E  CTD+Bucket  1         none          198, 100, 50, 10, 0
 6   12/28/2015  14:05  24.63 S  112.00 E  CTD+Bucket  1    0, 10, 50,  100    698, 570, 370, 280,
                                                                               200, 100, 50, 10, 0
10   12/29/2015  10:30  24.38 S  110.59 E  CTD+Bucket  3    0, 10, 50,  100    3210, 3000, 1000, 800, 600,
                                                                               400, 300, 200, 100, 50, 10, 0
14   12/30/2015  12:55  22.42 S  110.76 E  CTD+Bucket  1    0, 10, 50,  100    5135, 3080, 1070, 830, 630, 
                                                                               430, 330, 200, 100, 50, 10, 0
18   12/31/2015  13:33  20.48 S  110.92 E  CTD+Bucket  1    0, 10, 50,  100    3704, 2930, 970, 770, 570, 
                                                                               370, 280, 200, 100, 50, 10, 0
22   01/01/2016  12:50  18.53 S  111.09 E  CTD+Bucket  2    0, 10, 50,  100    4797, 3000, 1000, 800, 600, 
                                                                               400, 300, 200, 100, 50, 10, 0
28   01/03/2016   3:36  15.97 S  111.30 E  CTD+Bucket  3    0, 10, 50,  100    5235, 5000, 3000, 1000, 800, 600,
                                                                               400, 300, 200, 100, 50, 10, 0
31   01/04/2016   1:30  14.87 S  111.39 E  CTD+Bucket  1         none          5774, 5000, 3000, 1000, 600,
                                                                               400, 300, 200, 100, 50, 10, 0
37   01/05/2016  23:33  12.19 S  111.62 E  CTD+Bucket  4    0, 10, 50,  100    2800, 1000, 800, 600,
                                                                               400, 300, 200, 100, 50, 10, 0
41   01/06/2016  18:03  11.21 S  111.72 E  CTD+Bucket  1  0, 10, 50, Chl(max)  4246, 3080, 1070, 830, 630,
                                                             (71), 100         430, 330, 200, 100, Chl(max)
                                                                               (71), 50, 10, 0
45   01/07/2016  17:25  10.22 S  111.81 E  CTD+Bucket  1  0, 10, 50, Chl(max)  3648, 2930, 970, 770, 570, 
                                                             (65), 100         370, 280, 200, 100, Chl(max)
                                                                               (65), 50, 10, 0
50   01/08/2016  14:51   8.99 S  111.93 E  CTD+Bucket  1  0, 10, 50, Chl(max)  2005, 1070, 830, 630, 430
                                                            (63), 100          330, 200, 100, Chl(max)(63)
                                                                               50, 10, 0
52   01/08/2016  21:57   8.62 S  111.96 E  CTD+Bucket  1  0, 10, 50, Chl(max)  549, 400, 300, 200, 100,
                                                            (62), 100          Chl(max)(62), 50, 10, 0


Fig. 3.11-1: Location of sampling stations for absorption coefficients of 
             phytoplankton and CDOM along the I10 section in the Indian Ocean 
             during MR15-05.

Fig. 3.11-2: Examples of chlorophyll-specific phytoplankton absorption 
             coefficient spectra (a*ph(λ)) at 400-750 nm, (a) Stn.01, 
             (b) Stn.06, (c) Stn.28, (d) Stn.52. All spectra were normalized 
             to 0.0 at 750nm. 

Fig. 3.11-3: Contours showing distribution of CDOM (as absorption coefficient at 
             325 nm, unit = m-1) along the I10 section during MR15-05. 


3.12  Bio-sampling 

3.12.1  Vertical profiles of microbial abundance, activity and diversity in the 
        eastern Indian Ocean 

(1) Personnel 

       Taichi Yokokawa (JAMSTEC) 
       Michinari Sunamura (University of Tokyo) 
       Takuro Nunoura (JAMSTEC) 
       Hirai Miho (JAMSTEC) 
       Chisato Yoshikawa (JAMSTEC) 
       Kanta Chida (Rakuno Gakuen University) 

(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 matter. (Herndl and 
Reinthaler 2013; Yokokawa et al. 2013). Moreover, microbial diversity and 
biogeography in bathypelagic and abyssal ocean and its relationship with upper 
layers and deep-water circulation have also not been well studied (Nagata et al. 
2010). 

The objectives of this study, which analyze the water columns from sea surface 
to just above the bottom of the eastern Indian Ocean, were 1) to determine the 
abundance of microbes; 2) to study the heterotrophic production and chemo-
autotrophic 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, and the three BIO casts. Samples were 
fixed with glutaraldehyde (final concentration 1%) or mixed with Glycerol-EDTA, 
and frozen at -80°C. The abundance of microbes and viruses will be measured by a 
flow cytometry in both University of Tokyo (Sunamura) and JAMSTEC (Nunoura) 
after nucleic acid staining with SYBR-Green I. 

Prokaryotic activity measurements 

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 relative contribution of Archaea and Bacteria to total prokaryotic leucine 
incorporation was determined using antibiotics and an inhibitor; erythromycin 
(Sigma-Aldrich, final conc. 10 µg mL-1) for bacteria, diphtheria toxin (Sigma-
Aldrich, final conc. 10 µg mL-1) and N1-Guanyl-1,7-Diaminoheptane (GC7, 
BIOSEARCH TECHNOLOGIES, final conc. 0.2 mM) for archaea, and (2-(4-
carboxyphenyl)-4, 4,5,5-tetramethylimidazoline-1-oxyl-3-oxide) (carboxy-PTIO; 
Dojindo Molecular Technology, INC. final conc. 100 µM) for inhibiting ammonia-
oxidizing archaea (AOA). 

