CRUISE REPORT: P01/P10 (Updated FEB 2019) Highlights Cruise Summary Information Leg 1 Leg 2 Section Designation P10 P01 Expedition designation 49NZ20140709 49NZ20140717 Chief Scientists Hiroshi Uchida / JAMSTEC Dates 2014 JUL 09 – 2014 JUL 15 2014 JUL 17 – 2014 AUG 29 Ship R/V Mirai Ports of call Yokosuka, Japan – Kushiro, Japan – Kushiro, Japan Dutch Harbor, USA 50°N Geographic Boundaries 143.E 125.W 30°N Stations 121 stations for CTD/Carousel Water Sampler (Leg 1: 5, Leg 2: 116) 30 stations for XCTD 19 stations for radiosonde and 4 stations for HYVIS 2 stations for ORI net and 10 stations for NORPAC net Floats and drifters 6 Argo floats (2 S2A floats with RINKO oxygen sensor; deployed 4 NAVIS floats) Moorings deployed or 0 recovered Contact Information: Hiroshi Uchida Research and Development Center for Global Change (RCGC) Japan Agency for Marine-Earth Science and Technology (JAMSTEC) 2-15 Natsushima • Yokosuka, Kanagawa • Japan • 237-0061 Tel: +81-46-867-9474 • Fax: +81-46-867-9835 • email: huchida@jamstec.go.jp Final Report Assembly by Jerry Kappa, SIO/UCSD WHP P01 REVISIT IN 2014 DATA BOOK Edited by Hiroshi Uchida (JAMSTEC), Toshimasa Doi (JAMSTEC) WHP P01 REVISIT in 2014 Towards a Sustained Global Survey of the Ocean Interior WHP P01 REVISIT IN 2014 DATA BOOK March 24, 2017 Published Edited by Hiroshi Uchida (JAMSTEC) and Toshimasa Doi (JAMSTEC) Published by © JAMSTEC, Yokosuka, Kanagawa, 2017 Japan Agency for Marine-Earth Science and Technology 2-15 Natsushima, Yokosuka, Kanagawa. 237-0061, Japan Phone +81-46-867-9474, Fax +81-46-867-9835 ISBN 978–4–901833–22–6 Printed by Aiwa Enterprise, Ltd. 3-22-4 Takanawa, Minato-ku, Tokyo 108-0074, Japan Contents Contents ……………………………………………………………………………………………………………………………………………………………………………… 4 Preface ………………………………………………………………………………………………………………………………………………………………………………… 5 H. Uchida (JAMSTEC) Documents and station summary files 1 Cruise Narrative ……………………………………………………………………………………………………………………………………………… 6 H. Uchida (JAMSTEC) 2 Underway Measurements 2.1 Navigation ………………………………………………………………………………………………………………………………………………… 13 H. Uchida (JAMSTEC), R. Oyama (GODI) et al. 2.2 Swath Bathymetry ………………………………………………………………………………………………………………………………… 14 T. Matsumoto (Univ. Ryukyus), R. Oyama (GODI) et al. 2.3 Surface Meteorological Observations ……………………………………………………………………………… 16 M. Katsumata (JAMSTEC), R. Oyama (GODI) et al. 2.4 Thermo-Salinograph and Related Measurements ………………………………………………………… 20 H. Uchida (JAMSTEC) et al. 2.5 Underway pCO2 ………………………………………………………………………………………………………………………………………… 23 A. Murata (JAMSTEC) et al. 2.6 Shipboard ADCP ……………………………………………………………………………………………………………………………………… 25 S. Kouketsu (JAMSTEC) et al. 2.7 XCTD ………………………………………………………………………………………………………………………………………………………………… 28 H. Uchida (JAMSTEC) et al. 3 Hydrographic Measurement Techniques and Calibrations 3.1 CTDO2 Measurements …………………………………………………………………………………………………………………………… 31 H. Uchida (JAMSTEC) et al. 3.2 Bottle Salinity …………………………………………………………………………………………………………………………………… 49 H. Uchida (JAMSTEC) et al. 3.3 Density ………………………………………………………………………………………………………………………………………………………… 51 H. Uchida (JAMSTEC) 3.4 Oxygen …………………………………………………………………………………………………………………………………………………………… 54 Y. Kumamoto (JAMSTEC) et al. 3.5 Nutrients …………………………………………………………………………………………………………………………………………………… 60 M. Aoyama (Fukushima Univ./JAMSTEC) et al. 3.6 Carbon Items (CT, AT and pH) ………………………………………………………………………………………………… 74 A. Murata (JAMSTEC) et al. 3.7 Chlorophyll a ………………………………………………………………………………………………………………………………………… 80 K. Sasaoka (JAMSTEC) et al. 3.8 Absorption Coefficients of Particulate Matter and Colored Dissolved Organic Matter (CDOM) …………………………………………………………………… 81 K. Sasaoka (JAMSTEC) 3.9 Calcium ………………………………………………………………………………………………………………………………………………………… 85 Y. Shinoda (JAMSTEC) 3.10 Dissolved Organic Carbon …………………………………………………………………………………………………………… 86 T. Yoshimura (CRIEPI), D. A. Hansell and A. Margolin (Univ. of Miami) 3.11 Lowered Acoustic Doppler Current Profiler (LADCP) ………………………………………… 88 S. Kouketsu and H. Uchida (JAMSTEC) Station Summary (see cchdo.ucsd.edu) 49NZ20140709 .sum file 49NZ20140717 .sum file Figures (see pdf version) Figure captions ………………………………………………………………………………………………………………………………………………… 92 Preface In the 18 years since Japan Agency for Marine-Earth Science and Technology (JAMSTEC) conducted a repeat hydrography observation along the World Ocean Circulation Experiment (WOCE) Hydrographic Program (WHP) line P01 in 1999, JAMSTEC revisited 17 WHP lines (P01 in 1999, P17N in 2001, P06, A10, I04 in 2003, I03 in 2004, P10, P03 in 2005, P01, P14 in 2007, P21 in 2009, P10 in 2011, P14S in 2012, S04I in 2013, P01 in 2014, I10 in 2015, and P17E in 2017) in the Pacific Ocean, Atlantic Ocean, Indian Ocean, and Southern Ocean. The trans-Pacific section along 47ºN reported in this data book is forth section for WHP P01 in recent 30 years from the original section conducted by the United States of America in 1985. From the results in 1985 and 1999, large-scale bottom water warming was revealed (Fukasawa et al., 2004, doi:10.1038/nature02337). From the results in 2007, it was found that such large-scale bottom water warming continued after 1999 (Kawano et al., 2010, doi:10.1016/j.dsr2.2009.12.003). After these discoveries, bottom water warming was clarified around the world ocean and reported in the fifth assessment report of the Intergovernmental Panel on Climate Change (IPCC) (Rhein et al., 2013). In recent repeat hydrography observations, measurement uncertainty is greatly reduced. For example, for temperature measurement, it was found that the in- situ reference thermometers have no pressure dependency and the overall expanded uncertainty of the deep ocean temperature measurement is estimated to be 0.7 mK (Uchida et al., 2015, doi:10.1175/JTECH-D-15-0013.1). Also, for nutrients measurement, Reference Materials for Nutrients in Seawater (RMNS) has developed and used globally to improve the comparability of nutrients data (Aoyama et al., Analytical Sciences, 28 (9), 911, 2012). These highly quality controlled data enable us to evaluate long-term changes in not only temperature but also dissolved materials in the ocean. In the deep North Pacific, however, long-term change in salinity associated with the bottom water warming might be too small (an order of 0.0001 g/kg) to detect by the current measurement technology (a resolution of AUTOSAL salinometer is 0.0002 g/kg and uncertainty of the certified value of the IAPSO Standard Seawater might be ±0.001 g/kg [Kawano et al., 2006, doi:10.1007/s10872-006-0097-8; Table A1 of this data book]). Also, some parameters (such as dissolved oxygen and pH) require standard materials to improve the comparability. In the repeat hydrography observation, we should try to keep highest level of measurement technology, as well as to develop more accurate measuring devices and standards. You may find the contents of this data book, and links to other WHP revisit data books, on the website http:// www.jamstec.go.jp/iorgc/ocorp/data/post- woce.html. Updates and corrections will be found online. I would like to acknowledge the dedication and passion that Drs. Takeshi Kawano and Masao Fukasawa have shown in leading Japanese repeat hydrography, and congratulate them for producing such a significant contribution to GO- SHIP activities. I am sure that JAMSTEC’s repeat hydrography data will be used as reference data in a world ocean database. At Screaming Sixties in the Middle of WHP P17E Revisit (February 2017) Hiroshi Uchida Global Chemical and Physical Oceanography Group, JAMSTEC 1 Cruise Narrative September 28, 2014 Hiroshi Uchida (JAMSTEC) 1.1 Highlights WOCE Section Designation: P10N, P01 Cruise code: MR14-04 Expedition Designation: Leg 1: 49NZ20140709 Leg 2: 49NZ20140717 Chief Scientist and Affiliation: Hiroshi Uchida huchida@jamstec.go.jp Research and Development Center for Global Change (RCGC) Japan Agency for Marine-Earth Science and Technology (JAMSTEC) 2-15 Natsushima, Yokosuka, Kanagawa, Japan 237-0061 Tel: +81-46-867-9474, Fax: +81-46-867-9835 Ship: R/V Mirai Ports of call: Leg 1: Yokosuka, Japan – Kushiro, Japan Leg 2: Kushiro, Japan – Dutch Harbor, USA Cruise Dates: Leg 1: July 9, 2014 – July 15, 2014 Leg 2: July 17, 2014 – August 29, 2014 Number of Stations: 121 stations for CTD/Carousel Water Sampler (Leg 1: 5, Leg 2: 116) 30 stations for XCTD 19 stations for radiosonde and 4 stations for HYVIS 2 stations for ORI net and 10 stations for NORPAC net Geographic Boundaries (for hydrographic stations): 30.N – 50.N 143.E – 125.W Floats and Drifters Deployed: 6 Argo floats (2 S2A floats with RINKO oxygen sensor and 4 NAVIS floats) Mooring Deployed or Recovered Mooring: None 1.2 Cruise Summary It is well known that the oceans play a central role in determining global climate. However heat and material transports in the ocean and their temporal changes have not yet been sufficiently quantified. Therefore, global climate change is not understood satisfactorily. The main purposes of this research are to evaluate heat and material transports such as anthropogenic CO2, nutrients, etc. in the Pacific Ocean and to detect their long-term changes and basin-scale biogeochemical changes since the 1990s. This cruise is a reoccupation of the hydrographic sections called WHP-P10N along 149.E and WHP-P01 along 47.N of the North Pacific (Fig. 1.1.1). The WHP-P10N section was previously observed by the Japan Agency for Marine-Earth Science and Technology (JAMSTEC) in 2005 (Kawano and Uchida, 2007), in 2011 (Uchida et al., 2014), and in 2014 by the Japan Meteorological Agency. The WHP-P01 section was previously observed in 1985 by the Scripps Institution of Oceanography (USA), in 1999 by the Japan Fisheries Agency / the JAMSTEC / the Institute of Ocean Sciences (Canada) (Uchida et al., 2002), and in 2007 by the JAMSTEC (Kawano et al., 2009). This study was conducted under the Global Ocean Ship-based Hydrographic Investigations Program (abbreviated as GO-SHIP, http://www.go-ship.org/). Data obtained from those cruises are available from the CLIVAR & Carbon Hydrographic Data Office (CCHDO) web site (http://cchdo.ucsd.edu). In leg 1 of this cruise, we conducted CTD and discrete water sampling at selected 5 stations and zooplankton sampling by using ORI net at two stations along the WHP-P10N section mainly for estimation of dispersion of radioactive substances released into the sea by the Fukushima Dai-ichi nuclear power plant accident in March 2011. To understand the oceanographic condition along the WHP-P10N section in detail, we deployed XCTDs between the CTD stations. In addition, we launched radiosondes and HYdrometer VIdeo Sondes (HYVIS) to understand the atmospheric condition along the cruise track. Especially in the section across the Kuroshio Extension, we densely launched radiosondes simultaneously with the XCTDs (Fig. 1.1.2). At station 1, an ARGO float was deployed to take a photograph and recovered after that. In leg 2 of this cruise, we conducted full-depth CTD, lowered acoustic Doppler current profiler (LADCP), Micro-Rider measurements, and discrete water sampling for physical, chemical and biogeochemical properties of seawater from a maximum of 36 layers along the WHP-P01 section and at the ocean station PAPA (Figs. 1.1.3 and 1.1.4). We deployed two ARGO floats with RINKO oxygen sensor in an anticyclonic eddy off Hokkaido and four ARGO floats in the area where the number of ARGO floats is small to maintain the global array. Furthermore, we sampled marine plankton by using NORPAC net to examine changes in calcification responses of planktonic organisms and pH in the subarctic North Pacific. Also, we sampled seawater to examine horizontal and vertical distribution of microbial population (picoeukaryotes, bacteria, archaea, and viruses) in gene level to explain relationship between the microbial population and ocean circulations (seawater properties). In addition, we observed physical, chemical, and biogeochemical properties of seawater and atmosphere, and geophysical parameters (sea bottom topography, gravity acceleration, etc.) continuously along the cruise track in order to accumulate basic scientific data in global scale, especially for unobserved regions. References Kawano, T., and H. Uchida (Eds.) (2007): WHP P10 Revisit Data Book, JAMSTEC, 139 pp. Kawano, T., H. Uchida, and T. Doi (Eds.) (2009): WHP P01, P14 Revisit Data Book, JAMSTEC, 212 pp. Uchida, H., A. Murata, and T. Doi (Eds.) (2014): WHP P10 Revisit in 2011 Data Book, JAMSTEC, 179 pp. Uchida, H., M. Fukasawa, and H. J. Freeland (Eds.) (2002): WHP P01 Revisit Data Book, JAMSTEC, 73 pp. Fig. 1.1.1: Cruise track of the R/V Mirai cruise MR14-04. Fig. 1.1.2: Station locations for MR14-04 leg 1. Fig. 1.1.3: Station locations for MR14-04 leg 2. Fig. 1.1.4: Bottle depth diagram. 1.3 List of Principal Investigator and Person in Charge on the Ship The principal investigator (PI) and the person in charge responsible for major parameters measured on the cruise are listed in Table 1.3.1. Table 1.3.1: List of principal investigator and person in charge on the ship. Item Principal Investigator Person in charge onboard ————————————— ———————————————————————————————————— —————————————————————————————— Underway Navigation Hiroshi Uchida (JAMSTEC) Ryo Oyama (GODI) (leg 1) huchida@jamstec.go.jp Wataru Tokunaga (GODI) (leg 2) Bathymetry Takeshi Matsumoto (Univ. of Ryukyus) Ryo Oyama (GODI) (leg 1) tak@sci.u-ryukyu.ac.jp Wataru Tokunaga (GODI) (leg 2) Meteorology Masaki Katsumata (JAMSTEC) Ryo Oyama (GODI) (leg 1) katsu@jamstec.go.jp Wataru Tokunaga (GODI) (leg 2) TSG Hiroshi Uchida (JAMSTEC) Keitaro Matsumoto (MWJ) huchida@jamtec.go.jp pCO2 Akihiko Murata (JAMSTEC) Atsushi Ono (MWJ) murataa@jamstec.go.jp ADCP Shinya Kouketsu (JAMSTEC) Ryo Oyama (GODI) (leg 1) skouketsu@jamstec.go.jp Wataru Tokunaga (GODI) (leg 2) XCTD Hiroshi Uchida (JAMSTEC) Ryo Oyama (GODI) (leg 1) huchida@jamstec.go.jp Wataru Tokunaga (GODI) (leg 2) FlowCAM Hiroshi Uchida (JAMSTEC) Hiroshi Uchida (JAMSTEC) huchida@jamstec.go.jp Ceilometer Masaki Katsumata (JAMSTEC) Ryo Oyama (GODI) (leg 1) katsu@jamstec.go.jp Wataru Tokunaga (GODI) (leg 2) Raindrop Masaki Katsumata (JAMSTEC) Masaki Katsumata (JAMSTEC) katsu@jamstec.go.jp Doppler Radar Masaki Katsumata (JAMSTEC) Ryo Oyama (GODI) (leg 1) katsu@jamstec.go.jp Wataru Tokunaga (GODI) (leg 2) Radiosonde Masaki Katsumata (JAMSTEC) Ryo Oyama (GODI) katsu@jamstec.go.jp HYVIS Masaki Katsumata (JAMSTEC) Ryo Oyama (GODI) katsu@jamstec.go.jp Gravity Takeshi Matsumoto (Univ. of Ryukyus) Ryo Oyama (GODI) (leg 1) tak@sci.u-ryukyu.ac.jp Wataru Tokunaga (GODI) (leg 2) Magnetic Takeshi Matsumoto (Univ. of Ryukyus) Ryo Oyama (GODI) (leg 1) Field tak@sci.u-ryukyu.ac.jp Wataru Tokunaga (GODI) (leg 2) Satellite Masaki Katsumata (JAMSTEC) Ryo Oyama (GODI) (leg 1) Image katsu@jamstec.go.jp Wataru Tokunaga (GODI) (leg 2) Sky Kazuma Aoki (Univ. of Toyama) none Radiometer kazuma@sci.u-toyama.ac.jp MAX-DOAS Hisahiro Takashima (JAMSTEC) none hisahiro@jamstec.go.jp Ozone and CO Yugo Kanaya (JAMSTEC) none yugo@jamstec.go.jp Black Carbon Takuma Miyakawa (JAMSTEC) none miyakawat@jamstec.go.jp Fluorescent Fumikazu Taketani (JAMSTEC) none Aerosol taketani@jamstec.go.jp Aerosol Par- Fumikazu Taketani (JAMSTEC) none ticle Size taketani@jamstec.go.jp Hydrography CTD/O2 Hiroshi Uchida (JAMSTEC) Shinsuke Toyoda (MWJ) huchida@jamstec.go.jp Salinity Hiroshi Uchida (JAMSTEC) Tatsuya Tanaka (MWJ) huchida@jamstec.go.jp Density Hiroshi Uchida (JAMSTEC) Hiroshi Uchida (JAMSTEC) huchida@jamstec.go.jp Oxygen Yuichiro Kumamoto (JAMSTEC) Keitaro Matsumoto (MWJ) kumamoto@jamstec.go.jp Nutrients Michio Aoyama (Fukushima Univ.) Yasuhiro Arii (MWJ) r706@ipc.fukushima-u.ac.jp CFCs/SF6 Ken'ichi Sasaki (JAMSTEC) Ken'ichi Sasaki (JAMSTEC) (leg 1) ksasaki@jamstec.go.jp Hironori Sato (MWJ) (leg 2) DIC Akihiko Murata (JAMSTEC) Atsushi Ono (MWJ) murataa@jamstec.go.jp Alkalinity Akihiko Murata (JAMSTEC) Tomonori Watai (MWJ) murataa@jamstec.go.jp Alkalinity Yoshihiro Shinoda (JAMSTEC) Yoshihiro Shinoda (JAMSTEC) duplicate by yshinoda@jamstec.go.jp potentiometry pH Akihiko Murata (JAMSTEC) Tomonori Watai (MWJ) murataa@jamstec.go.jp Chlorophyll a Kosei Sasaoka (JAMSTEC) Keitaro Matsumoto (MWJ) sasaoka@jamstec.go.jp CDOM/ Kosei Sasaoka (JAMSTEC) Kosei Sasaoka (JAMSTEC) Absorption sasaoka@jamstec.go.jp Coefficients Calcium Yoshihiro Shinoda (JAMSTEC) Yoshihiro Shinoda (JAMSTEC) Yshinoda@jamstec.go.jp DOC Dennis A. Hansell (RSMAS) Yuichiro Kumamoto (JAMSTEC) dhansell@rsmas.miami.edu Takeshi Yoshimura (CRIEPI) ytakeshi@criepi.denken.or.jp DOC duplicate Masahide Wakita (JAMSTEC) Hiroshi Uchida (JAMSTEC) at station mwakita@jamstec.go.jp 73 (K2) Δ14C/δ13C Yuichiro Kumamoto (JAMSTEC) Yuichiro Kumamoto (JAMSTEC) kumamoto@jamstec.go.jp 134Cs/137Cs Yuichiro Kumamoto (JAMSTEC) Yuichiro Kumamoto (JAMSTEC) kumamoto@jamstec.go.jp Iodine-129 Yuichiro Kumamoto (JAMSTEC) Yuichiro Kumamoto (JAMSTEC) kumamoto@jamstec.go.jp δ18O/δD Hiroshi Uchida (JAMSTEC) Hiroshi Uchida (JAMSTEC) huchida@jamstec.go.jp PFASs Nobuyoshi Yamashita (AIST) Nobuyoshi Yamashita (AIST) (leg 1) nob.yamashita@aist.go.jp Sachi Taniyasu (AIST) (leg 2) N2O/CH4 Osamu Yoshida (RGU) Osamu Yoshida (RGU) (leg 1) yoshida@rakuno.ac.jp Takuya Takahashi (RGU) (leg 2) Cell Takuro Nunoura (JAMSTEC) Taichi Yokokawa (Ehime Univ.) (leg 1) abundance takuron@jamstec.go.jp Takuro Nunoura (JAMSTEC) (leg 2) Microbial Takuro Nunoura (JAMSTEC) Takuro Nunoura (JAMSTEC) diversity takuron@jamstec.go.jp Microbial Takuro Nunoura (JAMSTEC) Taichi Yokokawa (Ehime Univ.) (leg 1) carbon uptake takuron@jamstec.go.jp Takuro Nunoura (JAMSTEC) (leg 2) Nitrification Akiko Makabe (TUAT) Akiko Makabe (TUAT) a-makabe@cc.tuat.ac.jp Nitrogen Masanori Kaneko (JAMSTEC) Masanori Kaneko (JAMSTEC) (leg 1) fixation m_kaneko@jamstec.go.jp Shuichiro Matushima (TITECH) (leg 2) Methanogen Masanori Kaneko (JAMSTEC) Masanori Kaneko (JAMSTEC) (leg 1) biomarker m_kaneko@jamstec.go.jp Takuya Takahashi (RGU) (leg 2) δ13C/CH4 Masanori Kaneko (JAMSTEC) Masanori Kaneko (JAMSTEC) (leg 1) m_kaneko@jamstec.go.jp Takuya Takahashi (RGU) (leg 2) δ15N δ18O/NO3- Chisato Yoshikawa (JAMSTEC) Chisato Yoshikawa (JAMSTEC) (leg 1) yoshikawac@jamstec.go.jp Akiko Makabe (TUAT) (leg 2) δ15N/ Chisato Yoshikawa (JAMSTEC) Chisato Yoshikawa (JAMSTEC) (leg 1) chlorophyll yoshikawac@jamstec.go.jp Takuya Takahashi (TUAT) (leg 2) δ15N δ18O/N2O, Sakae Toyoda (TITECH) Shuichiro Matsushima (TITECH) (leg 2) NO2 toyoda.s.aa@m.titech.ac.jp δ15N/NH4+, Akiko Makabe (TUAT) Akiko Makabe (TUAT) DON, urea a-makabe@cc.tuat.ac.jp LADCP Shinya Kouketsu (JAMSTEC) Hiroshi Uchida (JAMSTEC) (leg 1) skouketsu@jamstec.go.jp Shinya Kouketsu (JAMSTEC) (leg 2) Micro-Rider Ichiro Yasuda (AORI) Shinya Kouketsu (JAMSTEC) ichiro@aori.u-tokyo.ac.jp Biology ORI net Minoru Kitamura (JAMSTEC) Minoru Kitamura (JAMSTEC) kitamura@jamstec.go.jp NORPAC net Katsunori Kimoto (JAMSTEC) Shinya Iwasaki (AORI) kimopy@jamstec.go.jp Phytoplankton Koji Sugie (JAMSTEC) Koji Sugie (JAMSTEC) Incubation sugie@jamstec.go.jp Floats ARGO float Toshio Suga (JAMSTEC) Hiroshi Matsunaga (MWJ) sbaba@jamstec.go.jp JAMSTEC Japan Agency for Marine-Earth Science and Technology GODI Global Ocean Development Inc. MWJ Marine Works Japan, Ltd. RSMAS Rosenstiel School of Marine and Atmospheric Science, University of Miami CRIEPI Central Research Institute of Electric Power Industry AIST National Institute of Advanced Industrial Science and Technology RGU Rakuno Gakuen University TUAT Tokyo University of Agriculture and Technology TITECH Tokyo Institute of Technology AORI Atmosphere and Ocean Research Institute, The Univ. of Tokyo 1.4 List of Cruise Participants Table 1.4.1: List of cruise participants for leg 1. Name Responsibility Affiliation ——————————————————— ——————————————————————————————————————— ———————————— Hiroshi Uchida Density/FlowCAM/LADCP/δ18O RCGC/JAMSTEC Yuichiro Kumamoto DO/Radionuclides/Water sampling RCGC/JAMSTEC Yoshihiro Shinoda Water sampling RCGC/JAMSTEC Minoru Kitamura ORI net RCGC/JAMSTEC Masaki Katsumata HYVIS/Radiosonde/Doppler radar/Raindrop RCGC/JAMSTEC Biao Geng HYVIS/Radiosonde/Doppler radar RCGC/JAMSTEC Shuichi Mori HYVIS/Radiosonde/Doppler radar DCOP/JAMSTEC Ryuichi Shirooka HYVIS/Radiosonde/Doppler radar DCOP/JAMSTEC Ken'ichi Sasaki CFCs/SF6 MIO/JAMSTEC Takuro Nunoura Microbiology RCMB/JAMSTEC Miho Hirai Microbiology RCMB/JAMSTEC Chisato Yoshikawa Chlorophyll/NO3 isotope geochemistry BGC/JAMSTEC Masanori Kaneko CH4 geochemistry/Nitrogen fixation BGC/JAMSTEC Akiko Makabe Nitrification/Nitrogen geochemistry TUAT Taichi Yokokawa Microbiology Ehime Univ. Nobuyoshi Yamashita PFASs AIST Osamu Yoshida N2O/CH4 RGU Kanta Chida N2O/CH4 RGU Takuya Takahashi N2O/CH4 RGU Tomoyuki Shirakawa TV camera JBC Fumihiko Saito TV camera JBC Ryo Oyama Chief technologist /meteorology/ GODI geophysics/ADCP/XCTD Souichiro Sueyoshi Meteorology/geophysics/ADCP/XCTD GODI Katsuhisa Maeno Meteorology/geophysics/ADCP/XCTD GODI Koichi Inagaki Meteorology/geophysics/ADCP/XCTD GODI Yutaro Murakami Meteorology/geophysics/ADCP/XCTD GODI Shinsuke Toyoda Chief technologist/CTD/water sampling MWJ Hiroshi Matsunaga CTD/ARGO MWJ Kenichi Katayama CTD MWJ Rei Ito CTD MWJ Akira Watanabe CTD MWJ Tatsuya Tanaka Salinity MWJ Sonoka Wakatsuki Salinity MWJ Keitaro Matsumoto DO/Chlorophyll-a/TSG MWJ Misato Kuwahara DO/Chlorophyll-a/TSG MWJ Haruka Tamada DO/Chlorophyll-a/TSG MWJ Yasuhiro Arii Nutrients MWJ Minoru Kamata Nutrients MWJ Tomomi Sone Nutrients MWJ Katsunori Sagishima CFCs/SF6 MWJ Hironori Sato CFCs/SF6 MWJ Hideki Yamamoto CFCs/SF6 MWJ Atsushi Ono DIC MWJ Yoshiko Ishikawa DIC MWJ Tomonori Watai pH/Alkalinity MWJ Emi Deguchi pH/Alkalinity MWJ JAMSTEC Japan Agency for Marine-Earth Science and Technology RCGC Research and Development Center for Global Change DCOP Department of Coupled Ocean-Atmosphere-Land Processes Research MIO Mutsu Institute of Oceanography RCMB Research and Development Center for Marine Biosciences BGC Department of Biogeochemistry TUAT Tokyo University of Agriculture and Technology AIST National Institute of Advanced Industrial Science and Technology RGU Rakuno Gakuen University JBC Japan Broadcasting Corporation GODI Global Ocean Development Inc. MWJ Marine Works Japan, Ltd. Table 1.4.2: List of cruise participants for leg 2. Name Responsibility Affiliation ———————————————————— —————————————————————————————————————— ———————————— Hiroshi Uchida Density/FlowCAM/LADCP/Micro-Rider/δ18O RCGC/JAMSTEC Yuichiro Kumamoto DO/Radionuclides/Water sampling RCGC/JAMSTEC Yoshihiro Shinoda Calcium/Water sampling RCGC/JAMSTEC Shinya Koketsu LADCP/Micro-Rider/δ18O RCGC/JAMSTEC Kosei Sasaoka CDOM/Absorption coefficient RCGC/JAMSTEC Koji Sugie Phytoplankton incubation/NORPAC net RCGC/JAMSTEC Shinya Iwasaki NORPAC net/Phytoplankton incubation AORI/Univ. of Tokyo Takuro Nunoura Microbiology RCMB/JAMSTEC Akiko Makabe Nitrification/Nitrogen geochemistry TUAT Shuichiro Matsushima Nitrogen fixation/Nitrogen TITECH geochemistry/CH4 Seiya Takahashi Microbiology Tsukuba Univ. Sachi Taniyasu PFASs AIST Kanta Chida N2O/CH4 RGU Takuya Takahashi N2O/CH4 RGU Wataru Tokunaga Chief technologist /meteorology/ GODI geophysics/ADCP/XCTD Kazuho Yoshida Meteorology/geophysics/ADCP/XCTD GODI Yutaro Murakami Meteorology/geophysics/ADCP/XCTD GODI Tetsuya Kai Meteorology/geophysics/ADCP/XCTD GODI Shinsuke Toyoda Chief technologist/CTD/water sampling MWJ Hiroshi Matsunaga CTD/ARGO MWJ Tomoyuki Takamori CTD MWJ Rei Ito CTD MWJ Akira Watanabe CTD MWJ Tatsuya Tanaka Salinity MWJ Sonoka Wakatsuki Salinity MWJ Keitaro Matsumoto DO/Chlorophyll-a/TSG MWJ Katsunori Sagishima DO/Chlorophyll-a/TSG MWJ Haruka Tamada DO/Chlorophyll-a/TSG MWJ Yasuhiro Arii Nutrients MWJ Kenichiro Sato Nutrients MWJ Elena Hayashi Nutrients MWJ Hironori Sato CFCs/SF6 MWJ Hideki Yamamoto CFCs/SF6 MWJ Shoko Tatamisashi CFCs/SF6 MWJ Kanako Yoshida CFCs/SF6 MWJ Atsushi Ono DIC MWJ Yoshiko Ishikawa DIC MWJ Tomonori Watai pH/Alkalinity MWJ Emi Deguchi pH/Alkalinity MWJ Rina Tajima Water sampling MWJ Toshiki Nosho Water sampling MWJ Miho Arai Water sampling MWJ Kohei Kumagai Water sampling MWJ Yuki Kawabuchi Water sampling MWJ Yuki Komuro Water sampling MWJ JAMSTEC Japan Agency for Marine-Earth Science and Technology RCGC Research and Development Center for Global Change AORI Atmosphere and Ocean Research Institute, The Univ. of Tokyo RCMB Research and Development Center for Marine Biosciences TUAT Tokyo University of Agriculture and Technology TITECH Tokyo Institute of Technology AIST National Institute of Advanced Industrial Science and Technology RGU Rakuno Gakuen University GODI Global Ocean Development Inc. MWJ Marine Works Japan, Ltd. 2 Underway Measurements 2.1 Navigation September 17, 2014 (1) Personnel Hiroshi Uchida JAMSTEC: Principal investigator Ryo Oyama Global Ocean Development Inc., (GODI) - leg 1 - Souichiro Sueyoshi GODI - leg 1 - Katsuhisa Maeno GODI - leg 1 - Koichi Inagaki GODI - leg 1 - Wataru Tokunaga GODI - leg 2 - Kazuho Yoshida GODI - leg 2 - Tetsuya Kai GODI - leg 2 - Yutaro Murakami GODI - leg 1, leg 2 - Masanori Murakami MIRAI crew - leg 1, leg 2 - (2) System description Ship’s position and velocity were provided by Navigation System on R/V MIRAI. This system integrates GPS position, Doppler sonar log speed, Gyro compass heading and other basic data for navigation, and calculated speed and course over ground on workstation. 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) GPS system: R/V MIRAI has four GPS systems, all GPS positions were offset to radar- mast position, datum point. Anytime changeable manually switched as to GPS receiving state. a) MultiFix6 (software version 1.01), Differential GPS system. Receiver: Trimble SPS751, with GPS antenna located on navigation deck, starboard. Decoder: FUGURO STARFIX 4100LRS b) MultiFix6 (software version 1.01), Differential GPS system. Receiver: Trimble SPS751, with two GPS antenna located on compass deck, port side. Decoder: FUGURO STARFIX 4100LRS c) Standalone GPS system. Receiver: Trimble 4000DS, GPS antenna located on navigation deck, port side. d) Standalone GPS system. Receiver: FURUNO GP-36, GPS antenna located on navigation deck, starboard. 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) Data period (Times in UTC) Leg 1: 22:10, 08 Jul. 2014 to 04:00, 15 Jul. 2014 Leg 2: 02:00, 17 Jul. 2014 to 18:00, 29 Aug. 2014 (4) Remarks (Times in UTC) i) The following periods, navigation data (position, speed and course over ground) was often invalid due to position fix error for loss of GPS satellites. Leg 1: 14 Jul. to 15 Jul., 2014 Leg 2: 17 Jul. to 16 Aug., 2014 ii) The following periods, navigation data was invalid due to the system error. Leg 2: 12:37 to 12:45 23 Aug., 2014 iii) Some data records were lacked due to the system error or GPS trouble. See data “readme.txt" which contains the time of data lost. Fig.2.1.1: Cruise track of MR14-04 Leg 1. Fig.2.1.2: Cruise track of MR14-04 Leg 2. 2.2 Swath Bathymetry September 17, 2014 (1) Personnel Takeshi Matsumoto Univ. of Ryukyus: Principal investigator (Not-onboard) Ryo Oyama Global Ocean Development Inc., (GODI) - leg 1 - Souichiro Sueyoshi GODI - leg 1 - Katsuhisa Maeno GODI - leg 1 - Koichi Inagaki GODI - leg 1 - Wataru Tokunaga GODI - leg 2 - Kazuho Yoshida GODI - leg 2 - Tetsuya Kai GODI - leg 2 - Yutaro Murakami GODI - leg 1, leg 2 - Masanori Murakami MIRAI crew - leg 1, leg 2 - (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 the MR14-04 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: SEABEMA 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 (Spacing mode: Equi-angle) Beam spacing: 1.5% of water depth (Spacing mode: Equi-distance) 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 8.1.7 (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: 100 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 (-S): 150 m Number of sectors (-N): 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 observations were carried out. Leg 1: 02:52 09 Jul. to 23:22 14 Jul., 2014 Leg 2: 06:19 17 Jul. to 12:29 28 Aug., 2014 ii) The following periods, navigation data (position, speed and course over ground) was often invalid due to position fix error for loss of GPS satellites. If bathymetric data were included error position and heading information, we interpolated from the just before and behind correct data using the HIPS. Leg 1: 14 Jul. to 15 Jul., 2014 Leg 2: 17 Jul. to 16 Aug., 2014 iii) The following periods, navigation data was invalid due to the server error. Leg 2: 12:37 to 12:45 23 Aug., 2014 iv) The following periods, data acquisition was suspended due to the system error and maintenance. 01:55 30 Jul. to 01:59 30 Jul., 2014 06:43 30 Jul. to 07:40 30 Jul., 2014 2.3 Surface Meteorological Observations September 17, 2014 (1) Personnel Masaki Katsumata (JAMSTEC): Principal Investigator Ryo Oyama (Global Ocean Development Inc., GODI) -leg1- Souichiro Sueyoshi (GODI) -leg1- Katsuhisa Maeno (GODI) -leg1- Koichi Inagaki (GODI) -leg1- Wataru Tokunaga (GODI) -leg2- Kazuho Yoshida (GODI) -leg2- Tetsuya Kai (GODI) -leg2- Yutaro Murakami (GODI) -leg1, leg2- Masanori Murakami (MIRAI Crew) -leg1, 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 the MR14-04 cruise from 8th July 2014 to 29th August 2014, except for the USA territorial waters. 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) 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 data every 6 seconds, CR1000 data every 10 seconds, air temperature and relative humidity data every 2 seconds and ORG data every 5 seconds. SCS composed Event data (JamMet) from these data and ship’s navigation data. 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. a) 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. b) Barometer (SMet and SOAR) Comparison with the portable barometer value, PTB220, VAISALA c) Thermometer (air temperature and relative humidity) (SMet and SOAR) Comparison with the portable thermometer value, HMP41/45, VAISALA (4) Preliminary results Figs. 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 (SOAR) 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) Data acquisition was suspended in the territorial waters of USA. ii) The following periods, sea surface temperature of SMet data was available. Leg 1: 01:39, 09 Jul. 2014 - 23:31, 14 Jul. 2014 Leg 2: 02:04, 17 Jul. 2014 - 12:30, 28 Aug. 2014 iii) The following periods, navigation data (position, speed and course over ground) of SMet and JamMet were often invalid due to position fix error for loss of detected GPS satellites. Leg 1: 14 Jul. to 15 Jul. 2014 Leg 2: 17 Jul. to 16 Aug. 2014 iv) The following period, navigation data of SMet was invalid due to network server trouble. Leg 2: 12:37, 23 Aug. 2014 - 12:44, 23 Aug. 2014 v) The following period, ship gyro and LOG of JamMet were invalid due to communication error to network server. Leg 1: 07:57:06, 18:38:32; 11 Jul. 2014 Leg 2: 11:28:40, 08 Aug. 2014 19:21:00, 21 Aug. 2014 vi) The following time, increasing of SMet capacitive rain gauge data were invalid due to test transmitting for VHF radio. Leg 2: 14:23, 23:14; 19 Jul. 2014 05:18, 25 Jul. 2014 06:17, 26 Jul. 2014 06:06, 18:32; 27 Jul. 2014 18:13, 28 Jul. 2014 06:04, 17:19; 30 Jul. 2014 vii) The following period, PRP data was invalid due to PC trouble. Leg 1: 01:08, 09 Jul. 2014 - 01:25, 09 Jul. 2014 14:48, 09 Jul. 2014 - 14:54, 09 Jul. 2014 viii) The following period, logging interval of PRP was longer than normal. Leg 1: 08:50, 09 Jul. 2014 - 14:54, 09 Jul. 2014 ix) The following period, ORG data was invalid due to sensor error. Leg 2: 19:37:51 to 19:40:33, 27 Aug. 2014, Table 2.3.1: Instruments and installation locations of MIRAI Surface Meteorological observation system. Location Sensors Type Manufacturer (altitude from surface) ————————————————————— ————————— ———————————————————— ————————————————————————— Anemometer KE-500 Koshin Denki, Japan foremast (24 m) Tair/RH HMP155 Vaisala, Finland with 43408 Gill R.M. Young, USA compass deck (21 m) aspirated starboard side and radiation shield port side 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 MS-802 Eko Seiki, Japan radar mast (28 m) wave) Radiometer (long MS-202 Eko Seiki, Japan radar mast (28 m) wave) Wave height meter WM-2 Tsurumi-seiki, Japan bow (10 m) Table 2.3.2: Parameters of MIRAI Surface Meteorological observation system. Parameter Units Remarks ———————————————————————————————————————— —————— ——————————————————————— 2 Longitude degree 3 Ship’s speed knot Mirai log, DS-30 Furuno 4 Ship's heading degree Mirai gyro, TG-6000,TOKYO-KEIKI 5 Relative wind speed m/s 6sec./10min. averaged 6 Relative wind direction degree 6sec./10min. averaged 7 True wind speed m/s 6sec./10min. averaged 8 True wind direction degree 6sec./10min. averaged 9 Barometric pressure hPa adjusted to sea surface level 6sec. averaged 10 Air temperature (starboard side) degC 6sec. averaged 11 Air temperature (port side) degC 6sec. averaged 12 Dewpoint temperature (starboard side) degC 6sec. averaged 13 Dewpoint temperature (port side) degC 6sec. averaged 14 Relative humidity (starboard side) % 6sec. averaged 15 Relative humidity (port side) % 6sec. averaged 16 Sea surface temperature degC 6sec. averaged 17 Rain rate (optical rain gauge) mm/hr hourly accumulation 18 Rain rate (capacitive rain gauge) mm/hr hourly accumulation 19 Down welling shortwave radiation W/m2 6sec. averaged 20 Down welling infra-red radiation W/m2 6sec. averaged 21 Significant wave height (bow) m hourly 22 Significant wave height (aft) m hourly 23 Significant wave period (bow) second hourly 24 Significant wave period (aft) second hourly Table 2.3.3: Instruments and installation locations of SOAR system. Location Sensors Type Manufacturer (altitude from surface) ————————————————————— ————————— ———————————————————— ————————————————————————— Meteorological Anemometer 05106 R.M. Young, USA foremast (25 m) Barometer PTB210 Vaisala, Finland with 61002 Gill pressure port R.M. Young, USA foremast (23 m) Capacitive rain gauge 50202 R.M. Young, USA foremast (24 m) Tair/RH HMP155 Vaisala, Finland with 43408 Gill aspirated R.M. Young, USA foremast (23 m) radiation shield Optical rain gauge ORG-815DR Osi, USA foremast (24 m) PRP Radiometer (short PSP Epply Labs, USA foremast (25 m) wave) Radiometer (long PIR Epply Labs, USA foremast (25 m) wave) Fast rotating shadowband Yankee, USA foremast (25 m) radiometer PAR PAR sensor PUV-510B 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 E/cm2/sec Figure 2.3.1: Time series of surface meteorological parameters during the MR14-04 cruise. 2.4 Thermo-Salinograph and Related Measurements September 25, 2014 (1) Personnel Hiroshi Uchida (JAMSTEC) Keitaro Matsumoto (MWJ) Katsunori Sagishima (MWJ) Haruka Tamada (MWJ) (2) Objectives The objective is to collect sea surface salinity, temperature, dissolved oxygen, fluorescence, 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 six sensors and automatically measures salinity, temperature, dissolved oxygen, and fluorescence in sea surface water every one minute. This system is located in the sea surface monitoring laboratory 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. 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 in leg 2. 