

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 
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Aoyama, M., 2006: 2003 Intercomparison Exercise for Reference Material for 
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    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 
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Hydes, D.J., Aoyama, M., Aminot, A., Bakker, K., Becker, S., Coverly, S., 
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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