In the laboratory 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. 

DIC fixation was measured via the incorporation of 50 µCi of [14C]-bicarbonate 
(NEC086H, PerkinElmer) in 20 ml seawater samples. Triplicate samples and 
formaldehyde-fixed blanks were incubated in the dark at in situ temperature (± 
4°C) for 72 h. Incubations were terminated by adding formaldehyde (1% final 
concentration) to the samples. 

The relative contribution of Archaea, Bacteria and AOA to total prokaryotic DIC 
fixation was determined using erythromycin (Sigma-Aldrich, final conc. 10 µg mL-
1), GC7 (BIOSEARCH TECHNOLOGIES, final conc. 0.2 mM) and PTIO (Dojindo Molecular 
Technology, INC. final conc. 100 µM) as bacterial, archaeal and AOA inhibitors 
of protein synthesis, respectively, and compared with the DIC fixation in the 
control sample. 

In the laboratory, the samples will be filtered onto 0.2-µm polycarbonate 
filters. Subsequently, the filters are fumed with concentrated HCl for 12 h. The 
samples will be radioassayed with a liquid scintillation counter using Filter-
count (PerkinElmer) as scintillation cocktail. Quenching is corrected by 
external standard channel ratio. The disintegrations per minute (DPM) of the 
formaldehyde-killed blank is subtracted from the average DPM of the samples, and 
the resulting DPM is converted into bicarbonate incorporation rates. 
Samples for leucin incorporation activity measurements were taken at stations 1, 
6, 10, 14, 18, 22, 26, 31, 37 in the routine casts, and those for inorganic 
carbon fixation rates assessed at stations 10, 22, 37 in the routine casts. 


Microbial diversity 

Microbial cells in water samples were filtrated on cellulose acetate filter 
(0.2µm) and stored at -80C. 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 -80C for 
single cell genomic analyses. Samples for microbial diversity were taken at 
stations 1, 6, 10, 14, 18, 22, 26, 31,  and 37 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 

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 

Nagata T, Tamburini C, Aristegui J, Baltar F, Bochdansky AB, Fonda-Umani S, 
    Fukuda H, Gogou A, Hansell DA, Hansman RL, Herndl GJ, Panagiotopulos C, 
    Reinthaler T, Sohrin R, Verdugo P, Yamada N, Yamashita Y, Yokokawa T, 
    Bartlett DH (2010) Emerging concepts on microbial processes in the 
    bathypelagic ocean – ecology, biogeochemistry, and genomics. Deep-Sea 
    Research II 57:1519-1536 



3.12.2  Geochemistry and Microbiology: Nitrogen and carbon cycles in the eastern 


Indian Ocean 

(1) Personnel 

       Akiko Makabe (JAMSTEC) 
       Chisato Yoshikawa (JAMSTEC) 
       Kanta Chida (Rakuno Gakuen University) 
       Keisuke Koba (Tokyo University of Agriculture and Technology) 
       Miho Hirai (JAMSTEC) 
       Osamu Yoshida (Rakuno Gakuen University) 
       Shotoku Kotajima (Tokyo University of Agriculture and Technology) 
       Taichi Yokokawa (JAMSTEC) 
       Takuro Nunoura (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). 


Nitrogen cycle 

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. 2012). Therefore 
marine N2O production processes are poorly understood quantitatively. N2O 
isotopomers 14N15N16O 15N14N16O (oxygen isotope ratio (.18O), difference in 
abundance of and (SP), and average nitrogen isotope ratio (.15N)) 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., in press). In this study we conducted water sampling for 
isotope analysis of N2O and related substances (NO3, phytoplankton and 
Chlorophyll-a) and some key reaction rates (nitrification rates) at three MBC 
shallow stations (above 500 m). By using the results of isotope analysis we will 
apply the model to the Indian 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. 




Methane in ocean 

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 Eastern Indian 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 15 layers above 500 m and surface layer taken by plastic bucket at 
hydrographic stations as shown in Table 1. 


Table 1: Parameters and hydrographic station names for this study. 

Parameters                              Hydrographic stations 
——————————————————————————————————————  ——————————————————————————————————————————————
1. δ15N and δ18O of NO3-                1, 6, 10, 14, 18, 22, 26, 31, 37 
2. δ15N of Chlorophyll-a                10, 22, 37 
3. δ15N of Phytoplankton                10, 22, 37 
4. δ15N, SP and δ18O of dissolved N2O   1, 6, 10, 14, 18, 22, 26, 31, 37 
5. Nitrification rate                   1, 6, 10, 18, 22, 26, 31, 37
6. Dissolved CH4 and N2O concentration  1, 4, 6, 8, 10, 14, 18, 22, 26, 28, 31, 35, 37
7. F430                                 10, 22, 37 
8. δ13C of CH4                          1, 6, 10, 14, 18, 22, 26, 31, 37


Isotopic analyses for N2O, NO3-, chlorophyll-a and phytoplankton, and 
concentration analyses for N2O and CH4 

Sample for N2O isotopomer analysis was transferred to two of 100 ml glass vials. 
After an approximately two-fold volume overflow, 200µL 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 (PreCon/HP6890 GC/ MAT 252) at TIT described in detail in 
Yamagishi et al. (2007). 

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 light-blocking 
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 light-
blocking polypropylene tanks. The samples were condensed using an 
ultrafiltration system and sorted for phytoplankton samples using a cell sorter. 
The phytoplankton samples were filtered under reduced pressure and collected on 
pre-combusted Whatman GF-75 filters. The filters were stored at -23°C until 
analysis. The δ15N values of phytoplankton will be measured by using EA-IRMS at 
JAMSTEC. 

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. 