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: 4552788-0319 Bottom of ship thermometer Model: SBE 38, SEA-BIRD ELECTRONICS, INC. Serial number: 3852788-0457 Dissolved oxygen sensor Model: OPTODE 3835, Aanderaa Data Instruments, AS. Serial number: 1519 Model: RINKO-II, JFE Advantech Co. Ltd. Serial number: 0013 Fluorometer Model: C3, TURNER DESIGNS Serial number: 2300123 Nitrate sensor Model: Deep SUNA, Satlantic, LP. (used only for leg 2) Serial number: 0385 Table 2.4.1: Events of the Continuous Sea Surface Water Monitoring System operation. System Date System Time Event [UTC] [UTC] ——————————— ——————————— ———————————————————————————————— 2014/07/09 02:32 Logging for leg 1 start 2014/07/14 23:30 Logging for leg 1 end 2014/07/17 02:50 Logging for leg 2 start 2014/07/28 23:52 Logging stop for filter cleaning 2014/07/29 00:48 Logging restart 2014/08/12 01:42 Logging stop for filter cleaning 2014/08/12 03:20 Logging restart 2014/08/22 02:27 Logging stop for filter cleaning 2014/08/22 03:27 Logging restart 2014/08/25 16:55 Logging stop for filter cleaning 2014/08/25 17:00 Logging restart 2014/08/28 12:29 Logging for leg 2 end (4) Data Processing and Quality Control The navigation data (latitude and longitude) for leg 2 was often invalid due to position fix error for loss of GPS satellites. The invalid navigation data were replaced by using the dataset “interpoGGA”. The “interpoGGA” was made using all available navigation data and was interpolated on a time interval of 1 second and low-pass filtered with a window of 20 seconds. Data from the Continuous Sea Surface Water Monitoring System were obtained at 1 minute intervals. Data from the nitrate sensor were obtained at 1 minute intervals until 2014/07/18 03:50. However, the nitrate sensor frequently continued to show invalid data (-1.0) and needed to restart the system. Therefore, the time interval was changed to 2 minutes since then. 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 0.1°C for temperature and 0.5 for salinity. Data gaps were linearly interpolated when the gap was ≤ 7 minutes. Fluorometer data were low-pass filtered using a median filter with a window of 3 scans (3 minutes) to remove spikes. Raw data from the RINKO oxygen sensor, fluorometer and nitrate data were low-pass filtered using a Hamming filter with a window of 15 scans (15 minutes). 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 3.8 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] = NRA + c0 + c1 t where S is practical salinity, t is days from a reference time (2014/07/09 02:32 [UTC]), T is temperature in °C. 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 from Figs. 2.4.1 to 2.4.4. For fluorometer data, water sampled data obtained at night [PAR (Photosynthetically Available Radiation) < 50 μE/(m2 sec), see Section 2.3] 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 be also different between high and low temperature. Therefore, slope (c1) of the calibration coefficients was changed for temperature range (Table 2.4.3). For temperature between 20.5°C and 19.5°C, chlorophyll a was estimated from weighted mean of the two equations as Chl-a = Chl-a1 f2 + Chl-a2 f1 f1 = 1 – (TSG temperature + 19.5°C) f2 = 1 – f1 where Chl-a1 is chlorophyll a calculated by using the set of coefficients A, and Chl-a2 is chlorophyll a calculated by using the set of coefficients B (Table 2.4.2). Noise of the nitrate data tended to become large over time (Fig. 2.4.4). Dismounting of the flow cell improved the data quality probably because the optical windows were wiped and cleaned by the O rings of the flow cell. Data affected by the large noise were flagged as questionable data (Fig. 2.4.4). (5) Reference Uchida, H., K. Katsumata, and T. Doi (eds.) (2015): WHP P14S, S04I Revisit in 2012 Data Book, 187 pp., JAMSTEC. Table 2.4.2: Calibration coefficients for the salinity, dissolved oxygen, and chlorophyll a, and nitrate. c0 c1 c2 c3 ———————————————— ————————————— ———————————— ———————————— ———————————————————— Salinity -8.026137e-02 1.002264 4.381446e-04 Dissolved oxygen 5.929262 0.9575661 0.1590061 -5.164405e-02 Chlorophyll a 4.845356e-02 0.1030891 (A: for TSG temperature ≥ 20.5°C) 4.845356e-02 5.411620e-02 (B: for TSG temperature < 19.5°C) Nitrate -23.140 2.7154355 (t ≤ 14.76) 14.304 0.2678845 (14.76 < t ≤ 34.0) -29.419 1.044715855 (34.0 < t ≤ 44.0) -46.856 1.044715855 (44.0 < t) Figure 2.4.1: Comparison between TSG salinity (red: before correction, green: after correction) and sampled salinity. Figure 2.4.2: Comparison between TSG oxygen (red: before correction, green: after correction) and sampled oxygen. Figure 2.4.3: Comparison between TSG fluorescence and sampled chlorophyll a. Open circles indicate the daytime data. Blue dots indicate data obtained at temperature higher than or equal to 20°C and red dots indicate data obtained at temperature lower than 20°C. For bottom panel, blue or red dots indicate fluorescence and green dots indicate water sampled chlorophyll a. Line indicates chlorophyll a estimated from fluorometer. Figure 2.4.4: Comparison between TSG nitrate (blue line: before correction, red and gray lines: after correction) and sampled nitrate (dots). Gray lines indicate questionable data obtained during following periods: 26.3 < t ≤ 34.0 and 41.9 < t ≤ 44.0. 2.5 Underway pCO2 February 1, 2017 (1) Personnel Akihiko Murata (JAMSTEC) Yoshiko Ishikawa (MWJ) Atsushi Ono (MWJ) (2) Introduction According to the latest report from Intergovernmental Panel on Climate Change, concentrations of CO2 in the atmosphere have increased by 40% since pre-industrial times owing to human activities such as burning of fossil fuels, deforestation, and cement production. It is evaluated that the ocean has absorbed about 30% of the emitted anthropogenic CO2. 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 future global warming depends on the levels of CO2 in the atmosphere. The North Pacific 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 is absorbed in the ocean interior of the North Pacific. For the purpose, we measured atmospheric and surface seawater partial pressures of CO2 (pCO2) along the extended WHP P10 and P01 lines at 149°E and 47°N, respectively, in the North Pacific. (3) Apparatus and shipboard measurement Continuous underway measurements of atmospheric and surface seawater pCO2 were made with the CO2 measuring system (Nippon ANS, Ltd) installed in the R/V Mirai of JAMSTEC. The system comprises of a non-dispersive infrared gas analyzer (Li-COR LI-7000), an air-circulation module and a showerhead-type equilibrator. To measure concentrations (mole fraction) of CO2 in dry air (xCO2a), air sampled from the bow of the ship (approx. 30 m above the sea level) was introduced into the NDIR through a dehydrating route with an electric dehumidifier (kept at ~2°C), a Perma Pure dryer (GL Sciences Inc.), and a chemical desiccant (Mg(ClO4)2). The flow rate of the air was 500 ml min-1. To measure surface seawater concentrations of CO2 in dry air (xCO2s), the air equilibrated with seawater within the equilibrator was introduced into the NDIR through the same flow route as the dehydrated air used in measuring xCO2a. The flow rate of the equilibrated air was 400 – 900 ml min- 1. The seawater was taken by a pump from the intake placed at the approx. 4.5 m below the sea surface. The flow rate of seawater in the equilibrator was 4000 – 5000 ml min-1. The CO2 measuring system was set to repeat the measurement cycle such as 4 kinds of CO2 standard gases (Table 2.5.1), xCO2a (twice), xCO2s (7 times). This measuring system was run automatically throughout the cruise by a PC control. (4) Quality control Concentrations of CO2 of the standard gases are listed in Table 2.5.1, which were calibrated after cruise by the JAMSTEC primary standard gases. The CO2 concentrations of the primary standard gases were calibrated by the Scripps Institution of Oceanography, La Jolla, CA, USA. In actual shipboard observations, the signals of NDIR usually reveal a trend. The trends were adjusted linearly using the signals of the standard gases analyzed before and after the sample measurements. Effects of water temperature increased between the inlet of surface seawater and the equilibrator on xCO2s were adjusted based on Takahashi et al. (1993), although the temperature increases were slight, being ~0.3°C. We checked values of xCO2a and xCO2s by examining signals of the NDIR by plotting the xCO2a and xCO2s as a function of sequential day, longitude, sea surface temperature and sea surface salinity. (5) Reference Takahashi, T., J. Olafsson, J.G. Goddard, D.W. Chipman, and S. C. Southerland (1993) Seasonal variation of CO2 and nutrients in the high-latitude surface oceans: a comparative study, Global Biogeochem. Cycles, 7, 843 – 878. Table 2.5.1: Concentrations of CO2 standard gases used during the North Pacific cruise. Cylinder no. Concentrations (ppmv) ———————————— ————————————————————— CQB09459 249.59 CQB09354 299.03 CQB06574 398.90 CRC00732 448.90 2.6 Shipboard ADCP November 21, 2016 (1) Personnel Shinya Kouketsu (JAMSTEC) : Principal Investigator Ryo Oyama (Global Ocean Development Inc., GODI) -leg1- Souichiro Sueyoshi (GODI) -leg1- Katsuhisa Maeno (GODI) -leg1- Koichi Inagaki (GODI) -leg1- Wataru Tokunaga (GODI) -leg2- Kazuho Yoshida (GODI) -leg2- Tetsuya Kai (GODI) -leg2- Yutaro Murakami (GODI) -leg1, leg2- Masanori Murakami (MIRAI Crew) -leg1, leg2- (2) Objective To obtain continuous measurement of the current profile along the ship’s track. (3) Methods Upper ocean current measurements were made in the MR14-04 Leg1 and Leg2 cruises, using the hullmounted Acoustic Doppler Current Profiler (ADCP) system. For most of its operation the instrument was configured for water- tracking mode. Bottom-tracking mode, interleaved bottom-ping with water-ping, was made to get the calibration data for evaluating transducer misalignment angle in the shallow water. The system consists of following components; i) R/V MIRAI has installed vessel-mount ADCP (acoustic frequency 76.8 kHz “Ocean Surveyor”, Teledyne RD Instruments). It has a phased-array transducer with single ceramic assembly and creates 4 acoustic beams electronically. We mounted the transducer head rotated to a ship- relative angle of 45 degrees azimuth from the keel. ii) For heading source, we use ship’s gyro compass (TOKYO KEIKI, Japan), continuously providing heading to the ADCP system directory. Also we have Inertial Navigation System (PHINS, IXBLUE) which provide high- precision heading and attitude information are stored in “.N2R” data files. iii) DGPS system (Trimble SPS751 & StarFixXP) and GPS systems (Trimble 4000DS and FURUNO GP-36) providing position fixes. We selected the best system according to their positioning condition. iv) We used VmDas version 1.46.5 (TRDI) for data acquisition. v) To synchronize time stamp of pinging with GPS time, the clock of the logging computer is adjusted to GPS time every 5 minutes. vi) The sound speed at the transducer does affect the vertical bin mapping and vertical velocity measurement, is calculated from temperature, salinity (constant value; 35.0 psu) and depth (6.5 m; transducer depth) by equation in Medwin (1975). Data was configured for 8-m intervals starting 23-m below the surface. Every ping was recorded as raw ensemble data (.ENR). Also, 60 seconds and 300 seconds averaged data were recorded as short term average (.STA) and long term average (.LTA) data, respectively. Major parameters for the measurement (Direct Command) are shown in Table 2.6.1. After the cruises, we plan to carry out the alignment correction and provide the processed data. (4) Preliminary results Fig.2.6.1 and 2.6.2 shows surface current profile along the ship’s track, averaged four depth cells from 12th to 15th, about 110 m to 135 m with 60 minutes average. (5) Data archive These data obtained in this cruise will be submitted to the Data Management Group (DMG) of JAMSTEC, and will be opened to the public via JAMSTEC home page. (6) Remarks (Times in UTC) i) Data acquisition was suspended in the territorial waters of USA. ii) During the Leg1 cruise, background signal under sail was large due to biofouling on the ship bottom window. iii) The following periods, data acquisition was suspended for system condition check. Leg1: 23:29UTC 09 Jul. 2014 - 00:15UTC 10 Jul. 2014 05:55UTC 10 Jul. 2014 - 06:48UTC 10 Jul. 2014 03:42UTC 11 Jul. 2014 - 04:11UTC 11 Jul. 2014 11:13UTC 12 Jul. 2014 - 11:20UTC 12 Jul. 2014 00:42UTC 14 Jul. 2014 - 01:07UTC 14 Jul. 2014 iv) The following periods, navigation data was often invalid due to GPS position fix error. Leg1: 14 Jul. to 15 Jul. 2014 Leg2: 17 Jul. to 16 Aug. 2014 (7) Processed data The processed data were corrected with the ADCP misalignment calculated by comparison between bottom track and ship velocities during the cruise. In this cruise, as there are many outliers in the GPS data, we did not use the data 3 times standard deviation far from the positions averaged in 5000 minutes. After that, by inverse method with the available beam velocities during 5 minutes, we obtained the velocity profiles and their estimation errors. Table 2.6.1: Major parameters Bottom-Track Commands BP = 001 Pings per Ensemble (almost less than 1300m depth) Leg1: 22:32UTC 08 Jul. 2014 - 03:08UTC 09 Jul. 2014 16:44UTC 14 Jul. 2014 - 03:45UTC 14 Jul. 2014 Leg2: 00:07UTC 17 Jul. 2014 - 14:21UTC 17 Jul. 2014 14:49UTC 22 Aug. 2014 - 23:59UTC 22 Aug. 2014 11:57UTC 28 Aug. 2014 - 12:30UTC 28 Aug. 2014 Environmental Sensor Commands EA = +04500 Heading Alignment (1/100 deg) EB = +00000 Heading Bias (1/100 deg) ED = 00065 Transducer Depth (0 - 65535 dm) EF = +001 Pitch/Roll Divisor/Multiplier (pos/neg) [1/99 - 99] EH = 00000 Heading (1/100 deg) ES = 35 Salinity (0-40 pp thousand) EX = 00000 Coord Transform (Xform:Type; Tilts; 3Bm; Map) EZ = 10200010 Sensor Source (C; D; H; P; R; S; T; U) C (1): Sound velocity calculates using ED, ES, ET (temp.) D (0): Manual ED H (2): External synchro P (0), R (0): Manual EP, ER (0 degree) S (0): Manual ES T (1): Internal transducer sensor U (0): Manual EU Timing Commands TE = 00:00:02.00 Time per Ensemble (hrs:min:sec.sec/100) TP = 00:02.00 Time per Ping (min:sec.sec/100) Water-Track Commands WA = 255 False Target Threshold (Max) (0-255 count) WB = 1 Mode 1 Bandwidth Control (0=Wid, 1=Med, 2=Nar) WC = 120 Low Correlation Threshold (0-255) WD = 111 100 000 Data Out (V; C; A; PG; St; Vsum; Vsum^2;#G;P0) WE = 1000 Error Velocity Threshold (0-5000 mm/s) WF = 0800 Blank After Transmit (cm) WG = 001 Percent Good Minimum (0-100%) WI = 0 Clip Data Past Bottom (0 = OFF, 1 = ON) WJ = 1 Rcvr Gain Select (0 = Low, 1 = High) WM = 1 Profiling Mode (1-8) WN = 100 Number of depth cells (1-128) WP = 00001 Pings per Ensemble (0-16384) WS= 0800 Depth Cell Size (cm) WT = 000 Transmit Length (cm) [0 = Bin Length] WV = 0390 Mode 1 Ambiguity Velocity (cm/s radial) Figure 2.6.1: Current profile along the ship’s track, about 110m to 136m depth, averaged every 60 minutes (Leg1). Figure 2.6.2: Current profile along the ship’s track, about 110m to 135m depth, averaged every 60 minutes (Leg2). 2.7 XCTD September 16, 2014 (1) Personnel Hiroshi Uchida (JAMSTEC) Ryo Oyama (GODI) (Leg 1) Souichiro Sueyoshi (GODI) (Leg 1) Katsuhisa Maeno (GODI) (Leg 1) Koichi Inagaki (GODI) (Leg 1) Yutaro Murakami (GODI) (Legs 1 and 2) Wataru Tokunaga (GODI) (Leg 2) Kazuho Yoshida (GODI) (Leg 2) Tetsuya Kai (GODI) (Leg 2) (2) Objectives In this cruise, XCTD (eXpendable Conductivity, Temperature and Depth profiler) measurements were carried out to substitute for CTD measurements and to evaluate the fall rate equation and temperature by comparing with CTD (Conductivity, Temperature and Depth profiler) measurements. (3) Instrument and Method The XCTD used was XCTD-4 (Tsurumi-Seiki Co., Ltd., Yokohama, Kanagawa, Japan) with an MK-150N deck unit (Tsurumi-Seiki Co., Ltd.). The manufacturer’s specifications are listed in Table 2.7.1. In this cruise, the XCTD probes were deployed by using 8-loading automatic launcher or hand 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 (P10N_1, P10N_7, P10N_14, P10N_30, P01_77, P01_78, P01_80 and P01_81). 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 2.7.2). (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. 2.7.1. The terminal velocity error was estimated for the XCTD-4 (Table 2.7.2). The XCTD 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. 2.7.2). The XCTD data used were corrected for the depth error. Average thermal bias below 900 dbar was 0.011°C. Mean of the thermal biases of XCTD data estimated from five cruises was 0.014 ± 0.004°C (Table 2.7.3). The XCTD data were corrected for the mean thermal bias (0.014°C). Differences of salinity on pressure surfaces were examined by using side-by-side XCTD and CTD data (Fig. 2.7.3). The XCTD data used were corrected for the depth error and thermal bias. Average salinity bias was 0.013 ± 0.007 (Table 2.7.4). The XCTD data were corrected for the salinity bias. Temperature-salinity plot using the quality controlled XCTD data is shown in Fig. 2.7.4. (5) 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 Data Book, 187 pp., JAMSTEC. Table 2.7.1: Manufacturer’s specifications of XCTD-4. Parameter Range Accuracy ———————————— ——————————————— ————————————————————————————————— Conductivity 0 ~ 60 mS cm–1 ± 0.03 mS cm–1 Temperature –2 ~ 35°C ± 0.02 °C Depth 0 ~ 1850 m 5 m or 2%, whichever is greater * ———————————————————————————————————————————————————————————————— * Depth error is shown in Kizu et al (2008). Table 2.7.2: Manufacturer’s coefficients for the fall-rate equation. Model a (terminal b (acceleration, e (terminal velocity velocity, m/s) m/s2) error, m/s) —————— —————————————— ———————————————— ———————————————————— XCTD-4 3.68081 0.00047 –0.0075 —————————————————————————————————————————————————————————————— Table 2.7.3: Thermal biases of the XCTD temperature data. Cruise Average thermal Depth range Source bias (°C) ——————— ——————————————— ———————————— ———————————————————— 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 This report Mean 0.014 ± 0.004 Table 2.7.4: Salinity bias of the XCTD data. Cruise Average salinity bias Data ——————— ————————————————————— ————————————————————————————————————— MR14-04 0.013 ± 0.007 Stations 1, 7, 14, 30, 77, 78, 80, 81 ————————————————————————————————————————————————————————————————————— Figure 2.7.1: Differences between XCTD and CTD depths for XCTD-4. Differences were estimated with the same method as Uchida et al. (2011). Standard deviation of the estimates (horizontal bars) and the manufacturer’s specification for XCTD depth error (dotted lines) are shown. The regressions for the data (solid line) and for the data obtained in the cruise MR12-05 (broken line) are also shown. Figure 2.7.2: 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 2.7.3: Comparison between XCTD and CTD salinity profiles. (a) Mean salinity of CTD profiles with standard deviation (shade) and (b) mean salinity 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 2.7.4: Comparison of temperature-salinity profiles of CTD (green lines) data used for the XCTD salinity bias estimation and salinity bias-corrected XCTD (red and black lines) data. 3 Hydrographic Measurements 3.1 CTDO2 Measurements April 20, 2015 (1) Personnel Hiroshi Uchida (JAMSTEC) Shinsuke Toyoda (MWJ) Hiroshi Matsunaga (MWJ) Rei Ito (MWJ) Akira Watanabe (MWJ) Kenichi Katayama (MWJ) (leg 1) Tomoyuki Takamori (MWJ) (leg 2) 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 8500 m of 9.53 mm armored cable (Ocean Cable and Communications Co., Yokohama, Kanagawa, Japan). (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 optode (RINKO-III; JFE Advantech Co., Ltd, Kobe Hyogo, Japan), a fluorometer (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), a colored dissolved organic matter (ECO FL CDOM, WET Labs, Inc., Philomath, Oregon, USA), and an UV nitrate sensor (Deep SUNA, Satlantic, LP, Halifax, Nova Scotia, Canada) 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 x 90 cm). An additional set of SBE 911plus CTD system with 12-position SBE 32 was also used for four shallow casts (stations 73_4, 73_5, 124_2, and 124_3) for water sampling for phytoplankton incubation in leg 2. The SBE 9plus was mounted horizontally in a 12-position carousel frame. The 12-litre Niskin-X water sample bottles (General Oceanics, Inc.) were carefully cleaned and stored for the water sampling. 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 09P54451-117457 (pressure sensor S/N: 1027) Temperature sensor: SBE 3plus, S/N 4811 (primary) SBE 3, S/N 1359 (secondary) Conductivity sensor: SBE 4, S/N 2435 (primary) SBE 4, S/N 2854 (secondary) Oxygen sensor: SBE 43, S/N 0394 (stations from 001 to 057) SBE 43, S/N 0330 (stations from 058 to 150) JFE Advantech RINKO-III, S/N 0024 (foil batch no. 144002A) Pump: SBE 5T, S/N 4595 (primary) SBE 5T, S/N 4598 (secondary) Altimeter: PSA-916T, S/N 1157 Deep Ocean Standards Thermometer: SBE 35, S/N 0022 Fluorometer: Seapoint Sensors, Inc., S/N 3618 (measurement range: 0-5 μg/L) Transmissometer: C-Star, S/N CST-1363DR PAR: Satlantic LP, S/N 0049 CDOM: ECO FL CDOM, S/N 2014 (measurement range: 0-500 ppb) Nitrate: Deep SUNA, S/N 0385 (used only for stations 001_2, 007_1, 014_1, and 030_1) Carousel Water Sampler: SBE 32, S/N 0924 (stations from 001_1 to 001_2) SBE 32, S/N 0391 (stations from 007_1 to 150_1) Water sample bottle: 12-litre Niskin-X model 1010X (no TEFLON coating) 12-position Carousel system (used for water sampling for phytoplankton incubation) Deck unit: SBE 11plus, S/N 11P54451-0872 Under water unit: SBE 9plus, S/N 09P27443-79511 (pressure sensor S/N: 0677) Temperature sensor: SBE 3, S/N 1524 Conductivity sensor: SBE 4, S/N 1088 Pump: SBE 5T, S/N 3118 Carousel Water Sampler: SBE 32, S/N 0278 Water sample bottle: 12-litre Niskin-X model 1010X (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. S/N 1027, 4 February 2011 S/N 0677, 5 March 2014 The time drift of the pressure sensor is adjusted by periodic recertification corrections against a deadweight 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 1027, 9 April 2014 slope = 0.99995022 offset = -0.74973 S/N 0677, 9 April 2014 slope = 0.99972807 offset = -0.10585 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 4811, 18 January 2014 S/N 1359, 1 May 2014 S/N 1524, 12 November 2013 Pressure sensitivities of SBE 3s were corrected according to a method by Uchida et al. (2007), for the following sensors. S/N 4811, -2.7192e-7 [°C/dbar] S/N 1359, -1.8386e-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 2435, 1 May 2014 S/N 2854, 1 May 2014 S/N 1088, 17 July 2013 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 0394, 29 April 2014 S/N 0330, 29 April 2014 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; Uchida et al., 2015b). 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. From the end of 2011, the SBE has been applying a NIST correction to the fixed-point cells used for the calibration. S/N 0022, 3 September 2013 (slope and offset correction) Slope = 1.000006 Offset = 0.000187 The time required per sample = 1.1 x 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 = 0.007 (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 x T + C2 x T2 V0 = 1 + C3 x T V = C4 + C5 x 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. The coefficients of the equation by García and Gordon (1992) were modified based on the laboratory experiment (Uchida et al., in prep.) and used for the compensation (B0 = –6.33568e–3, B1 = –6.84389e–3, B2 = –1.18326e–2, B3 = –5.51960e–2, C0 = 3.40543e–6). Pre-cruise sensor calibrations were performed at RCGC/JAMSTEC. S/N 0024, 14 May 2014 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) x 100 cp = – (1 / 0.25) ln(Tr / 100) The calibration coefficients were determined by using the data obtained in the R/V Mirai MR13-06 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 2014, 21 September 2010 Dark Counts: 0.027 V Scale Factor: 101 ppb/V Maximum Output: 4.94 V xii. Deep SUNA The SUNA (Submersible Ultraviolet Nitrate Analyzer) is a chemical-free nitrate sensor (Satlantic, LP, Halifax, Nova Scotia, Canada). It is based on the ISUS (In Situ Ultraviolet Spectroscopy) technology developed at Monterey Bay Aquarium Research Institute (MBARI). The Deep SUNA housing is made from anodized aluminum. The housing is designed to withstand depths of up to 2000 m. The SUNA measures the concentration of dissolved nitrate in water. The sensor illuminates the water sample with its deuterium UV light source, and measures the throughput using its photo-spectrometer. The difference between this measurement and a prior baseline reference measurement of pure water constitutes an absorption spectrum. Absorbance characteristics of natural water components are provided in the sensor calibration file. The Beer-Lambert Law for multiple absorbers establishes the relationship between the total measured absorbance and the concentrations of individual components. Based on this relationship, the sensor obtains a best estimate for the nitrate concentration using multi- variable linear regression. The Deep SUNA was used with the CTD system as an auxiliary analog sensor at shallow casts in leg 1 (stations 001_2, 007_1, 014_1, and 030_1), since it is designed to operate down to 2000 m and it was used with the Continuous Sea Surface Water Monitoring System (see Section 2.4) in leg 2. (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 (20 seconds from station 049_1 to save the observation time) 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, the bottle was exceptionally fired after waiting from the stop for 60 seconds (50 seconds from station 049_1 to save the observation time) 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 (or 12-bottles) SBE 32 Carousel Water Sampler with 12-litre Niskin-X bottles. Before a cast taken water for CFCs, the bottle frame and Niskin-X bottles were wiped with acetone. Data acquisition software SEASAVE-Win32, version 7.23.2 ii. Data collection problems (a) Miss trip, miss fire, and remarkable leak Niskin bottles did not trip correctly at the following stations. Miss trip Miss fire Remarkable leak 140_1, #16 001_1, #6 074_1 ~ 093_1, #3 001_2, #24 Since all of the latch assemblies for the SBE 32 (S/N 0924) was defective, the SBE 32 was replaced from S/N 0924 to S/N 0391 after the station 001_2. Also, the latch assembly for #16 of S/N 0391 was replaced after the station 140_1. The bottle sampled salinity data were relatively lower (about 0.001) than the CTD salinity data for the bottle #3 at stations from 074 to 093. The drain cock of the bottle #3 was replaced after the station 094_1. (b) Failure of insulation of the CTD winch armored cable Failure of insulation of the CTD winch armored cable occurred at 2608 dbar of up cast of the station 041_1. Therefore, the up cast was aborted and the armored cable was cut 1620 m after the cast. (c) Detachment of some sensors at deep casts deeper than 6000 m Fluorometer, transmissometer, CDOM, LADCP, and Micro Rider were detached at stations 047_1, 046_1, 045_1, and 044_1, because of the withstand depth of 6000 m for these sensors. At stations 001_1, 080_1, 081_1, 088_1, and 089_1, the CTD package was lowered depths up to 6000 m without detachment of these sensors, although water depths of these stations were deeper than 6000 m. (d) Noise of SBE 43 (S/N 0394) Relatively large noise was found in the SBE 43 data at about 4762~4789 dbar of down cast. Therefore, the SBE 43 was replaced from S/N 0394 to S/N 0330 after the station 056_1. (e) Noise of primary temperature and salinity data The primary temperature and/or salinity data were noisy for down cast of following stations: 074_1 and 145_1. Therefore, the secondary temperature and salinity data were used for these stations for vertical profile (wct file). The primary temperature and/or salinity data were noisy for up cast of following stations: 050_1, 144_1, and 145_1. Therefore, the secondary temperature and salinity data were used for these stations for bottle data (seafile). (f) Noise of transmissometer The transmissometer data were (partly) noisy for down cast at following stations: 022_1, 043_1, 057_1, 065_1, 077_1, 079_1, 080_1, 089_1, 091_2, 092_1, 095_1, 097_1, 126_1, 130_1, 141_1, 142_1, and 145_1. Therefore, the up cast data were used for vertical profile data (wct file) for these stations instead using the down cast 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 (or 1 second for the bottle fired without stop). 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 6 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. 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 (sq). SPLIT was used to split data into the down cast and the up cast. Remaining spikes in the CTD data were manually eliminated from the 1-dbar-averaged data. The data gaps resulting from the elimination were linearly interpolated with a quality flag of 6. (6) Post-cruise calibration i. Pressure The CTD pressure sensor offset in the period of the cruise was estimated from the pressure readings on the ship deck. For best results the Paroscientific sensor was powered on for at least 20 minutes before the operation. In order to get the calibration data for the pre- and post-cast pressure sensor drift, the CTD deck pressure was averaged over first and last one minute, respectively. Then the atmospheric pressure deviation from a standard atmospheric pressure (14.7 psi) was subtracted from the CTD deck pressure to check the pressure sensor time drift. The atmospheric pressure was measured at the captain deck (20 m high from the base line) and sub-sampled one-minute interval as a meteorological data. Time series of the CTD deck pressure is shown in Fig. 3.1.1. 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 (–0.04 dbar) from the pre- cruise calibration. The post-cruise correction of the pressure data is not deemed necessary for the pressure sensor. Figure 3.1.1: 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 was performed at SBE, Inc in February 2015. S/N 0022, 4 February 2015 (2nd step: fixed point calibration) Slope = 1.000007 Offset = 0.000246 Offset of the SBE 35 data from the pre-cruise calibration was estimated to be smaller than 0.1 mK for temperature smaller than 4.5.C. So the post-cruise correction of the SBE 35 temperature data was not deemed necessary for the SBE 35. The CTD temperature was preliminary calibrated as Calibrated temperature = T – (c0 x P + c1 x 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 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 Figs. 3.1.2 and 3.1.3. Table 3.1.1: Calibration coefficients for the CTD temperature sensors. Serial number c0 (°C/dbar) c1 (°C/day) c2 (°C) ————————————— ———————————— ——————————— ——————— 4811 -1.29748e-8 4.02418e-6 -0.0003 1359 1.67653e-8 5.20248e-6 -0.0002 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 950 dbar. Number of data used is also shown. Serial number Pressure ≥ 950 dbar Pressure < 950 dbar ——————————————————— ——————————————————— Number Mean Sdev Number Mean Sdev (mK) (mK) (mK) (mK) ————————————— —————— ———— —————— —————— ———— ————— 4811 1544 -0.0 0.2 2756 -0.1 11.7 1359 1546 0.0 0.2 2774 0.3 9.1 ———————————————————————————————————————————————————————— Figure 3.1.2: 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. Figure 3.1.3: Same as Fig. 3.1.2, but for secondary temperature sensor. 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 x C + c1 x P + c2 x C x P + c3 x t + c4 where C is CTD conductivity in S/m, P is pressure in dbar, t is time in days from 11 July 2009, 00:58 (UTC) and c0, c1, c2, c3 and c4 are calibration coefficients. The best fit sets of coefficients were determined by a least square technique to minimize the deviation from the conductivity calculated from the bottle salinity data. The primary conductivity data created by the software module ROSSUM were basically used after the post-cruise calibration for the temperature data. The secondary conductivity sensor was also calibrated and used instead of the primary conductivity data when the data quality of the primary temperature or conductivity data was bad. 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 Figs. 3.1.4 and 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) [S/(m day)] (S/m) —————— ——————————— ———————————— ——————————— ——————————— —————————— 2435 -7.51283e-5 2.42062e-7 -6.89235e-8 -5.29014e-7 1.93028e-4 2854 -2.18278e-4 -1.62860e-7 5.27345e-8 1.50084e-6 5.46236e-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 —————— —————— ———— ———— —————— ———— ———— 2435 1574 0.0 0.4 2105 -0.9 7.3 2854 1580 0.0 0.5 2140 -0.9 7.5 Figure 3.1.4: 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. Figure 3.1.5: Same as Fig. 3.1.4, but for secondary salinity. iv. Oxygen The RINKO oxygen optode (S/N 0024) was calibrated and used as the CTD oxygen data, since the RINKO has a fast time response. The pressure-hysteresis corrected RINKO data was calibrated by the modified Stern-Volmer equation, basically according to a method by Uchida et al. (2010) with slight modification: [O2] (μmol/l) = [(V0 / V)1.1 – 1] / Ksv and Ksv = C0 + C1 x T + C2 x T2 V0 = 1 + C3 x T V = C4 + C5 x Vb + C6 x t + C7 x t x 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 for each leg. 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 4.08789e-3 c1 1.58333e-4 c2 2.10854e-6 c3 -1.14204e-3 c4 -0.109961 c5 0.356093 c6 -2.55873e-4 c7 3.13918e-4 cp 0.014 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 number Pressure ≥ 1950 dbar Pressure < 1950 dbar Number Mean Sdev Number Mean Sdev [μmol/kg] [μmol/kg] ————————————— ————— ————— ———— —————— ———— ———— 0024 1571 -0.03 0.30 2100 0.01 1.50 Figure 3.1.6: Difference between the CTD oxygen and the bottle oxygen for leg 1. Blue and red dots indicate before and after the post-cruise calibration, respectively. Lower two panels show histogram of the difference after the calibration. Correction of down cast RINKO profiles for pressure hysteresis 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 empirically determined before the R/V Mirai cruise MR12- 05 and used for the cruises MR12-05 and MR14-04 as follows: H1 = 0.007 (for serial no. 0024) H2 = 5000 dbar H3 = 2000 seconds. However, it was found that magnitude of the time-dependent, pressure-induced hysteresis was changed in time (Fig. 3.1.7). Although to determine the calibration coefficients (H1, H2, and H3) and to reprocess from the raw RINKO data is the best way for correction of the hysteresis, it is actually quite time-consuming to reprocess. Therefore, the discrepancy between the down and up cast profiles for depths deeper than 300 dbar were simply corrected by using a model as a function of pressure and the maximum pressure of the cast as follows: Ocor = O + Cx(pmax-300)/(6500.0-300.0)xsin(π/(pmax-300.0)x(P-300.0)) where O is the RINKO oxygen in μmol/kg before the correction, P is pressure in dbar, pmax is maximum pressure of the CTD cast, and C is correction factor. The correction factor C was estimated to be 0.3, 0.5 and 0.7 for MR12-05 leg 2, MR12-05 leg 3, and MR14-04 cruise, respectively. Figure 3.1.7: Difference between down and up cast CTD oxygen. Data at depths shallower than 300 dbar were compared on the same pressure surface and data at depths deeper than 300 dbar were compared on the same density surface (potential density with a reference pressure of 2500 dbar). Large dots indicate median value estimated from the data obtained at depths shallower than 300 dbar or at depths deeper than 300 dbar at 1000-dbar intervals. v. Fluorometer The CTD fluorometer (FLUOR in μg/L) was calibrated by comparing with the bottle sampled chlorophyll-a as FLUORc = c0 + c1 x 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), see Section 2.3] 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., 2015a). Sensitivity of the fluorometer to chlorophyll a may be also different between high and low temperature (see Section 2.4). Therefore, the slopes (c1) of the calibration coefficients are determined for three groups of stations: stations south of 38.8°N in leg 1 (001, 007, 014, and 022), the closest station to the coast (036), and other stations (Fig. 3.1.8). For the last group of stations, sensitivity of the fluorometer to chlorophyll a change at about 0.3 μg/L of the fluorometer data, so that the slope (c1) is changed for the fluorometer data larger than 0.3 μg/L. 