Nitrification activity measurements 

Water samples for nitrification activity analysis were transferred into 100 mL 
glass vials 15N without headspace. Combination of enriched substrates (ammonium, 
urea, and glutamine (amide group)) and inhibitors (carboxy-PTIO, allylthiourea, 
and GC7) were added to each vial. The final concentration of 15N enriched 
substrates was 50 nM. The glass vials were incubated in dark for 12 hours or 3 
days at in situ temperature. After incubation, the samples for nitrate analysis 
were filtered with a DISMIC® filter (pore size: 0.45 µm) and frozen until 
analysis. The samples for N2O analysis were added by 0.2 mL of saturated HgCl2 
solution and stored at 4 ºC until analysis. The 15N enrichment of nitrates will 
be measured by GC-IRMS after conversion to N2O using the “bacterial” method of 
Sigman et al. (2001). The 15N enrichment of N2O will be measured by GC-IRMS 
described in detail in Yamagishi et al. (2007). 

Nitrous oxide and methane concentration measurements 

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. 

Isotopic analysis of methane 

Water samples for δ13C-CH4 analysis were transferred to 100 mL glass vials from 
the Niskin sampler without headspace. After the vials were sealed with butyl 
rubber and aluminum caps, 200 µL of saturated HgCl2 solution was added. The 
water samples were stored until analysis on land. The δ13C value of Methane 
will be measured using isotope ratio mass spectrometry using a method of 
Tsunogai et al. (1998 and 2000). 

Biomarker of methanogens 

Water samples for F430 analysis (5 or 10 L) were filtered (0.01 MPa) with a 
Whatman GF-75 filter (47 mm in diameter). The filter samples were wrapped with 
aluminum foil and stored at .20°C prior to analysis on land. Extraction and 
analysis of F430 will be conducted at JAMSTEC using a method of Kaneko et al. 
(2014). 

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 

Nitrogen cycle and microbial carbon uptake associated with nitrogen cycle 

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 Indian Ocean. 

Methane 

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. 

A depth profile of F430 concentration in water column will provide information 
about δ13C quantitative distribution of methanogens. The value of methane 
reflects carbon source and methaogenic pathway (Whiticar, 1999). If the profile 
correlate with other chemical profiles including concentrations of methane, 
chlorophyll-and dissolved oxygen, it can be a strong evidence of that 
methanogens are source organisms for methane in the surface seawater. The .13C 
value of methane will support presence of methanogen and provide further 
constraints on methaongenic pathway, In addition with the vertical distribution, 
a lateral distribution (east-west) of F430 and other chemicals will provide 
insight into environmental factors controlling distribution of methanogens. 


References 

Alldredge AA, Cohen Y (1987) Can microscale chemical patches persist in the sea? 
    Microelectrode study of marine snow, fecal pellets. Science, 235:689-691 

Alonso-Sáez L, Galand PE, Casamayor EO, Pedrós-Alió C, Bertilsson S (2010) High 
    bicarbonate assimilation in the dark by Arctic bacteria. ISME J, 174:1581–90 

Anantharaman K, Breier JA, Sheik CS, Dick GJ (2013) Evidence for hydrogen 
    oxidation and metabolic plasticity in widespread deep-sea sulfur-oxidizing 
    bacteria. Proceedings of the National Academy of Sciences, 110:330–335 

Bange, HW, Bartell UH, Rapsomanikis S, Andreae MO (1994) Methane in the Baltic 
    and the North seas and a reassessment of the marine emissions of methane. 
    Global Biogeochemical Cycles, 8:465–480 

Cicerone RJ, Oremland RS (1988) Biogeochemical aspects of atmospheric methane, 
    Global Biogeochemical Cycles, 2:299–327 

Conrad R (2009) The global methane cycle: recent advances in understanding the 
    microbial processes involved. Environmental Microbiology Report, 1:285-292 

de Angelis MA, Lee C (1994) Methane production during zooplankton grazing on 
    marine phytoplankton. Limnology and Oceanography, 39:1298-1308 

Dore JE, Popp BN, Karl DM, Sansone FJ (1998) A large source of atmospheric 
    nitrous oxide from subtropical North Pacific surface water. Nature, 396:63-66 

Francis CA, Beman JM, Kuypers MM (2007) New processes and players in the 
    nitrogen cycle: the microbial ecology of anaerobic and archaeal ammonia 
    oxidation. ISME J 1: 19–27 

German CR. et al. (2010) Diverse styles of submarine venting on the ultraslow 
    spreading Mid-Cayman Rise. Proceedings of the National Academy of Sciences, 
    107:14020–14025. 

Granger J, Sigman DM (2009) Removal of nitrite with sulfamic acid for nitrate N 
    and O isotope analysis with the denitrifier method. Rapid Communications in 
    Mass Spectrometry, 23:3753-3762 

Grossart HP, Frindte K, Dziallas C, Eckert W, Tang WK (2011) Microbial methane 
    production in oxygenated water column of an oligotrophic lake. Proceedings 
    of the National Academy of Sciences, 108:19657-19661 

Herndl GJ, Reinthaler T (2013) Microbial control of the dark end of the 
    biological pump. Nature Geoscience, 6:718–724 

IPCC Working group I (2013): Climate change 2013: The physical science basis. 
    IPCC The 5th Assessment report, http://www.ipcc.ch/report/ar5/wg1/. 