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. 3.1.9. Figure 3.1.8: 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. Stations c0 c1 Note —————————————————— ——————————— ———————— —————————————————————————— 001, 007, 014, 022 -1.64441e-2 0.691796 036 -1.64441e-2 0.783024 Other stations -1.64441e-2 0.630088 Fluorometer data ≤ 0.3 g/L 9.75510e-2 0.250104 Fluorometer data > 0.3 g/L 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 —————— —————————— ————————— 221 -0.00 μg/L 0.08 μg/L Figure 3.1.9: 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) x 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. 3.1.10), Vr is expressed as Vr = c0 + c1 x t + c2 x t2 where t is working time (in days) of the transmissometer, and c0, c1, and c2 are calibration coefficients. The calibration coefficients are listed in Table 3.1.9. For stations 066 and 097, Vr shifted though Vd was same as others. Therefore, Vr was individually estimated as to be 4.6166 and 4.6044 for stations 066 and 097, respectively. In addition, the transmissometer data for station 141_1 was also corrected with an offset of +0.0055 volts. Figure 3.1.10: Time series of an output signal (voltage) from transmissometer at on deck before CTD casts (Vair) and deep ocean (Vdeep). The black solid line indicates the modeled signal in the deep clear ocean. Table 3.1.9: Calibration coefficients for the CTD transmissometer. Leg c0 c1 c2 Vd ——— ——————— ——————————— —————————— —————— 1 4.65763 -2.28408e-2 - 0.0012 2 4.64582 -2.91438e-3 5.23667e-5 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. viii. 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), since the data was noisy (Fig. 3.1.11). Moreover, the data were flagged as 4 (bad measurement) for depths deeper than about 4500 m due to large shift of the data (Fig. 3.1.11). Figure 3.1.11: An example of vertical profile of the CDOM sensor (station 100). Blue line shows original data and red line shows low- pass filtered data. ix. Deep SUNA The down and up cast profile from the Deep SUNA showed relatively large difference (Fig. 3.1.12). Maximum difference between the down and up cast data was about 0.084 volts and it corresponded to 4 μmol/kg of nitrate (Fig. 3.1.13). Since average of the down and up cast data at same pressure surface showed better linearity against the bottle sampled nitrate data (Fig. 3.1.13), nitrate from the Deep SUNA (NRA in μmol/kg) was estimated from the average data (NRAVave in volts) by comparing with the bottle sampled nitrate data as NRA = c0 + c1 x NRAVave where c0 and c1 are calibration coefficients. The calibration coefficients are listed in Table 3.1.10. The average of the down and up cast data was used for the bottle sampled data (seafile) and profile data (wct file). Table 3.1.10: Calibration coefficients for the Deep SUNA. number of comparison c0 c1 Sdev ———————————————————— ———————— ——————— ———————————— 43 –5.84651 22.7101 0.53 μmol/kg Figure 3.1.12. Vertical profiles of raw data (voltage) of the Deep SUNA (red line: down cast, black line: upcast) and temperature (blue line). Figure 3.1.13. Comparison of the Deep SUNA output (voltage) and the bottle sampled nitrate. Upper panels are for down cast, middle panels are for up cast, and lower panels are for average of the down and up cast for the Deep SUNA data. The regression lines for the average data are shown. (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 GOSHIP 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 (eds.) (2015a): WHP P14S, S04I Revisit in 2012 Data Book, 187 pp., JAMSTEC. Uchida, H., T. Nakano, J. Tamba, J.V. Widiatmo, K. Yamazawa, S. Ozawa and T. Kawano (2015b): Deep ocean temperature measurements 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 September 10, 2014 (1) Personnel Hiroshi Uchida (JAMSTEC) Tatsuya Tanaka (MWJ) Sonoka Wakatsuki (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 62827), which was modified by adding a 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 22.5 to 24.5°C, while the bath temperature was stable and varied within ±0.002°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 collect31 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 the0.00003, 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 3 to 18 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 4584 water samples were measured during the cruise. (4) Results i. Standard Seawater Standardization control was set to 512. The value of STANDBY was 5392 or 5393±0001 and that of ZERO was 0.00000 or -0.00001. We used IAPSO Standard Seawater batch P156 whose conductivity ratio is 0.99984(double conductivity ratio is 1.99968) as the standard for salinity measurement. We measured 188 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 0.0003 in salinity. Figure 3.2.1: History of double conductivity ratio measurement of the Standard Seawater (P156). Horizontal and vertical axes represent date and double conductivity ratio, respectively. Blue dots indicate raw data and red 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 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 675 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 of the absolute deference was 0.0002. Figure 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 We took 37 pairs of duplicate samples collected from the different Niskin bottle at same depth. Histogram of the absolute difference between duplicate samples is shown in Fig. 3.2.3. The root-mean-square of the absolute deference was 0.0003. Fig. 3.2.3: Histogram of the absolute difference between duplicate samples. Horizontal axis is absolute difference in salinity and vertical axis is frequency. (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 November 25, 2014 (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 ninetysix 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°C) 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°C 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°C 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) x 0.000411 [kg m–3]. The offset correction was verified by measuring Reference Material for Density in Seawater (prototype Dn-RM1 and Pre 18) 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°C) with TEOS-10. (4) Results Results of density measurements of the Reference Material for Density in Seawater (Dn-RM1 and Pre 18) were shown in Table 3.3.1 and Table 3.3.2. Mean densities of the Dn-RM1 and Pre 18 were in good agreement with the measurements before the reevaluation of the offset of density measurements (Table 3.3.2). A total of 16 pairs of replicate samples were measured. The root-mean square of the absolute difference of replicate samples was 0.0008 g/kg. The measured density salinity anomalies (δSA) are shown in Fig. 3.3.1. The measured δSA 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 (sample no.) Dn-RM1 (kg/m3) —————————— ——————————————— ——————————————— —————————————— Leg 1 2014/07/11 001 1024.2625 2014/07/12 007,014 1024.2649 2014/07/14 022,030 1024.2645 Leg 2 2014/07/18 036,037,038,040 1024.2641 2014/07/19 045 1024.2627 2014/07/20 043 1024.2622 2014/07/21 051 1024.2643 2014/07/25 060 1024.2617 2014/07/27 067 1024.2632 2014/07/29 073 1024.2621 2014/08/01 079 1024.2619 2014/08/03 089 1024.2615 2014/08/05 095 1024.2613 2014/08/07 101 1024.2621 2014/08/11 110 1024.2625 2014/08/14 120 1024.2618 2014/08/16 128 1024.2631 2014/08/17 151 1024.2620 2014/08/20 136 1024.2623 2014/08/22 140,143 1024.2639 Stn. 140 #16: Miss trip (flag 4) 2014/08/23 145,147 1024.2621 2014/08/24 148,149,150 1024.2618 Average: 1024.2627 ± 0.0010 Table 3.3.2: Comparison of density measurement of the Reference Material for Density in Seawater (prototype Dn-RM1 and Pre 18). Date Serial no. Density [kg/m3] Note ———————————— —————————— ———————————————————— ——————————————— Measurements on this cruise Pre 18 2014/07/23 270 1024.2222 2014/08/18 150 1024.2216 2014/08/18 309 1024.2219 2014/08/20 370 1024.2223 2014/08/22 289 1024.2223 Average: 1024.2221 ± 0.0003 Dn-RM1 2014/07/11- 1024.2627 ± 0.0010 See Table 3.3.1 2014/08/24 Recent measurements before this cruise Pre 18 2014/03/27- 1024.2216 ± 0.0012 4 bottles 2014/04/06 Dn-RM1 2014/04/03-06 1024.2623 ± 0.0007 8 bottles ——————————————————————————————————————————————————————————————— 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 August 26, 2014 (1) Personnel Yuichiro Kumamoto (Japan Agency for Marine-Earth Science and Technology) Misato Kuwahara (Marine Works Japan Co. Ltd) Keitaro Matsumoto (Marine Works Japan Co. Ltd) Katsunori Sagishima (Marine Works Japan Co. Ltd) Haruka Tamada (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 MR14- 04 cruise, we measured dissolved oxygen concentration from surface to bottom layers at all the hydrocast stations in the North Pacific Ocean. All the stations reoccupied the WOCE Hydrographic Program P10N (Leg- 1) and P01 (Leg-2) stations in the 1990s. Our purpose is to evaluate temporal change in dissolved oxygen concentration in the North Pacific Ocean during the past decades. (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): Wako Pure Chemical Industries, Ltd., volumetric standard, reference material for iodometry, Lot No. TLG0272, Purity: 99.97 ± 0.04% CSK standard of potassium iodate: Lot TLM1372, 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 (ARO-PR, JFE Advantech Co. Ltd.) that was calibrated with a standard thermometer (SBE 3plus, Sea-Bird Electronics, Inc.). 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-7 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 0.02 ± 0.01% (n = 36), 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 x 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-7 and DOT-8 were 0.000 ± 0.001 (standard deviation, S.D., n=18) and 0.000 ± 0.001 (S.D., n=18) cm3, respectively. Table 3.4.1: Results of the standardization (End point, E.P.) and the blank determinations (cm3). DOT-7 DOT-8 ————————————— ————————————— Date(UTC) KIO3 No. Na2S2O3 No. E.P. blank E.P. blank Stations ————————— ———————— ——————————— ————— —————— ————— —————— ————————————— 2014/7/10 K1404B01 T1406A 3.957 -0.002 3.960 -0.002 001, 007, 014, 022, 030 2014/7/16 K1404B02 T1406C 3.956 0.000 3.961 -0.001 036, 037, 038, 039, 040, 047, 046, 045, 044, 041, 042, 043, 048, 049, 050, 051, 052, 053, 054 2014/7/22 K1404B03 T1406D 3.957 0.000 3.963 -0.001 055, 056, 057, 058, 059, 060, 061, 062, 063, 064, 065, 066, 067, 068 2014/7/26 K1404B04 T1406D 3.958 0.001 3.962 0.001 069, 070, 071, 072, 073, 074, 075, 076, 077, 078 2014/7/30 K1404B05 T1406E 3.958 0.001 3.958 0.000 079, 080, 081, 082, 083, 084, 085, 086, 087, 088, 089, 090, 091, 092, 093, 094, 095, 096, 097 2014/8/5 K1404B06 T1406E 3.956 0.000 3.962 -0.001 098, 099, 100, 101, 102, 103, 104 2014/8/8 K1404B07 T1406F 3.957 0.001 3.958 -0.001 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118 2014/8/13 K1404B09 T1406F 3.955 0.002 3.959 0.000 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 151 2014/8/17 K1404C01 T1406G 3.956 0.001 3.958 0.000 129, 130, 131, 132, 133, 134, 135, 136 2014/8/20 K1404C02 T1406G 3.955 0.000 3.958 0.000 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150 (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 447 (Fig. 3.4.1). The standard deviation of the replicate measurement was 0.12 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 (Data from Stn. 139-1 #35: 0.79 and Stn. 146-1 #35: 4.00 (μmol kg-1)2 are not shown in this figure). (10) Duplicate sample measurement During the Leg-2 duplicate sampling were taken 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 equivalent with that of the replicate measurements (0.12 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 TLM1372) against our KIO3 standards as samples before and during the cruise (Table 3.4.3). A good agreement among them confirms that there was no systematic shift in our oxygen analyses between preparation of our KIO3 standards onshore and the sample measurements on board. (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 3.4.4). 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 flagged 4. e. If the bottle flag was 4 (did not trip correctly), a datum was flagged 4 (bad). In case of the bottle flag 3 (leaking) or 5 (unknown problem), a datum was flagged based on steps a, b, c, and d. Table 3.4.2: Results of duplicate sample measurements. Duplicated Duplicated Dissolved oxygen Leg Stns Niskin # Niskins Pres.(db) (μmol/kg) ——— ———— —————————— ——————————— —————————— ———————————————— 1 2 042 2-9 X12J02, 03, 4000 150.62 150.54 04, 05, 06, 150.56 150.63 07, 08 ,09 150.68 150.53 150.49 150.44 2 2 048 1, (2) X12J01 5575 160.04 159.98 3 2 049 (4), 10 X12J10 5330 159.42 159.25 4 2 051 (4), 11 X12J11 5250 159.90 160.04 5 2 052 (5), 12 X12J12 5080 159.06 159.29 6 2 053 (4), 13 X12113 5170 160.64 160.54 7 2 055 (4), 14 X12J14 5330 160.77 160.72 8 2 056 (3), 15 X12J15 5420 163.02 162.98 9 2 057 (3), 16 X12J16 5500 160.68 160.60 10 2 059 (4), 17 X12J17 5170 159.17 159.10 11 2 061 (5), 18 X12J18 5080 157.19 157.17 12 2 062 (4), 19 X12J19 5170 157.33 157.42 13 2 063 (5), 20 X12J20 5000 157.24 157.34 14 2 064 (4), 21 X12J21 5330 157.35 157.23 15 2 065 (4), 22 X12J22 5170 158.59 158.63 16 2 066 (4), 23 X12J23 5250 157.28 157.20 17 2 068 (4), 24 X12J24 5170 157.09 157.13 18 2 069 (6), 25 X12J25 4750 157.17 157.05 19 2 070 (6), 26 X12J26 4830 156.52 156.46 20 2 071 (6), 27 X12J27 4670 155.65 155.44 21 2 072 (5), 28 X12J28 5000 157.30 157.11 22 2 074 (3), 29 X12J29 5420 159.10 159.25 23 2 075 (3), 30 X12J30 5500 157.10 157.05 24 2 082 (5), 31 X12J31 5080 156.15 155.97 25 2 083 (8), 32 X12J32 4170 150.07 149.90 26 2 086 (9), 33 X12J33 3920 147.63 147.43 27 2 090 (3), 34 X12J34 5500 155.63 155.68 28 2 094 (3), 35 X12J35 5580 154.33 154.23 29 2 096 (3), 36 X12J36 5500 152.86 152.84 30 2 106 (2), 3 X12J03 5580 152.84 152.63 31 2 107 (2), 3 X12J03 5420 151.88 151.69 Table 3.4.3: Results of the CSK standard (Lot TLM1372) measurements. DOT-5 - Date KIO3 ———————————————————— ————————————————— (UTC) ID No. Conc. (N) error (N) - - Remarks —————————— ———————— ————————— ————————— ————————— ———————— —————————————— 2014/05/13 K1404A01 0.010012 0.000005 Onshore lab. 2014/05/14 K1404C12 0.010013 0.000003 Onshore lab. 2014/05/15 K1404I12 0.010010 0.000002 Onshore lab. DOT-7 DOT-8 ———————————————————— ——————————————————— Conc. (N) error (N) Conc. (N) error (N) —————————— ———————— ————————— ————————— ————————— ———————— —————————————— 2014/06/09 K1404A09 0.010009 0.000004 0.010005 0.000003 MR14-03 2014/07/10 K1404B01 0.010005 0.000003 0.010004 0.000005 MR14-04 Leg-1 2014/08/17 K1404C01 0.010007 0.000004 0.010006 0.000003 MR14-04 Leg-2 Table 3.4.4: Summary of assigned quality control flags. Flag Definition Number* ———— ——————————————————— ——————— 2 Good 3714 3 Questionable 1 4 Bad 4 5 Not report (missing) 2 Total 3721 *Replicate samples (n = 447) 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 October 14, 2016 (ver.2.2) (1) Personnel Michio AOYAMA (JAMSTEC / Fukushima University, Principal Investigator) Leg 1 Yasuhiro ARII (Department of Marine Science, Marine Works Japan Ltd.) Minoru KAMATA (Department of Marine Science, Marine Works Japan Ltd.) Tomomi SONE (Department of Marine Science, Marine Works Japan Ltd.) Leg 2 Yasuhiro ARII (Department of Marine Science, Marine Works Japan Ltd.) Kenichiro SATO (Department of Marine Science, Marine Works Japan Ltd.) Elena HAYASHI (Department of Marine Science, Marine Works Japan Ltd.) (2) Objectives The objectives of nutrients analyses during the R/V Mirai MR1404 cruise, WOCE P1 revisited cruise in 2014, in the North Pacific 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 P1 cruises in 2007, 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 129 QuAAtro 2-HR runs for the samples at 118 casts, 113 stations in MR1404. The total amount of layers of the seawater sample reached up to 3918 for MR1404. We made duplicate measurement at all layers, except for ammonium samples. (4) Instrument and Method (4.1) Analytical detail using QuAAtro 2-HR systems (BL-Tech) We applied three units of QuAAtro in this cruise. Unit 1 and Unit 2 were put for R/V Mirai equipment. Unit 3 was carried on R/V Mirai. Configurations of all three units are completely same for four parameters, Nitrate, Nitrite, Silicate and Phosphate, while Unit 3 has ammonium measurement channel as channel 5. 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-Naphthylethylenediamine 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 GOSHIP 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 and 0.2 ml 1% CuSO4 solution. 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% solution in ethanol) is added. N-1-Napthylethylene-diamine dihydrochloride, 0.004 M (0.1% w/v) Dissolve 1 g NED, 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. Stored in a dark bottle. Figure 3.5.1: NO3 + NO2 (1ch.) Flow diagram. note a: 5turn Cd coil were doubled during MR1404 cruise (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 NED, 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) Dissolved 50 g oxalic acid anhydrous, HOOC: COOH, in 950 ml of DIW. Ascorbic acid, 0.01 M (3% w/v) Dissolved 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) Dissolved 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 Dissolved 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 Dissolved 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 Dissolved 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 Mixed 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, 24 ± 2 degree Celsius, in about 30 minutes before use to stabilize the temperature of samples in MR1404. 