Kaneko M, Takano Y, Chikaraishi Y, Ogawa ON, Asakawa S, Watanabe T, Shima S, 
    Krüger M, Matsushita M, Kimura H, Ohkouchi N (2014). Quantitative Analysis 
    of Coenzyme F430 in Environmental Samples: A New Diagnostic Tool for 
    Methanogenesis and Anaerobic Methane Oxidation. Analytical Chemistry, 
    86:3633-3638 

Karl DM, Tilbrook BD (1994) Production and transport of methane in oceanic 
    particulate organic matter. Nature, 368:732–734 

Karl DM, Beversdorf L, Björkman KM, Church MJ, Martinez A, DeLong EF (2008). 
    Aerobic production of methane in the sea. Nature Geoscience, 1:473-478 

Katz ME, Pak DK, Dickkens GR, Miller KG (1999) The source and fate of massive 
    carbon input during the latest Paleocene thermal maximum. Scince, 286:1531–
    1533 

Kawagucci S, Yoshida YT, Noguchi T, Honda MC, Uchida H, Ishibashi H, Nakagawa F, 
    Tsunogai U, Okamura K, Takaki Y, Nunoura T, Miyazaki J, Lin W, Kitazato H, 
    Takai K (2012) Disturbance of deep-sea environments induced by the M9.0 
    Tohoku Earthquake. Scientific Reports, 2:270. 

Knapp AN, Sigman DM, Lipschultz F (2005) N isotopic composition of dissolved 
    organic nitrogen and nitrate at the Bermuda Atlantic time-series study site. 
    Global Biogeochemical Cycles, 19:GB1018 

Knowles R, Lean DRS, Chan YK (1981) Nitrous oxide concentrations in lakes: 
    variations with depth and time. Limnology and Oceanography, 26:855-866 

Koba K, Inagaki K, Sasaki Y, Takebayashi Y, Yoh M (2010) Nitrogen isotopic 
    analysis of dissolved inorganic and organic nitrogen in soil extracts. 
    Earth, life, and isotopes, Kyoto University Press 

Lelieveld J, Crutzen PJ, Dentener FJ (1998) Changing concentration, lifetime and 
    climate forcing of atmospheric methane. Tellus Series B, 50:128–150 

Maribeb CG, Laura F (2004) N2O cycling at the core of the oxygen minimum zone 
    off northern Chile. Marine Ecology Progress Series, 280:1-11 

McIlvin MR, Altabet MA (2005) Chemical conversion of nitrate and nitrite to 
    nitrous oxide for nitrogen and oxygen isotopic analysis in freshwater and 
    seawater. Analytical Chemistry, 77:5589-5595 

Revilla M, Alexander J, Glibert PM (2005) Urea analysis in coastal waters: 
    comparison of enzymatic and direct methods. Limnology and Oceanography 
    Methods, 3:290-299 

Oudot C, Jean-Baptiste P, Fourre E, Mormiche Guevel C, Ternon JF-, Corre PL 
    (2002) Transatlantic equatorial distribution of nitrous oxide and methane. 
    Deep-Sea Research Part I, 49:1175–1193 

Owens NJP, Law CS, Mantoura RFC, Burkill PH, Llewellyn CA(1991) Methane flux to 
    the atmosphere from the Arabian Sea. Nature, 354:293–296 

Rysgaard S, Risgaard-Petersen N, Nielsen LP, Revsbech NP (1993) Nitrification 
    and denitrification in lake and estuarine sediments measured by the 15N 
    dilution technique and isotope pairing. Applied and Environmental 
    Microbiology, 59:2093-2098 

Sasakawa M, Tsunogai U, Kameyama S, Nakagawa F, Nojiri Y, Tsuda A (2008) Carbon 
    isotopic characterization for the origin of excess methane in subsurface 
    seawater. Journal of Geophysical Research, 113:C03012, doi: 
    10.1029/2007JC004217 

Santoro AE, Buchwald C, McIlvin MR, Casciotti KL (2011) Isotopic signature of 
    N2O produced by marine ammonia-oxidizing Archaea. Science, 333:1282-1285 

Scranton IM, Brewer GP (1977) Occurrence of Methane in near-Surface Waters of 
    Western Subtropical North-Atlantic. Deep-Sea Research, 24:127-138 

Sigman DM, Casciotti KL, Andreani M, Barford C, Galanter M, Boehlke JK (2001) A 
    bacterial method for the nitrogen isotopic analysis of nitrate in seawater 
    and freshwater. Analytical Chemistry, 73:4145-4153 

Stieglmeier M, Mooshammer M, Kitzler B, Wanek W, Zechmeister-Boltenstern S, 
    Richter A, Schleper C (2014) Aerobic nitrous oxide production through N-
    nitrosating hybrid formation in ammonia-oxidizing archaea. ISME J, 8:1135-
    1146 

Swan BK, Martinez-Garcia M, Preston CM, Sczyrba A, Woyke T, Lamy, D, Reinthaler 
    T, Poulton NJ, Masland ED, Gomez ML, Sieracki ME, DeLong EF, Herndl GJ, 
    Stepanauskas R (2011) Potential for chemolithoautotrophy among ubiquitous 
    bacteria lineages in the dark ocean. Science, 333:1296-1300 

Svensson JM (1998) Emission of N2O, nitrification and denitrification in a 
    eutrophic lake sediment bioturbated by Chironomus plumosus. Aquatic 
    Microbial Ecology, 14:289-299 

Tilbrook BD, Karl DM (1995) Methane sources, distributions and sinks from 
    California coastal waters to the oligotrophic North Pacific gyre. Marine 
    Chemistry, 49:51–64 

Tsunogai U, Ishibashi J, Wakita H, Gamo T (1998) Methane-rich plumes in the 
    Suruga Trough (Japan) and their carbon isotopic characterization. Earth and 
    Planetary Science Letters, 160:97-105 

Tsunogai U, Yoshida N, Ishibashi J, Gamo T (2000) Carbon isotopic distribution 
    of methane in deep-sea hydrothermal plume, Myojin Knoll Caldera, Izu-Bonin 
    arc: Implications for microbial methane oxidation in the oceans and 
    applications to heat flux estimation. Geochimca et Cosmochimca Acta, 
    64:2439-2452 

Ueda S, Ogura N, Yoshinari T (1993) Accumulation of nitrous oxide in aerobic 
    ground water. Water Research, 27:1787-1792 

Ward BB, Kilpatrick KA, Novelli PC, Scranton MI (1987) Methane oxidation and 
    methane fluxes in the ocean surface layer and deep anoxic waters. Nature, 
    327:226–229 

Watanabe S, Higashitani N, Tsurushima N, Tsunogai S (1995) Methane in the 
    western North Pacific. Journal of Oceanography, 51:39–60 

Whiticar MJ (1999) Carbon and hydrogen isotope systematics of bacterial 
    formation and oxidation of methane. Chemical Geology, 161:291-314 

Yamagishi H, Westley MB, Popp BN, Toyoda S, Yoshida N, Watanabe S, Koba K, 
    Yamanaka Y (2007) Role of nitrification and denitrification on the nitrous 
    oxide cycle in the eastern tropical North Pacific and Gulf of California. J. 
    Geophys. Res. Biogeosciences, doi:10.1029/2006JG000227 

Yoshida N, Toyoda S (2000) Constraining the atmospheric N2O budget from 
    intramolecular site preference in N2O isotopomers. Nature, 405:330-334 

Yoshida O, Inoue HY, Watanabe S, Noriki S, Wakatsuchi M (2004) Methane in the 
    western part of the Sea of Okhotsk in 1998-2000. Journal of Geophysical 
    Research, doi:10.1029/2003JC001910 

Yoshida O, Inoue HY, Watanabe S, Suzuki K, Noriki S (2011) Dissolved methane 
    distribution in the South Pacific and the Pacific Ocean in austral summer. 
    Journal of Geophysical. Research, doi:10.1029/2009JC006089 

Yoshikawa C, Abe H, Aita MN, Breider F, Kuzunuki K, Ogawa NO, Suga H, Ohkouchi 
    N, Danielache SO, Wakita M, Honda MC, Toyoda S, Yoshida N (in prep.) 
    Insights into the production processes of nitrous oxide in the western north 
    Pacific by using a marine ecosystem isotopomer model. 




3.13  Carbon isotopes 
                                                                January 27, 2016 
                                                               Yuichiro Kumamoto 
                  Japan Agency for Marine-Earth Science and Technology (JAMSTEC) 


(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 3.13.1. All 
samples for carbon isotope ratios (total 129 samples) were collected at 4 
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 • l 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 3.13.1: Sampling stations and number of samples for carbon isotope ratios. 

                                                     Number 
                                Sampling   Number      of        Max.
                                  Date       of     replicate  Pressure 
     Stn  Lat. (S)  Long. (E)    (UTC)     samples   samples    (dbar)  
     ———  ————————  —————————  ——————————  ———————  —————————  ————————
     016  21-27.10  110-50.56  2015/12/31    33         2        5132  
     021  19-00.91  111-03.03  2016/01/01    27         2        3565  
     028  15-58.13  111-18.37  2016/01/02    33         2        5220  
     036  12-41.24  111-35.04  2016/01/05    28         2        3898  
     Total  121  8  




3.14  Radioactive Cesium 

                                                                January 27, 2016 
                                                               Yuichiro Kumamoto 
                  Japan Agency for Marine-Earth Science and Technology (JAMSTEC) 


(1) Personnel 
    Yuichiro Kumamoto 
      Japan Agency for Marine-Earth Science and Technology 

(2) Objective 

In order to investigate water circulation and ventilation process in the eastern 
Indian Ocean, during MR15-05 cruise seawater samples were collected for 
measurements of radiocesium (Cs-134 and Cs-137), which were mainly released from 
the global fallout in the 1950s and 1960s and the Fukushima Daiichi nuclear 
power plant after its serious accident on the March 11 of 2011. 

(3) Sample collection 

The sampling stations and number of samples are summarized in Table 3.14.1. The 
total 126 of seawater samples for radioactive cesium were collected at 3 
stations. The seawaters were sampled vertically using 12-liter Niskin-X bottles. 
Surface seawater were collected from pumping-up water from the bottom of the 
ship. The seawater sample for radiocesium was collected into a 20-L plastic 
container and after two time washing. Immediately after sampling, the seawater 
was acidified by adding of 40-cm3 of concentrated nitric acid (85%, Wako Pure 
Chemical Industries, Ltd., Lot SAL6324) on board. 

(4) Sample preparation and measurements 

In our laboratory on shore, radiocesium in the seawater samples will be 
concentrated using ammonium phosphomolybdate (AMP) that forms insoluble compound 
with cesium. The radiocesium in AMP will be measured using Ge γ-ray 
spectrometer. 


Table 3.14.1: Sampling stations and number of samples for radiocesium 

                                               No. of
                                  Sampling     samples      Max.
                                    Date         for      Pressure
       Stn  Lat. (S)  Long. (E)    (UTC)     radiocesium   (dbar) 
       ———  ————————  —————————  ——————————  ———————————  ————————
       028  15-58.20  111-18.25  2016/01/03      42         802  
       033  14-08.52  111-27.52  2016/01/04      42         773  
       037  12-11.71  111-37.40  2016/01/05      42         803  
                                      Total     126  




3.15  Stable Isotopes of Water 
      January 27, 2016 

(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 were stored at room temperature. A total of 620 samples was collected 
including 37 pairs of replicate samples, except in the Exclusive Economic Zone 
(EEZ) of Indonesia. 