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. 7 casts among 29 casts of samples for ammonium were drawn into a virgin 50 ml PE tubes and frozen using liquid nitrogen after the water sampling immediately. After that, these samples were stored in deep freezer, -70 degree Celsius. Frozen samples were thawed using water bath, 40 degree Celsius, and put on room temperature just before the measurement. Samples were transferred into the virgin 10 ml vial due to set an auto sampler tray directly. However we observed concentrations changes of ammonium for frozen samples stated above 7casts, we measured samples of remaining 22 casts as NOT frozen. (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 MBC cast we used surface CTD data. - Calibration curves to get nutrients concentration were assumed second order equations. (5) Nutrients standards (5.1) Volumetric laboratory ware of in-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 4 K. Volumetric flasks Volumetric flasks of Class quality (Class A) are used because their nominal tolerances are 0.05% or less over the size ranges likely to be used in this work. Class A flasks are made of borosilicate glass, and the standard solutions were transferred to plastic bottles as quickly as possible after they are made up to volume and well mixed in order to prevent excessive dissolution of silicate from the glass. High quality plastic (polymethylpentene, PMP, or polypropylene) volumetric flasks were gravimetrically calibrated and used only within 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 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, “sodium nitrite” provided by Wako, Lot. HLK7554, CAS No. 7632-00-0, was used. The assay of nitrite salts was determined according JIS K8019 and the result of the assay was 98.53%. We use that value to adjust the weights taken. 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 HC382250 are used. The silicate concentration is certified by NIST-SRM3150 with the uncertainty of 0.5%. HC382250 was certified as 1001 mg L-1. Treatment of silicate standard due to high alkalinity Since the silicon standard solution Merck CertiPUR. is in NaOH 0.5 mol/l, we need to dilute and neutralize to avoid make precipitation of MgOH2 etc. When we make B standard, silicon standard solution is diluted by factor 12 with pure water and neutralized by HCl 1.0 mol L-1 to be about 7. After that B standard solution is used to prepare C standards. Ultra pure water Ultra pure water (Milli-Q 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 is stored in 20 liter cubitainer with paper box. The concentrations of nutrient of this water were measured carefully in October 2014. (5.3) Concentrations of nutrients for A, B and C standards Concentrations of nutrients for A, B and C standards are set as shown in Table 3.5.1. The C standard is prepared according recipes as shown in Table 3.5.2. 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 reference material of nutrients in seawater and C-6 was in-house standard. Table 3.5.1: Nominal concentrations of nutrients for A, B and C standards. A B C-1 C-2 C-3 C-4 C-5 C-6 C-7 C-8 ———————— ————— ———— ——— ——— ——— ——— ——— ——— ——— ——— NO3(μM) 22500 900 BY BU CA BW BZ 54 - - NO2(μM) 4000 20 BY BU CA BW BZ 1.2 - - SiO2(μM) 35000 2760 BY BU CA BW BZ 166 - - PO4(μM) 3000 60 BY BU CA BW BZ 3.7 - - NH4(μM) 4000 200 - - - - - 6.0 2.0 0 Table 3.5.2: Working calibration standard recipes. C std. B-1 std. B-2 std. B-3 std. —————— ———————— ———————— ———————— C-6 25 ml 25 ml 15 ml C-7 - - 5 ml C-8 - - 0 ml ———————————————————————————————————————————————————— B-1 std.: Mixture of nitrate, silicate 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 3.5.3(a) to (c). Table 3.5.3(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) maximum a month 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 A-2 std.) maximum 8 days B-3 std. (dilute A-4 std.) maximum 8 days Table 3.5.3(b): Timing of renewal of in-house standards. Working standards Renewal —————————————————————————————————————— —————————————— C-6 std. (mixture of B-1 and B-2 std.) C-7 std. (dilute B-3 std.) every 24 hours C-8 (LNSW) Table 3.5.3(c): Timing of renewal of in-house standards for reduction estimation. Reduction estimation Renewal —————————————————————— ——————————————————— D-1 std. (3600 μM NO3) maximum 8 days 43 μM NO3 when C Std. renewed 47 μM NO2 when C Std. renewed (6) Reference material of nutrients in seawater 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 (hereafter RMNS) are prepared (Aoyama et al., 2006, 2007, 2008, 2009). 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 degree Celsius in potential temperature (Aoyama and Joyce, 1996). During the period from 2003 to 2010, 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). (6.1) RMNSs for this cruise RMNS lots BY, BU, CA, BW and BZ, which cover full range of nutrients concentrations in the North Pacific Ocean are prepared for MR1404. 87 sets of BY, BU, CA, BW and BZ are prepared. 59 bottles of RMNS lot BV are prepared for this cruise. Lot BV was analyzed at all stations to keep the comparability. These RMNS assignment were completely done based on random number. The RMNS bottles were stored at a room in the ship, REAGENT STORE, where the temperature was maintained around 20 - 24 degree Celsius. (6.2) Assigned concentration for RMNSs We assigned nutrients concentrations for RMNS lots BY, BU, CA, BW, BZ, and BV as shown in Table 3.5.4. (6.3) Homogeneity of RMNSs The homogeneity of lot BV used in MR1404 cruise and analytical precisions are shown in Table 3.5.5. These are for the assessment of the magnitude of homogeneity of the RMNS bottles those are used during this cruise. As shown in Table 3.5.5, the homogeneity of RMNS lot BV for nitrate, phosphate and silicate are the same magnitude of analytical precision derived from fresh raw seawater in January 2009. Table 3.5.4: Assigned concentration of RMNSs. unit: μmol kg–1 Nitrate Phosphate† Silicate†† Nitrite ———— ——————— —————————— —————————— ——————————————— BY* 0.07 0.041 1.58 0.03 BU** 3.96 0.348 20.79 0.07 CA* 19.65 1.423 36.57 0.07 BW* 24.59 1.545 59.67 0.08 BZ* 43.40 3.059 160.65 0.21 BV** 35.32 2.512 102.10 0.06 ———————————————————————————————————————————————————————————————— * The values are assigned for this cruise on 5 March 2014. ** The values are assigned for MR1205 cruise on 7 November 2012. † The values of phosphate are re-assigned on 28 October 2014 due to correct by LNSW offset. †† The values of silicate are re-assigned on June 2016 by one of Merck KGaA silicon standard solution 1000 mg L-1 Si traceable to National Institute of Standards and Technology (NIST) SRM of silicon standard solution (SRM3150). Table 3.5.5: The homogeneity of lot BV derived from simultaneous samples measurements and analytical precision onboard R/V Mirai in MR1404 and offshore laboratory at YOKOSUKA in 2012. Nitrate Phosphate Silicate CV% CV% CV% —————————————————————— ——————— ————————— ———————— BV (on board)* 0.12 0.15 0.12 BV (laboratory)** 0.10 0.12 0.08 Precision (on board) 0.09 0.08 0.07 Precision (laboratory) 0.16 0.07 0.08 ———————————————————————————————————————————————————— *: N = 125 **: N = 30 (7) Quality control (7.1) Precision of nutrients analyses during the 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 3.5.6 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 0.09% for nitrate, 0.08% for phosphate and 0.07% for silicate in terms of median of precision, respectively. An improvement of analytical precisions of all parameters was estimated that replacement roller of the pump that improvement as shown Table 3.5.6. The reason of relative poor precision observed was contamination of the sample line tube. Table 3.5.6: Summary of precision based on the replicate analyses for all unit. Nitrate Nitrite Silicate Phosphate Ammonium CV % CV % CV % CV % CV % ——————— ——————— ——————— ———————— ————————— ———————— Median 0.09 0.14 0.07 0.08 0.22 Mean 0.09 0.15 0.09 0.09 0.24 Maximum 0.31 0.54 0.27 0.31 0.49 Minimum 0.03 0.04 0.02 0.02 0.03 N 125 125 125 125 25 Table 3.5.6(a): Summary of precision based on the replicate analyses for unit 1. Nitrate Nitrite Silicate Phosphate Ammonium CV % CV % CV % CV % CV % ——————— ——————— ——————— ———————— ————————— ———————— Median 0.08 0.13 0.07 0.07 0.23 Mean 0.10 0.14 0.09 0.08 0.23 Maximum 0.31 0.34 0.27 0.31 0.33 Minimum 0.03 0.05 0.03 0.02 0.16 N 63 63 63 63 5 Table 3.5.6(b). Summary of precision based on the replicate analyses for unit 2. Nitrate Nitrite Silicate Phosphate Ammonium CV % CV % CV % CV % CV % ——————— ——————— ——————— ———————— ————————— ———————— Median 0.07 0.14 0.06 0.08 0.22 Mean 0.07 0.18 0.07 0.08 0.25 Maximum 0.14 0.54 0.12 0.14 0.49 Minimum 0.03 0.04 0.04 0.02 0.03 N 17 17 17 17 20 Table 3.5.6(c). Summary of precision based on the replicate analyses for unit 3. Nitrate Nitrite Silicate Phosphate Ammonium CV % CV % CV % CV % CV % ——————— ——————— ——————— ———————— ————————— ———————— Median 0.10 0.14 0.09 0.08 - Mean 0.10 0.15 0.09 0.09 - Maximum 0.22 0.29 0.21 0.24 - Minimum 0.03 0.05 0.02 0.03 - N 46 46 46 46 - Figure 3.5.6: Time series of precision of nitrate in MR1404 Figure 3.5.7: Time series of precision of phosphate in MR1404. Figure 3.5.8: Time series of precision of silicate in MR1404. (7.2) RMNS lot. BV measurement during this cruise RMNS lot. BV was measured every run to keep the comparability. 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. Figure3.5.9: Time series of RMNS-BV of nitrate in MR1404. Figure 3.5.10: Time series of RMNS-BV of phosphate in MR1404. Figure 3.5.11: Time series of RMNS-BV of silicate in MR1404. (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 3.5.7 and Figures 3.5.12 to 3.5.14. The carryover in silicate had a bias by equipment. It was 0.1%, mean value, at Unit 1 and Unit 2, R/V Mirai equipment. The other hand, it was 0.2%, mean value, at Unit 3. We carried out the maintenance for Unit 3 by cleaning of the glass coils and changing for new transmission tube before the stn. 144. The bias was clearly solved by the maintenance. Table 3.5.7: Summary of carry over throughout MR1404. Nitrate Nitrite Silicate Phosphate Ammonium CV % CV % CV % CV % CV % ——————— ——————— ——————— ———————— ————————— ———————— Median 0.14 0.07 0.11 0.17 0.55 Mean 0.14 0.09 0.13 0.18 0.55 Maximum 0.22 0.40 0.34 0.41 0.92 Minimum 0.00 0.00 0.05 0.02 0.22 N 125 125 125 125 25 Figure 3.5.12: Time series of carryover of nitrate in MR1404. Figure 3.5.13: Time series of carryover of phosphate in MR1404. Figure 3.5.14: Time series of carryover of silicate in MR1404. (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 60 sets of RMNSs 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 are as follows, respectively. Phosphate Concentration Cp in μmol kg-1: Uncertainty of measurement of phosphate (%) = 0.035031 + 0.35937 x (1 / Cp) - (1) where Cp is phosphate concentration of sample. Nitrate Concentration Cno3 in μmol kg-1: Uncertainty of measurement of nitrate (%) = 0.10084 + 1.0963 x (1/Cno3) + 0.042373 x (1/Cno3) x (1/Cno3) - (2) where Cno3 is nitrate concentration of sample. Silicate Concentration Cs in μmol kg-1: Uncertainty of measurement of silicate (%) = 0.063921 + 7.3785 x (1/Cs) + 5.4241 x (1/Cs) x (1/Cs) - (3) where Cs is silicate concentration of sample. Nitrite Concentration Cno2 in μmol kg-1: Uncertainty of measurement of nitrite (%) = - 0.1648 + 0.2457 x (1/Cno2) - 0.00050611 x (1/Cno2) x (1/Cno2) - (4) where Ca is ammonium concentration of sample. Ammonium Concentration Ca in μmol kg-1: Uncertainty of measurement of ammonium (%) = 1.8748 + 1.5641 x (1/Ca) - 0.009571 x (1/Ca) x (1/Ca) - (5) where Ca is ammonium concentration of sample. (8) Problems / improvements occurred and solutions (8.1) LNSW offset LNSW was assigned concentration of each parameter before the cruise. We found an offset for concentration of phosphate, -0.03 μmol L-1 between this year assign and past, as a result to assess the value of the reagent blank. We corrected assign values of RMNSs from this cruise. (8.2) Contamination of ammonium from the air in the laboratory In ammonium data, we could find a contamination from the air in the laboratory in this cruise leg2. We made a closed supply system of the LNSW from the 20 liter cubitainer to auto sampler due to avoid the contamination from the air. We could not find the contamination on and after using this system. (8.3) Contamination of nitrite from the LNSW bottle In nitrite data, we could find a contamination. But we could not calculate an origin of the contamination. As the result of the maintenance and cleaning of the equipment, the origin was the contamination of the LNSW bottle. We applied the closed supply system as same as the contamination of ammonium on and after cleared this problem. (8.4) Remove of the dilution line at phosphate measurement Karel Bakker at NIOZ suggested us to remove the dilution line at phosphate measurement to improve the peak shape in Spring 2013, therefore we had removed dilution line since MR1304 R/V Mirai cruise. As a result of this, precision of phosphate measurement becomes drastically excellent up to 0.08% in terms of median of 127 runs. (8.5) Usage of a power pipettor We have applied a power pipettor to avoid a bias by operators since this cruise, when made calibration standards for nutrients analysis. The power pipettor was gravimetrically calibrated according to paragraph (5.1) before the cruise. (8.6) Improvement of reduction rate at nitrate measurement We added a 5 turn Cu-Cd coil to previously used a 5 turn Cu-Cd coil in nitrate measurement flow line and also added CuSO4 in the imidazole solution to get a stable and high redaction rate in this cruise. As a result, we achieved a good stable and high reduction rate which was 99.0% in terms of median of 126 runs during this cruise. Figure 3.5.15: Time series of reduction of nitrate in MR1404. (9) Data archive All data will be submitted to JAMSTEC Data Management Office (DMO) 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 analysis. 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. 3.6 Carbon Items (CT, AT and pH) November 18, 2016 (1) Personnel Akihiko Murata (JAMSTEC) Yoshihiro Shinoda (JAMSTEC) Tomonori Watai (MWJ) Yoshiko Ishikawa (MWJ) Atsushi Ono (MWJ) Emi Deguchi (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 North Pacific 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 North Pacific. For the purpose, we measured CO2-system parameters such as dissolved inorganic carbon (CT), total alkalinity (AT) and pH along the extended WHP P10 and P01 lines at 149°E and 47°N, respectively, in the North Pacific. (3) Apparatus i. CT Measurement of CT was made with two total CO2 measuring systems (called as Systems C and D, respectively; Nippon ANS, Inc.), which were slightly different from each other. The systems comprised of a seawater dispensing system, a CO2 extraction system and a coulometer. In this cruise, we used coulometers, Seacat2000 and Model23000 for Systems C and D, respectively, both of which were constructed by Nippon ANS. Each of the two systems had almost a same 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 rates is 140 ml min-1) to the coulometer through a dehydrating module. The modules of Systems C and D consist 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, Inc. or laboratory-made. 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, an auto-syringe (Hamilton) for hydrochloric acid, a spectrophotometer (TM- UV/VIS C10082CAH, Hamamatsu Photonics), and a light source (Mikropack), which are automatically controlled by a PC. The water dispensing unit has a water- jacketed pipette (42.2663 mL at 25°C) and a titration cell, which is also controlled at 25°C. A seawater of approx. 42 ml is transferred from a sample bottle (DURAN. glass bottle, 100 ml) into the pipette by pressurizing the sample bottle (nitrogen gas), and is introduced into the titration cell. The seawater is used to rinse the titration cell. Then, Milli-Q water is introduced into the titration cell, also for rinse. A seawater of approx. 42 ml is weighted again by the pipette, and is transferred into the titration cell. Then, for seawater blank, absorbances are measured at three wavelengths (730, 616 and 444 nm). After the measurement, an acid titrant, which is a mixture of approx. 0.05 M HCl in 0.65 M NaCl and 38 μM bromocresol green (BCG) is added into the titration cell. The volume of the acid titrant is changed between 1.980 mL and 2.200 mL according to estimated values of AT. The seawater + acid titrant solution is stirred for over 9 minutes with bubbling by nitrogen gas in the titration cell. Then, absorbances at the three wavelengths are measured. Calculation of AT is made by the following equation: + A = (-[H ] V + M V )/V T T SA A A S where M(A) 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 ) 616 730 444 730 where A(i) is the absorbance at wavelength i nm. The HCl in the acid titrant is standardized on land. The concentrations of BCG were estimated to be approx. 