3.16.  Primary productivity 

(1) Personnel 
    Kazuhiko Matsumoto (JAMSTEC) on board (Leg 1) 
    Yugo Kanaya (JAMSTEC) not on board 
    Fumikazu Taketani (JAMSTEC) not on board 
    Takuma Miyakawa (JAMSTEC) not on board 
    Hisahiro Takashima (JAMSTEC) not on board 
    Yuichi Komazaki (JAMSTEC) not on board 
    Hitoshi Matsui (JAMSTEC) not on board 

(2) Objectives 

The major objective is to investigate processes of biogeochemical cycles between 
the atmosphere and the ocean. We investigate the oceanic primary productivity to 
estimate the effect of atmospheric input of nutrients into the ocean. Primary 
productivity is estimated based on the incorporation of 13C-labeled inorganic 
carbon into phytoplankton biomass via the photosynthesis. Particularly, to 
characterize the optimal productivity in response to light, we investigate the 
relationship between phytoplankton photosynthetic rate (P) and scalar irradiance 
(E) with the experiments of P vs. E curve. 

(3) Methods and Instruments 

i. Sampling 

Seawater samples were collected using Teflon-coated and acid-cleaned Niskin 
bottles, except for the surface water, which was taken by a bucket. Samplings 
were conducted at three depths within the euphotic depth, and at five locations 
(Stations: 001, 012, 022, 030, 037). Seawater samples were transferred to acid-
cleaned, transparent bottles (approx. 1 liter) before the incubation. When the 
sampling had been conducted during night, seawater samples were stored 
temporarily at a temperature of that depth in dark until the incubation 
experiments. 

ii. Incubation 

Just before the incubation, NaH13CO3 was added to each bottle at a final 
concentration of 0.2 mM, sufficient to enrich the bicarbonate concentration by 
about 10%. Incubators were filled with water, and water temperature was 
controlled appropriately by a circulating water cooler, respectively (Fig. 
3.16). Each incubator was illuminated at one end by a 500W halogen lamp, and 
bottles were arranged linearly against the lamp and controlled light intensity 
by shielding with a neutral density filter on lamp side (Table 3.16). 
Incubations for the P vs. E curve experiment were conducted around noon for 3-h. 
In addition, another incubation experiments were conducted to the surface sample 
for 24-h from the early morning to estimate the incorporation of carbon and 
nitrate in a day with adding NaH13CO3 and K15NO3 in the on-deck bath with 
running surface seawater. 

iii. Measurement 

After the incubation, water samples were immediately filtered through a pre-
combusted GF/F filter, then the filters were kept in a deep-freezer (-80 ºC). 
Inorganic carbon in the filter will be removed by fuming HCl before the 
analysis, and the 15N and 13C content of the particulate fraction will be 
measured with an automatic nitrogen and carbon analyzer mass spectrometer 
(Sercon, Ltd.) at the laboratory based on the method of Hama et al. (1983). 

The analytical function and parameter values used to describe the relationship 
between the photosynthetic rate (P) and scalar irradiance (E) are best 
determined using a least-squares procedure from the following equation (Platt et 
al., 1980). 
                                 -αE/Pmax  -bαE/Pmax
                     P = P   (1-e         )e 
                          max

where, Pmax is the light-saturated photosynthetic rate, α is the initial slope 
of the P vs. E curve, b is a dimensionless photoinhibition parameter. 

Measurements with a high-performance liquid chromatography (Agilent Technologies 
Inc.) and a flow cytometer (Sony Biotechnology Inc.) are scheduled to estimate 
phytoplankton composition and abundance of the samples conducted the P vs. E 
curve experiments. 

(4) Preliminary results 

N/A (Data analysis is to be conducted.) 

(5) 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 

(6) References 

Platt T, Gallegos CL, Harrison WG (1980) Photoinhibition of photosynthesis in 
    natural assemblages of marine phytoplankton. Journal of Marine Research 38: 
    687-701. 

Hama T, Miyazaki T, Ogawa Y, Iwakuma T, Takahashi M, Otsuki A, Ichimura S (1983) 
    Measurement of photosynthetic production of a marine phytoplankton 
    population using a stable 13C isotope. Marine Biology 73: 31-36. 


Fig. 3.16: Look down view of incubator for the P vs. E curve experiment



Table 3.16: Light intensity of each bottle in the incubators 

                        A                B                C  
              Bottle  ————             ————             ————
                No.   Light intensity (µmol quanta m-2 sec-1)  
              ——————  ———————————————————————————————————————
                 1    2400             1600             2000  
                 2    1500             1000             1350  
                 3     820              530              720  
                 4     440              280              360  
                 5     210              150              190  
                 6     105               80               96  
                 7      54               40               47  
                 8      25.5             20               23  
                 9       0                0                0  




3.17  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(CPU firmware ver. 50.40) 

(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. 




3.18  XCTD 
      February 1, 2016 

(1) Personnel 

      Hiroshi Uchida (JAMSTEC) 
      Katsuro Katsumata (JAMSTEC) 
      Fadli Syamsudin (BPPT) 
      Wataru Tokunaga (GODI) 
      Yutaro Murakami (GODI) 
      Tetsuya Kai (GODI) 
      Ryo Kimura (MIRAI crew) 

(2) Objectives 

XCTD (eXpendable Conductivity, Temperature and Depth profiler) measurements were 
carried out to examine a hydrographic structure along south coast of Java Island 
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-2 (Tsurumi-Seiki Co., Ltd., Yokohama, Kanagawa, Japan), 
except for XCTD-1 (Tsurumi-Seiki Co., Ltd.) at station I10_0, with an MK-150N 
deck unit (Tsurumi-Seiki Co., Ltd.). The manufacturer’s specifications are 
listed in Table 3.18.1. In this cruise, the XCTD probes were deployed by using 
8-loading automatic launcher (Tsurumi-Seiki Co., Ltd.). For comparison with CTD, 
XCTD was deployed at about 10 minutes after the beginning of the down cast of 
the CTD (I10_44, 45, 46, 48, 49 and 50). For correction of the sound velocity 
profile used in the bathymetry observation, XCTD-1 was deployed near station 
I10_1. 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 3.18.2). (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. 
3.18.1. The terminal velocity error was estimated for the XCTD-2 (Table 3.18.2). 
The XCTD-2 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. 3.18.3). Average thermal 
bias below 900 dbar was – 0.003 °C. The XCTD data were corrected for the thermal 
bias. Differences of salinity on reference temperature surfaces were examined by 
using CTD data (Fig. 3.18.4). 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. 3.18.3. Potential temperature cross section is shown in Fig. 3.18.4. 

(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 (in prep.) 


Table 3.18.1: Manufacturer’s specifications of XCTD-2. 

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

Model   a (terminal velocity, m/s)  b (acceleration, m/s2)  e (terminal velocity 
                                                              error, m/s) 
——————  ——————————————————————————  ——————————————————————  ————————————————————
XCTD-4  3.43898                     0.00031                 –0.0198 


Table 3.18.3: 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  This report 
——————————————————————————————————————————————————————————————————————
Mean 0.011 ± 0.008 


Table 3.18.4: Salinity biases of the XCTD data. 

                         Reference              
      XCTD    Salinity  temperature  Reference     Reference 
     station    bias       (°C)      salinity     CTD stations 
     ———————  ————————  ———————————  —————————  —————————————————
        44     –0.008      3.0        34.7209   44,45,46,48,49,50 
        45     –0.003      3.0        34.7209   44,45,46,48,49,50 
        46     –0.022      3.0        34.7209   44,45,46,48,49,50 
        48     –0.016      3.0        34.7209   44,45,46,48,49,50 
        49     –0.015      3.0        34.7209   44,45,46,48,49,50 
        50     –0.010      3.0        34.7209   44,45,46,48,49,50 
       901     –0.035      6.0        34.6558   51 
       902     –0.034      4.2        34.6532   44,45,46,48,49,50 
       903     –0.023      4.2        34.6532   44,45,46,48,49,50 
       904     –0.040      3.0        34.7209   44,45,46,48,49,50 
       905     –0.034      3.0        34.7209   44,45,46,48,49,50 
       906     –0.035      3.0        34.7209   44,45,46,48,49,50 
       907     –0.033      3.0        34.7209   44,45,46,48,49,50 
       908     –0.030      3.0        34.7209   44,45,46,48,49,50 
       909     –0.042      3.0        34.7209   44,45,46,48,49,50 
       910     –0.022      3.0        34.7209   44,45,46,48,49,50 
       911     –0.022      3.0        34.7209   44,45,46,48,49,50 
       912     –0.037      3.0        34.7209   44,45,46,48,49,50 
       913     –0.035      4.2        34.6532   44,45,46,48,49,50 


Figure 3.18.1: Differences between XCTD and CTD depths for XCTD-2. 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 3.18.2: 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 3.18.3: 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).

Figure 3.18.4: Potential temperature (°C) section along south coast of Java 
               Island.




3.19  Micro Rider 

(1) Personnel 
    Shinya Kouketsu (JAMSTEC) 
    Hiroshi Uchida (JAMSTEC) 
    Katsurou Katsumata (JAMSTEC) 
    Ichiro Yasuda (AORI) 

(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, as the probes didn’t work well. 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. During this cruise, as we attached a bottom contact detector 
in some casts (Stations 001, 002, and 013), the string and weight with the 
detector may affect the microstructure measurements. 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 

    Station 001-030: T1111 and T1112 
    Station 031-052: T1114 and T1115 



4.  Floats, Drifters, and Moorings 

4.1  Argo floats  

(1) Personnel  

       Katsuro Katsumata  (JAMSTEC)  
       Ann Thresher       (CSIRO) not onboard  
       Mizue Hirano       (JAMSTEC) not onboard  
       Shungo Oshitani    (MWJ) Technical Staff  
       Shinsuke Toyoda    (MWJ) Technical Staff  

(2) Objectives 

Now Argo floats are one of the core components of the Global Ocean Observing 
System http://www.ioc-goos.org/). The data from these floats are indispensable 
for both operational and scientific purposes. We contribute to the maintenance 
of this system by deploying new floats. 

(3) Deployments 

The floats usually drift at a depth of 1000 dbar (called the parking depth), 
diving to a depth of 2000 dbar and rising up to the sea surface by decreasing 
and increasing their volume and thus changing the buoyancy in ten-day cycles. 
During the ascent, they measure temperature, salinity, and pressure. They stay 
at the sea surface, transmitting the CTD data to the land and then return to the 
parking depth by decreasing volume. These floats measure temperature, salinity, 
and pressure. Detail of deployments is shown in Table 4.1.1. 