2.0 x 10^(-6) M in sample seawater. iii. pH Measurement of pH was made by a pH measuring system (Nippon ANS, Inc.). For the detection of pH, spectrophotometry is adopted. The system comprises of a water dispensing unit and a spectrophotometer (Bio 50 Scan, Varian). For an indicator, m-cresol purple (2 mM), which is purified based on Patsavas et al. (2013), is used. Seawater is transferred from borosilicate glass bottle (250 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°C 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 (Liu et al., 2011): / R-e \ T | 1 | pH = -log(K e ) + log | —————————— | T 2 2 | 1-R(e /e | \ 3 2 / where 2 -log(K e ) = a + (b/T) + c x lnT – d x T; T 2 -4 2 a = –246.64209 + 0.315971 x S + 2.86855 x 10 x S ; 2 b = 7229.23864 – 7.098137 x S – 0.057034 x S ; c = 44.493382 – 0.052711 x S; d = 0.007762; -5 e1 = –0.007762 + 4.5174 x 10 T; -4 -4 e3/e2 = –0.020813 + 2.60262x 10 x T + 1.0436 x 10 x (S – 35). 2 The T and S indicate temperature in K and salinity, respectively. The K(T) is the dissociation constant of HI-, which is a protonated species of sulfonephthalein indicators. The R is the ratio of sulfonephthalein absorbances (= A/ A) at wavelengths of 578 nm and 434 nm. 578 433 (4) Shipboard measurement (4.1) Sampling i. CT All seawater samples were collected from depth with 12 liter Niskin bottles basically at every other station. The seawater samples for CT were taken with a plastic drawing tube (PFA tubing connected to silicone rubber tubing) into a 250 ml DURAN. glass bottle. The glass bottle was filled with seawater smoothly from the bottom following a rinse with sample seawater of 2 full, bottle volumes. The glass bottle was closed by an inner cap loosely, which was fitted tightly to the bottle mouth after mercuric chloride was added. At a chemical laboratory on ship, a volume of about 3mL seawater was removed with a plastic pipette from sampling bottles to have a headspace of approx. 1% of the bottle volume. A saturated mercuric chloride of 100 μl was added to poison seawater samples. The seawater samples were kept at 5°C in a refrigerator until analysis. A few hours just before analysis, the seawater samples were kept at 20°C in a water bath. ii. AT All seawater samples were collected from depth using 12 liter Niskin bottles at the same stations as for CT. The seawater samples for AT were taken with a plastic drawing tube (PFA tubing connected to silicone rubber tubing) into DURAN glass bottles of 100 ml. The glass bottle was filled with seawater smoothly from the bottom after rinsing it with sample seawater of 2 full, bottle volume. The samples were stored at about 5°C in a refrigerator. A few hours before analysis, the seawater samples were kept at 25°C in a water bath. iii. pH All seawater samples were collected from depth with 12 liter Niskin bottles at the same stations as for CT and AT. The seawater samples for pH were taken with a plastic drawing tube (PFA tubing connected to silicone rubber tubing) into a 250 ml borosilicate glass bottle. The glass bottle was filled with seawater smoothly from the bottom following a rinse with sample seawater of 2 full, bottle volumes. The glass bottle was closed by a stopper, which was fitted to the bottle mouth gravimetrically without additional force. A few hours just before analysis, the seawater samples were kept at 25°C in a water bath. (4.2) Analyses i. CT At the start of each leg, we calibrated the measuring systems by blank and 5 kinds of Na2CO3 solutions (nominally 500, 1000 1500, 2000, 2500 μmol/L). As it was empirically known that coulometers do not show a stable signal (low repeatability) with fresh (low absorption of carbon) coulometer solutions. Therefore, we measured 1.865% CO2 gas repeatedly until the measurements became stable. Then we started the calibration. The measurement sequence such as system blank (phosphoric acid blank), 1.865% CO2 gas in a nitrogen base, seawater samples (6) was programmed to repeat. The measurement of 1.865% CO2 gas was made to monitor response of coulometer solutions (from UIC, Inc. or in-house made). For every renewal of coulometer solutions, certified reference materials (CRMs, batch 136, certified value = 2021.15 μmol kg-1) provided by Prof. A. G. Dickson of Scripps Institution of Oceanography were analyzed. In addition, in-house reference materials (RM) (batch QRM Q30 and Q31) were measured at the initial, intermediate and end times of a coulometer solution’s lifetime. The preliminary values were reported in a data sheet on the ship. Repeatability and vertical profiles of CT based on raw data for each station helped us check performances of the measuring systems. In the cruise, we finished all the analyses for CT on board the ship. ii. AT We analyzed reference materials (RM), which were produced for CT measurement by JAMSTEC, but were efficient also for the monitor of AT measurement. In addition, certified reference materials (CRM, batches 136, certified value = 2246.74 μmol kg-1) were analyzed periodically to monitor systematic differences of measured AT. The reported values of AT were set to be comparable to the certified value of the batch 136. The preliminary values were reported in a data sheet on ship. Repeatability calculated from replicate samples and vertical profiles of AT based on raw data for each station helped us check performance of the measuring system. In the cruise, we finished all the analyses for AT on board the ship. iii. pH For an indicator solution, purified m-cresol purple (2 mM) was used. The indicator solution was produced on board a ship, and retained in a 1000 ml DURAN. laboratory bottle. The absorbance ratios of the indicator solution were kept between 1.4 and 1.6 by adding acid or alkali solution appropriately. It is difficult to mix seawater with an indicator solution sufficiently under no headspace condition. However, by circulating the mixed solution with a peristaltic pump, a well-mixed condition came to be attained rather shortly, leading to a rapid stabilization of absorbance. We renewed a TYGON. tube of a peristaltic pump periodically, when a tube deteriorated. We measured absorbances at 25°C. Absorbances of seawater only and seawater + indicator solutions were measured 5 times each after stable absorbances were attained, and the averaged values were used for the calculation of pH. The preliminary values of pH were reported in a data sheet on the ship. Repeatability calculated from replicate samples and vertical profiles of pH based on raw data for each station helped us check performance of the measuring system. We finished all the analyses for pH on board the ship. (5) Quality control i. CT We conducted quality control of the data after return to a laboratory on land. With calibration factors, which had been determined on board a ship based on blank and 5 kinds of Na2CO3 solutions, we calculated CT of CRM (batches 136), and plotted the values as a function of sequential day, separating legs and the systems used. There were no statistically-significant trends of CRM measurements. The repeatability of measurements was estimated to be 0.7 μmol kg-1, which was calculated from 230 differences of replicate measurements. ii. AT Temporal changes of AT, which originate from analytical problems, were monitored by measuring AT of CRM. We found no abnormal measurements during the cruises. The repeatability of measurements was estimated to be 1.1 μmol kg-1, which was calculated from 210 differences of replicate measurements. iii. pH It is recommended that correction for pH change resulting from addition of indicator solutions is made (Dickson et al., 2007). To check the perturbation of pH due to the addition, we measured absorbance ratios by doubling the volume of indicator solution and added it to a replicate seawater sample. We corrected absorbance ratios based on an empirical method (Dickson et al., 2007), although the perturbations were small. The correction was made by subtracting 0.0019 from measured absorbances. The repeatability of measurements was estimated to be 0.0005 pH unit, which was calculated from 272 differences of replicate measurements. We evaluated accuracy of pH values by comparing the corrected values with those computed from measured CT and AT. Averaged differences (computed – measured) of pH values were 0.011 ± 0.008 (n = 1957). References Clayton T. D. and R. H. Byrne (1993) Spectrophotometric seawater pH measurements: total hydrogen ion concentration scale calibration of m- cresol purple and at-sea results. Deep-Sea Research 40, 2115-2129. Dickson, A. G., C. L. Sabine and J. R. Christian eds. (2007) Guide to best practices for ocean CO2 measurements, PICES Special Publication 3, 191 pp. Liu, X., M. C. Patsavas and R. H. Byrne (2011) Purification and characterization of meta-cresol purple for spectrophotometric seawater pH measurements. Environmental Science and Technology, 45, 4862-4868. Patsavas, M. C., R. H. Byrne and X. Liu (2013) Purification of meta-cresol purple and cresol red by flash chromatography: Procedures for ensuring accurate spectrophotometric seawater pH measurements. Marine Chemistry, 150, 19-24. Yao, W. and R. B. Byrne (1998) Simplified seawater alkalinity analysis: Use of linear array spectrometers. Deep-Sea Research 45, 1383-1392. 3.7 Chlorophyll a December 16, 2016 (1) Personnel Kosei Sasaoka (JAMSTEC) (Leg 2) Hiroshi Uchida (JAMSTEC) (Legs 1, 2) Kanta Chida (Rakuno Gakuen University) (Legs 1, 2) Takuya Takahashi (Rakuno Gakuen University) (Legs 1, 2) Keitaro Matsumoto (MWJ) (Legs 1, 2) Katsunori Sagishima (MWJ) (Legs 1, 2) Haruka Tamada (MWJ) (Legs 1, 2) Misato Kuwahara (MWJ) (Leg 1) (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 P01 section in the North Pacific. 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 (500 ml bottles for samples from the surface water monitoring system). 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. 3.7.1). To estimate the chlorophyll a concentrations, we applied to the fluorometric “Non-acidification method” (Welschmeyer, 1994). (4) Results Vertical profiles of chlorophyll a concentrations along the P10N (Leg 1) and P01 (Leg 2) sections during the cruise are shown in Figure 3.7.2. and Figure 3.7.3. respectively. Cross section of chlorophyll a concentrations along the P01 line (Leg 2) is shown in Figure 3.7.4. To estimate the measurement precision, 41-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 41-pairs of the replicate samples was 0.008 μg/L, although absolute difference values between 36-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. Limnol. Oceanogr., 39, 1985- 1992. Figure 3.7.1. Relationships between pure chlorophyll a concentrations and fluorescence light intensity. Figure 3.7.2. Vertical profiles of chlorophyll a concentrations along the P10N section (Leg 1) obtained from hydrographic casts. Figure 3.7.3. Vertical profiles of chlorophyll a concentrations along the P01 section (Leg 2) obtained from hydrographic casts. Figure 3.7.4. Cross section of chlorophyll a concentrations along the P01- line (Leg 2) obtained from hydrographic casts. 3.8 Absorption Coefficients of Particulate Matter and Colored Dissolved Organic Matter (CDOM) September 12, 2014 (1) Personnel Kosei Sasaoka (JAMSTEC) (Leg 2) (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 east-west variability of light absorption by phytoplankton and CDOM along the P01 section in the North Pacific. (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 P01 section (Fig. 3.8.1, Table 3.8.1). Samples were collected in 3000ml dark bottles and filtered (500 – 3000 ml) through 25-mm What-man GF/F glass-fiber filters under a gentle vacuum (< 0.013 MPa) on board in the dark room. After filtration, the optical density of total particulate matter on filter (ODfp(λ)) between 350 and 750 nm at a rate of 1.0 nm was immediately measured by an UV-VIS recording spectrophotometer (UV-2400, Shimadzu Co.), and absorption coefficient was determined from the OD according to the quantitative filter technique (QFT) (Mitchell, 1990). A blank filter with filtered seawater was used as reference. All spectra were normalized to 0.0 at 750nm to minimize difference between sample and reference filter. To determine the optical density of non-pigment detrital particles (ODfd(λ)), the filters were then soaked in methanol for a few hours and rinsed with filtered seawater to extract and remove the pigments (Kishino et al., 1985), and its absorption coefficient was measured again by UV-2400. These measured optical densities on filters (ODfp(λ) and ODfd(λ)) were converted to optical densities in suspensions (ODsp(λ) and ODsd(λ)) using the pathlength amplification factor of Cleveland and Weidemann (1993) as follows: ODsp(λ) = 0.378 ODfp(λ) + 0.523 ODfp(λ)2 and ODsd(λ) = 0.378 ODfd(λ) + 0.523 ODfd(λ)2. The absorption coefficient of total particles (ap(λ) (m-1)) and non-pigment detrital particles (ad(λ) (m-1)) are computed from the corrected optical densities (ODs(λ)): ap(λ) = 2.303 x ODsp(λ) / L (L = V / S), and ad(λ) = 2.303 x 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. 3.8.1, Table 3.8.1). 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 x 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.3.8.2. Cross section of CDOM (as absorption coefficient at 325 nm, unit = m-1) along the P01 section were shown in Fig. 3.8.3. (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. Fig. 3.8.1: Location of sampling stations for absorption coefficients of phytoplankton and CDOM along the P01 section during MR14-04. Table 3.8.1: List of sampling stations for absorption coefficients of phytoplankton and CDOM during MR14-04. Stn Date(UTC) Time Lat. Lon. Sampling Cast Particle Sampling depth (db) (UTC) type No. absorbance CDOM absorbance ——— —————————— ———— ——————— ———————— —————————— ———— ———————————————— —————————————————————————————————————————————————————— 36 07/17/2014 7:28 42.97 N 145.45 E CTD+Bucket 1 0,10,50,86 0,10,50,86 41 07/19/2014 15:56 42.48 N 145.84 E CTD+Bucket 2 none Bottom-10,2930,1930,970,470,200,100,50,10,0 60 07/23/2014 13:34 41.27 N 150.39 E CTD+Bucket 1 0,10,50,100 Bottom-10,5000,4000,3000,2000,1000,500,200,100,50,10,0 61 07/25/2014 15:59 44.09 N 155.02 E CTD+Bucket 2 0,10,50,100 Bottom-10,5080,4080,3080,2070,1070,530,200,100,50,10,0 73 07/27/2014 11:59 47.01 N 160.02 E CTD+Bucket 1 0,10,50,100 Bottom-10,5000,3000,2000,1000,800,500,200,100,50,10,0 77 07/29/2014 22:47 47.00 N 164.51 E CTD+Bucket 1 0,10,50,100 Bottom-10,4920,2930,1930,970,770,470,200,100,50,10,0 87 08/01/2014 11:06 46.98 N 170.00 E CTD+Bucket 1 0,10,50,100 Bottom-10,3000,2000,1000,800,500,200,100,50,10,0 93 08/03/2014 12:05 47.00 N 176.09 E CTD+Bucket 1 0,10,50,100 Bottom-10,5000,3000,2000,1000,800,500,200,100,50,10,0 97 08/04/2014 18:25 46.99 N 179.43 W CTD+Bucket 1 0,10,50 Bottom-10,5080,3080,2070,1070,830,530,200,100,50,10,0 101 08/06/2014 5:30 47.00 N 174.95 W CTD+Bucket 3 0,10,50,100 Bottom-10,4920,2930,1930,970,770,470,200,100,50,10,0 105 08/08/2014 9:33 47.00 N 170.42 W CTD+Bucket 1 0,10,50 Bottom-10,5000,3000,2000,1000,800,500,200,100,50,10,0 109 08/09/2014 15:55 47.01 N 165.98 W CTD+Bucket 1 0,10,50,100 Bottom-10,5080,3080,2070,1070,830,530,200,100,50,10,0 114 08/11/2014 6:33 46.99 N 160.36 W CTD+Bucket 1 0,10,50,100 Bottom-10,5000,3000,2000,1000,800,500,200,100,50,10,0 118 08/12/2014 16:39 46.99 N 155.85 W CTD+Bucket 1 0,10,50,100 Bottom-10,5080,3080,2070,1070,830,530,200,100,50,10,0 122 08/13/2014 23:25 47.00 N 151.40 W CTD+Bucket 2 0,10,50,100 Bottom-10,4920,2930,1930,970,770,470,200,100,50,10,0 128 08/15/2014 21:25 46.90 N 144.44 W CTD+Bucket 1 0,10,50,100 Bottom-10,2930,1930,970,770,470,280,200,100,50,10,0 151 08/16/2014 20:20 50.00 N 144.99 W CTD+Bucket 1 0,10,50,100 Bottom-10,3000,2000,1000,800,500,300,200,100,50,10,0 132 08/18/2014 14:48 47.03 N 140.23 W CTD+Bucket 1 0,10,50,100 Bottom-10,3000,2000,1000,800,500,300,200,100,50,10,0 138 08/20/2014 8:35 46.99 N 133.47 W CTD+Bucket 1 0,10,50,100 Bottom-10,3000,2000,1000,800,500,300,200,100,50,10,0 141 08/21/2014 3:25 46.98 N 130.03 W CTD+Bucket 1 0,10,50,100 Bottom-10,2000,1000,800,500,300,200,100,50,10,0 149 08/22/2014 18:29 47.00 N 125.06 w CTD+Bucket 1 0,10,20,30,50,100 Bottom-10,970,770,470,280,200,100,50,30,20,10,0 Fig.3.8.2: Examples of chlorophyll-specific phytoplankton absorption coefficient spectra (a*ph(λ)) at 400-750 nm, (a) Stn.KNOT, (b) Stn. K2, (c) Stn. Papa, (d) Stn. 149. All spectra were normalized to 0.0 at 750nm. Fig.3.8.3: Contours showing distribution of CDOM (as absorption coefficient at 325 nm, unit = m-1) along the P01 section during MR14-04. 3.9 Calcium September 16, 2014 (1) Personnel Yoshihiro Shinoda (JAMSTEC) 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 emissions. 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 ). The decrease of CO3 is unfavorable to marine calcifying organisms, which utilize CO32–, together with Ca2+, to produce their calcium carbonate (CaCO3) shells and skeletons. To evaluate dissolution and precipitation of calcium carbonate, we measured directly the concentration of calcium in the sea water in the subarctic region of the North Pacific. (2) Reagents NH3/NH4buffer: 0.4 mol/l NH4Cl/ 0.4 mol/l NH3 buffer Zincon solution: 0.004 mol/l Zincon, 0.0925g Zincon was dissolved 0.8 ml 1M NaOH and was diluted to 50 ml EGTA titrant: 0.02 mol/l EGTA, 3.80g EGTA was dissolved 30 ml 1M NaOH and was diluted to 500 ml Zn/EGTA solution: 0.004 mol/l ZnSO4/ 0.004 mol/l EGTA STD solution: 40ml 1000mg/l Ca standard solution was diluted to 100ml (4) 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. The system comprises of a light source, photodiode detectors, auto-burette and control unit. Seawater of approx. 10ml is transferred from a sample bottle (60ml HDPE bottle) into 100 ml tall beaker by transfer pipet. A magnetic stirrer bar was added into beaker. 5ml NH3/NH4buffer, 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 measuring STD solution. (5) Performances The system worked well no troubles. The repeatability was estimated to 0.0089±0.0076 (n=20 pairs) mmol kg-1. 