Table 4.1.1: Argo floats 

                                                         Water  Serial 
                                            CTD station  Depth  Number 
Time                Location               if available   (m)   (Hull)  WMO ID  
——————————————————  —————————————————————  ————————————  —————  ——————  ———————
24 Dec 2015, 00:34   8-14.84S, 105-31.45E       -        3410   7435    5905006  
24 Dec 2015, 07:36   9-29.74S, 106-2.96E        -        6258   7426    5905007  
24 Dec 2015, 15:33  10-45.06S, 106-35.02E       -        5855   6542    5905008  
25 Dec 2015, 04:38  12-30.15S, 107-20.25E   Station 900  4668   7041    5905009  
25 Dec 2015, 14:13  14-15.04S, 108-5.04E        -        5331   7042    5905010  
31 Dec 2015, 15:18  20-28.37S, 110-55.37E   Station 18   3673   7040    5905011  
 1 Jan 2016, 14:57  18-31.68S, 110-5.57E    Station 22   4737   7039    5905012  
 2 Jan 2016, 21:36  16-19.92S, 111-16.59E   Station 27   5186   7430    5905013  
 4 Jan 2016, 04:04  14-52.02S, 111-23.75E   Station 31   5682   7431    5905014  
 4 Jan 2016, 19:25  14-8.15S,  111-35.04E   Station 33   5650   7429    5905015  
 5 Jan 2016, 14:13  12-41.08S, 111-27.15E   Station 36   3868   7428    5905016  
 7 Jan 2016, 01:56  10-57.86S, 111-44.82E   Station 42   4606   7432    5905017  
 7 Jan 2016, 23:40  10-2.72S,  111-49.84E   Station 46   2122   7427    5905018  
 8 Jan 2016, 12:00   9-14.05S, 111-54.13E   Station 49   3045   7434    5905019  
10 Jan 2016, 00:55   9-9.68S,  113-49.97E       -        2232   7425    5905020  
10 Jan 2016, 21:55   9-9.91S,  115-14.77E       -        3095   7433    5905021  

                                   Leg 2  

19 Jan 2016, 23:03  21-59.84N, 134-59.91E       -        5462   OIN     5901937  
                                                                11JAP-
                                                                ARI-01


Sixteen floats (Teledyne Webb Research) deployed during Leg 1 were purchased by 
Marine and Atmospheric Research CSIRO, transported by air from Australia to 
Japan, and loaded to R/V Mirai at Hachinohe on 6 Nov 2015. Before loading, all 
floats went through pre-deployment tests. These floats were deployed from the 
stern of the vessel using the harness-and-cardboard deployment system. After 
deployment, water pressure triggers internal electrical switch of the floats. 
The trigger of the deployment system for two floats (S/N 7040 and 7429) failed 
so that these floats were deployed using traditional snap-ring shackle. At CTD 
stations, floats were deployed just after the CTD/sampler system is recovered on 
deck. 

The float deployed during Leg 2 (Arvor –I, nke Instrumentation) was purchased by 
JAMSTEC. The float was activated using magnetic switch and deployed from the 
stern using snap-ring shackle. 


(4) Data archive 

The real-time data are provided to meteorological organizations, research 
institutes, and universities via Global Data Assembly Center (GDAC: 
http://www.usgodae.org/argo/argo.html, http://www.coriolis.eu.org/) and Global 
Telecommunication System (GTS), and utilized for analysis and forecasts of sea 
conditions. 




III. Notice on Using 

This cruise report is a preliminary documentation as of the end of the cruise. 

This report may not be corrected even if changes on contents (i.e. taxonomic 
classifications) may be found after its publication. This report may also be 
changed without notice. Data on the cruise report may be raw or unprocessed. If 
you are going to use or refer to the data written on this report, please ask the 
Chief Scientist for latest information. 

Users of data or results on this cruise report are requested to submit their 
results to the Data Management Group of JAMSTEC. 





CCHDO Data Processing Notes 

• File Merge SEE 
49NZ20151223_ct1.zip (download) #48021 
Date: 2016-03-22 
Current Status: merged 


• CTD exchange and netcdf formats online SEE 
Date: 2016-03-22 
Data Type: CTD 
Action: Website Update 
Note: 
I10 2015 49NZ20151223 processing -CTD/merge 
.CTDPRS,CTDTMP,CTDSAL,CTDOXY,FLUOR,XMISS,XMISSCP,PAR,CDOMF 
2016-03-22 
SEE 
Submission 
filename             submitted by   date       id 
-------------------- -------------- ---------- -----
49NZ20151223_ct1.zip Hiroshi Uchida 2016-03-09 12147 

Changes
-------
49NZ20151223_ct1.zip
    -Copied XMISS_FLAG_W to XMISSCP_FLAG_W
    -added UNITS comments 
    -renamed header from SECT to SECT_ID, value remained unchanged
    -renamed parameter from CDOM to CDOMF
    -renamed ct1.csv files to preferred exchange format 

Conversion 
----------
file                    converted from       software 
----------------------- -------------------- -----------------------
49NZ20151223_nc_ctd.zip 49NZ20151223_ct1.zip hydro 0.8.2-47-g3c55cd3 

Updated Files Manifest
----------------------
file                    stamp 
----------------------- -----------------
49NZ20151223_ct1.zip    20160322CCHSIOSEE 
49NZ20151223_nc_ctd.zip 20160322CCHSIOSEE 

:Updated parameters: CTDPRS,CTDTMP,CTDSAL,CTDOXY,FLUOR,XMISS,XMISSCP,PAR,CDOMF 

opened in JOA with no apparent problems:
     49NZ20151223_ct1.zip
     49NZ20151223_nc_ctd.zip 

opened in ODV with no apparent problems:
     49NZ20151223_ct1.zip 


• File Online Carolina Berys 

49NZ20151223_sum.txt (download) #4dcd2 
Date: 2016-03-16 
Current Status: unprocessed 


• File Online Carolina Berys 
49NZ20151223_ct1.zip (download) #48021 
Date: 2016-03-16 
Current Status: merged 


• File Submission Hiroshi Uchida 
49NZ20151223_sum.txt (download) #4dcd2 
Date: 2016-03-09 
Current Status: unprocessed 
Notes 
WHP I10 


• File Submission Hiroshi Uchida 
49NZ20151223_ct1.zip (download) #48021 
Date: 2016-03-09 
Current Status: merged 
Notes 
WHP I10