3.10 Dissolved Organic Carbon February 9, 2017 (1) Personnel Takeshi Yoshimura (Central Research Institute of Electric Power Industry) Dennis A. Hansell (RSMAS) Andrew Margolin (RSMAS) (2) Background and objectives For several years, the Hansell Laboratory has pursued opportunities to determine the global ocean distribution of dissolved organic carbon (DOC), which plays a significant role in marine carbon cycle. In the Pacific, in collaboration with Prof. Craig Carlson at the Univ. of California Santa Barbara, we have measured DOC on several of the CLIVAR Repeat Hydrography lines, including P16 (north and south), P06, P02, and P18 (http://yyy.rsmas.miami.edu/groups/biogeochem/Data.html). On the map given at that website, the major gaps in coverage of the global ocean are readily apparent, including the NW and the NE Pacific Ocean. P10N and P01 are well located for filling these critical gaps as they cover the distal end of the global ocean thermohaline circulation cell. Ultimately our goal is to evaluate the cause of DOC concentration gradients in the deep Pacific, but those gradients must first be established by surveys such as P01. Gradients indicate sources and sinks for refractory DOC (RDOC) in the deep layers, processes that are not understood at the present. RDOC has been implicated by paleoceanographers as the source of carbon responsible for climate hyperthermals of the Paleocene/Eocene epochs (45–50M ybp), but we know too little about RDOC in the modern ocean to confirm or refute that role. To fill the gaps in global coverage of DOC, we collected seawater samples at the stations on P10N and P01 lines during the MR14-04 cruise. (3) Samplings Seawater samples were collected in P10N (Leg. 1) and P01 line (Leg. 2) at all of the stations and layers where inorganic carbon parameters were measured in the main subject of this cruise. Water was collected directly into 60 mL polycarbonate bottles from the 12-L Niskin bottles attached to a CTD system. The bottles were then stored frozen until analysis at our laboratory at the University of Miami. Total number of the samples collected was approximately 2100. (4) Sample analyses and data management The frozen samples were returned to the laboratory and thawed for analysis by high temperature catalytic oxidation using a Shimadzu TOC analyzer. The method used was described in a chapter in the methods manual by Dickson et al. (2007). The method: An acidified water sample is sparged with oxygen to remove inorganic carbon. The water is then injected onto a combustion column packed with platinum-coated alumina beads held at 680°C. Non-purgeable organic carbon compounds are combusted and converted to CO2, which is detected by a non-dispersive infrared detector (NDIR). The instrument was a Shimadzu TOC-L with ASI-V auto sampler. Instrument conditions were as follows: Combustion temperature 680°C Carrier gas UHP Oxygen Carrier flow rate 50 ml min–1 Sample sparge time 2.0 min Minimum number of injections 3 Maximum number of injections 5 Number of washes 2 Standard deviation maximum 0.10 ppm CV maximum 2.0% Injection volume 100 µL Trace-impurity analyzed concentrated hydrochloric acid is used to acidify samples prior to analysis. Approximately 0.1% by volume of the concentrated acid is added to each sample prior to analysis to lower the pH of the sample to pH < 2. At this pH and with sparging, all inorganic carbon species are converted to CO2 and removed from the sample. The system is calibrated using potassium hydrogen phthalate in Milli-Q® water. System performance is verified daily using Consensus Reference Water (www.rsmas.miami.edu/ groups/biogeochem/CRM.html). This reference water is deep Sargasso Sea water (DSR) that has been acidified and sealed in 10 ml ampoules, the concentrations of which have been determined by the consensus of up to six expert and independent laboratories. Low Carbon Water (LCW) that has gone through the same acidification, sealing process, and consensus verification program as the DSR, and has an agreed upon carbon concentration of 1–2 μmol C L–1, is also analyzed and used to determine the instrument blank. After verifying proper operation of the instrument, samples are placed on an auto sampler for analysis. The run starts with a QW (Q Water) blank and a reference seawater analysis. Then six samples are analyzed, followed by another QW blank and reference sea water. This sequence is repeated until all samples for that run are analyzed. The run ends with a QW blank, reference water, and a QW blank that had not been acidified. This last blank verifies that the hydrochloric acid used to acidify the samples is not contaminated. QW blanks and reference water samples are used to evaluate system performance during the analytical run. If a problem is detected with the blanks or reference waters, the samples are reanalyzed. On a daily basis, CRM is analyzed to verify system performance. If the value of the CRM does not fall within the expected range, samples are not analyzed until the expected performance has been established. The QW blanks and reference seawater samples analyzed with the samples are used for quality assurance and quality control (QA/QC). By evaluating the performance of these reference waters, instrument drift and performance can be evaluated. If a problem is detected with either drift or performance, the samples are reanalyzed. (5) Reference Dickson, A.G., Sabine, C.L. and Christian, J.R. (Eds.) 2007. Guide to best practices for ocean CO2 measurements. PICES Special Publication 3, 191 pp. 3.11 Lowered Acoustic Doppler Current Profiler (LADCP) November 17, 2016 Personnel Shinya Kouketsu (JAMSTEC) (Principal Investigator, Leg 2) Hiroshi Uchida (JAMSTEC) (Legs 1 and 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 were obtained (e.g. Visbeck, 2002). However, in some stations, the shipboard ADCP profiles were not obtained due to GPS problems, and the estimation errors of the velocity estimations of lowered ADCP were slightly large at the stations. Furthermore, the first cast at station 1, the data process software did not work well due to small echo intensities in the deep layers. 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 At the following stations, the CTD cast was carried out without the LADCP, because the maximum pressure was beyond the pressure-proof of the LADCP (6000 m). Stations from P01_44 to P01_46 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. Station Summary (see data files) Water sample parameters: ———————————————————————————————————————————————————————————————— Num- Parameter Mnemonic Mnemonic for ber expected error ———— —————————————————————————————— ————————— ——————————————— 1 Salinity SALNTY 2 Oxygen OXYGEN 3 Silicate SILCAT SILUNC *1 4 Nitrate NITRAT NRAUNC *1 5 Nitrite NITRIT NRIUNC *1 6 Phosphate PHSPHT PHPUNC *1 7 Freon-11 CFC-11 8 Freon-12 CFC-12 9 Tritium 10 Helium 11 He-3/He-4 12 14Carbon DELC14 C14ERR 13 13Carbon DELC13 C13ERR 14 Kr-85 15 Argon 16 Ar-39 17 Neon 18 Ra-228 19 Ra-226 20 Ratio of O18 to O16 O18/O16 21 Sr-90 22 Cesium-137 CS-137 CS137ER *2 23 Total carbon TCARBN 24 Total alkalinity ALKALI 25 pCO2 26 pH PH 27 Freon-113 CFC113 28 Carbon tetrachloride CCL4 29 Iodate/Iodide 30 Ammonium NH4 31 Methane CH4 32 Dissolved organic nitrogen DON 33 Nitrous oxide N2O 34 Chlorophyll-a CHLORA 35 Pheophytin 36 Halocarbons 37 Biogenic sulfur compounds DMS 38 Hydrocarbons 39 Barium 40 Particulate organic carbon POC 41 Particulate organic nitrogen PON 42 Abundance of bacteria BACT 43 Dissolved organic carbon DOC 44 Carbon monoxide 45 Nitrogen (gas) 46 Total organic carbon TOC 47 Plutonium PLUTO PLUTOER *2 48 Primary productivity 64 Incubation 81 Particulate organic matter POM 82 15N-Nitrate 15NO3 83 Particulate inorganic matter PIM 84 Dissolved organic phosphate 85 Ratio of O-17 to O-16 O17/O16 86 Flowcytometry 87 Genetic analysis 88 Nitrogen fixation 89 Cesium-134 CS-134 CS134ER 90 Perfluoroalkyl substances PFAS 91 Iodine-129 I-129 92 Density salinity DNSSAL 93 Sulfur hexafluoride SF6 94 Isoprene 95 Pigment 96 Microscope 97 Calcium 98 Colored dissolved CDOM organic matter 99 Absorption coefficients AP of particulate matter 100 Nitrification 101 13C-CH4 102 Prokaryotic abundance 103 Fluorescence in situ hybridization 104 Prokaryotic activity 105 Viral production 106 Microbial diversity 107 N2O 15N-isotope 108 Nitrogen fixation 109 NH4 15N-isotope 110 Urea 111 NO2 15N-isotope 112 Coenzyme F430 113 Chlorophyll 15N-isotope Figure captions Figure 1: Station locations for (a) WHP P10N and (b) WHP P01 revisit in 2014 cruise with bottom topography. Figure 2: Bathymetry measured by Multi Narrow Beam Echo Sounding system. Figure 3: Surface wind measured at 25 m above sea level. Wind data is averaged over 6-hour. Figure 4: (a) Sea surface temperature (°C), (b) sea surface salinity (psu), (c) sea surface oxygen (µmol/ kg), and (d) sea surface chlorophyll a (mg/m3) measured by the Continuous Sea Surface Water Monitoring System. Figure 5: Difference in the partial pressure of CO2 between the ocean and the atmosphere, ∆pCO2. Figure 6: Surface current at 100 m depth measured by ship board acoustic Doppler current profiler (ADCP). Figure 7: Potential temperature (°C) cross sections calculated by using CTD temperature and salinity data calibrated by bottle salinity measurements. Vertical exaggeration of the 0-6500 m section is 1000:1, and expanded section of the upper 1000 m is made with a vertical exaggeration of 2500:1. Figure 8: CTD salinity (psu) cross sections calibrated by bottle salinity measurements. Vertical exaggeration is same as Fig. 7. Figure 9: Absolute salinity (g/kg) cross sections calculated by using CTD salinity data. Vertical exaggeration is same as Fig. 7. Figure 10: Density (upper: σ0, lower: σ4) (kg/m3) cross sections calculated by using CTD temperature and salinity data. Vertical exaggeration of the 0-1500 m and 1500-6500 m section are 2500:1 and 1000:1, respectively. (a) EOS-80 and (b) TEOS-10 definition. Figure 11: Neutral density (γn) (kg/m3) cross sections calculated by using CTD temperature and salinity data. Vertical exaggeration is same as Fig. 7. Figure 12: CTD oxygen (µmol/kg) cross sections. Vertical exaggeration is same as Fig. 7. Figure 13: CTD chlorophyll a (mg/m3) cross section. Vertical exaggeration of the upper 1000 m section is same as Fig. 7. Figure 14: CTD beam attenuation coefficient (m–1) cross sections. Vertical exaggeration is same as Fig. 7. Figure 15: Bottle sampled dissolved oxygen (µmol/kg) cross sections. Data with quality flags of 2 were plotted. Vertical exaggeration is same as Fig. 7. Figure 16: Silicate (µmol/kg) cross sections. Data with quality flags of 2 were plotted. Vertical exaggeration is same as Fig. 7. Figure 17: Nitrate (µmol/kg) cross sections. Data with quality flags of 2 were plotted. Vertical exaggeration is same as Fig. 7. Figure 18: Nitrite (µmol/kg) cross section. Data with quality flags of 2 were plotted. Vertical exaggeration of the upper 1000 m section is same as Fig. 7. Figure 19: Phosphate (µmol/kg) cross sections. Data with quality flags of 2 were plotted. Vertical exaggeration is same as Fig. 7. Figure 20: Dissolved inorganic carbon (µmol/kg) cross sections. Data with quality flags of 2 were plotted. Vertical exaggeration is same as Fig. 7. Figure 21: Total alkalinity (µmol/kg) cross sections. Data with quality flags of 2 were plotted. Vertical exaggeration is same as Fig. 7. Figure 22: pH cross sections. Data with quality flags of 2 were plotted. Vertical exaggeration is same as Fig. 7. Figure 23: Dissolved organic carbon (µmol/kg) cross sections. Data with quality flags of 2 were plotted. Vertical exaggeration is same as Fig. 7. Figure 24: Cross sections of current velocity (cm/s) normal to the cruise track measured by LADCP (eastward or northward is positive). Vertical exaggeration is same as Fig. 7. Figure 25: Difference in potential temperature (°C) between results from the WOCE revisit cruise in 2007 and the revisit in 2014. Red and blue areas show areas where potential temperature increased and decreased in the revisit cruise, respectively. On white areas differences in temperature do not exceed the detection limit of 0.002 °C. Vertical exaggeration is same as Fig. 7. Figure 26: Same as Fig. 25, but for salinity (psu). CTD salinity data with SSW batch correction1 were used. On white areas differences in salinity do not exceed the detection limit of 0.002 psu. Figure 27: Same as Fig. 25, but for dissolved oxygen (µmol/kg). CTD oxygen data were used. On white areas differences in dissolved oxygen do not exceed the detection limit of 2 µmol/kg. Note 1. As for the traceability of SSW to Kawano’s value (Kawano et al., 2006), the offset for the batches P148 (WOCE P01 revisit in 2007) and P156 (WOCE P01 revisit in 2014) are 0.0000 and 0.0004, respectively. The offset values for the recent batches are listed in Table A1 (Uchida et al., in preparation). Table A1: SSW batch to batch differences from P145 to P159 (Uchida et al., in preparation). The difference of P145 is reevaluated. Batch Production K15 Sp Batch batch difference (x10^(-3)) no. date Mantyla's standard Kawano's standard ————— —————————— ——————— ——————— —————————————————— ————————————————— P145 2004/07/15 0.99981 34.9925 - P146 2005/05/12 0.99979 34.9917 - P147 2006/06/06 0.99982 34.9929 - P148 2006/10/01 0.99982 34.9929 - 0.0 P149 2007/10/05 0.99984 34.9937 - 0.7 P150 2008/05/22 0.99978 34.9913 - 0.7 P151 2009/05/20 0.99997 34.9984 - P152 2010/05/05 0.99981 34.9926 - 0.0 P153 2011/03/08 0.99979 34.9918 - 0.4 P154 2011/10/20 0.99990 34.9961 - 0.6 P155 2012/09/19 0.99981 34.9925 - 0.1 P156 2013/07/23 0.99984 34.9937 - 0.4 P157 2014/05/15 0.99985 34.9941 - P158 2015/03/25 0.99970 34.9883 - P159 2015/12/15 0.99988 34.9953 - CCHDO Data History • File Merge Carolina Berys CruiseReport_MR14-04.pdf (download) #56f6e Date: 2017-06-07 Current Status: merged • File Merge Carolina Berys p01_49NZ20140717_do.pdf (download) #e481d Date: 2017-06-07 Current Status: dataset • File Submission Jerry Kappa p01_49NZ20140717_do.pdf (download) #e481d Date: 2017-06-07 Current Status: dataset Notes The final cruise report for p01_2014 is ready to be published on the CCHDO web site. It includes the all of the PI-provided data reports and figures, plus CCHDO data processing notes and summary pages. • File Merge SEE 49NZ20140717_ct1.zip (download) #c38c3 Date: 2016-05-11 Current Status: merged • File Merge SEE 49NZ20140717_nc_ctd.zip (download) #6291a Date: 2016-05-11 Current Status: merged • File Merge SEE 49NZ20140717_ct1.zip (download) #bb583 Date: 2016-05-11 Current Status: merged • Updated CTD exchange and netcdf formats SEE Date: 2016-05-11 Data Type: CTD Action: Website Update Note: P01 2014 49NZ20140717 processing - CTD/merge - CTDPRS,CTDTMP,CTDSAL,CTDOXY,FLUOR,XMISS,XMISSCP,PAR,CDOMF 2016-05-11 SEE Submission filename submitted by date id -------------------- -------------- ---------- ----- 49NZ20140717_ct1.zip Hiroshi Uchida 2015-06-25 11880 Changes ------- 49NZ20140717_ct1.zip - Renamed files to match EXCHANGE standard. Put original file name in file as a comment. - Changed the parameter name CDOM to CDOMF - Used the flag XMISS_FLAG_W as flag for both parameters XMISS and XMISSCP. Conversion ---------- file converted from software ----------------------- -------------------- ----------------- 49NZ20140717_nc_ctd.zip 49NZ20140717_ct1.zip 0.8.2-47-g3c55cd3 Updated Files Manifest ---------------------- file stamp ----------------------- ----------------- 49NZ20140717_ct1.zip 20160511CCHSIOSEE 49NZ20140717_nc_ctd.zip 20160511CCHSIOSEE :Updated parameters: CTDPRS,CTDTMP,CTDSAL,CTDOXY,FLUOR,XMISS,XMISSCP,PAR,CDOMF 49NZ20140717_ct1.zip and 49NZ20140717_nc_ctd.zip opened in JOA with no apparent problems. 49NZ20140717_ct1.zip opened in ODV with no apparent problems. • CTD online in Exchange and netCDF Carolina Berys Date: 2015-11-02 Data Type: CTD Action: Website Update Note: P01 2014 49NZ20140717 processing - CTD 2015-11-02 C Berys Submission filename submitted by date id ----------------------------------------------------------- 49NZ20140717_ct1.zip Hiroshi Uchida 2015-06-25 11880 * CTD files processed * NOTE: some parameters not in parameters table Conversion ---------- file converted from software -------------------------------------------------------------------- 49NZ20140717_nc_ctd.zip 49NZ20140717_ct1.zip hydro 0.8.2-47-g3c55cd3 Updated Files Manifest ---------------------- file stamp ----------------------------------------- 49NZ20140717_ct1.csv 20150419JAMSTECRCGC 49NZ20140717_nc_ctd.zip 20150419JAMSTECRCGC • File Online CCHDO Staff CruiseReport_MR14-04.pdf (download) #56f6e Date: 2015-10-30 Current Status: merged • File Online CCHDO Staff 49NZ20140717_sum.txt (download) #9a700 Date: 2015-10-30 Current Status: unprocessed • File Online CCHDO Staff 49NZ20140717_xc1.zip (download) #45c51 Date: 2015-10-30 Current Status: unprocessed • File Online CCHDO Staff 49NZ20140717_ct1.zip (download) #c38c3 Date: 2015-10-30 Current Status: merged • File Submission Hiroshi Uchida 49NZ20140717_ct1.zip (download) #c38c3 Date: 2015-06-25 Current Status: merged Notes CTDOXY data were updated. • File Submission Hiroshi Uchida CruiseReport_MR14-04.pdf (download) #56f6e Date: 2014-12-19 Current Status: merged Notes Expocode: 49NZ20140709, 49NZ20140717 Ship: R/V Mirai Woce Line: P10N, P01 Note: None • File Submission Hiroshi Uchida 49NZ20140717_xc1.zip (download) #45c51 Date: 2014-12-19 Current Status: unprocessed Notes Expocode: 49NZ20140709, 49NZ20140717 Ship: R/V Mirai Woce Line: P10N, P01 Note: None • File Submission Hiroshi Uchida 49NZ20140717_sum.txt (download) #9a700 Date: 2014-12-19 Current Status: unprocessed Notes Expocode: 49NZ20140709, 49NZ20140717 Ship: R/V Mirai Woce Line: P10N, P01 Note: None