ESSDEarth System Science DataESSDEarth Syst. Sci. Data1866-3516Copernicus PublicationsGöttingen, Germany10.5194/essd-8-383-2016A multi-decade record of high-quality fCO2 data in version 3 of the
Surface Ocean CO2 Atlas (SOCAT)
BakkerDorothee C. E.d.bakker@uea.ac.ukhttps://orcid.org/0000-0001-9234-5337PfeilBenjaminLandaCamilla S.MetzlNicolasO'BrienKevin M.OlsenArehttps://orcid.org/0000-0003-1696-9142SmithKarlCoscaCathyHarasawaSumikoJonesStephen D.https://orcid.org/0000-0003-0522-9851NakaokaShin-ichiroNojiriYukihiroSchusterUteSteinhoffTobiasSweeneyColmTakahashiTaroTilbrookBrontehttps://orcid.org/0000-0001-9385-3827WadaChisatoWanninkhofRikAlinSimone R.https://orcid.org/0000-0002-8283-1910BalestriniCarlos F.BarberoLeticiahttps://orcid.org/0000-0002-8858-5247BatesNicholas R.BianchiAlejandro A.BonouFrédéricBoutinJacquelinehttps://orcid.org/0000-0003-2845-4912BozecYannBurgerEugene F.CaiWei-JunCastleRobert D.ChenLiqiChiericiMelissaCurrieKimEvansWileyFeatherstoneCharlesFeelyRichard A.FranssonAgnetaGoyetCatherineGreenwoodNaomihttps://orcid.org/0000-0001-7166-9455GregorLukehttps://orcid.org/0000-0001-6071-1857HankinStevenHardman-MountfordNick J.https://orcid.org/0000-0001-9402-2953HarlayJérômeHauckJudithhttps://orcid.org/0000-0003-4723-9652HoppemaMariohttps://orcid.org/0000-0002-2326-619XHumphreysMatthew P.https://orcid.org/0000-0002-9371-7128HuntChristopher W.HussBettyIbánhezJ. Severino P.JohannessenTrulshttps://orcid.org/0000-0002-1671-3465KeelingRalphhttps://orcid.org/0000-0002-9749-2253KitidisVassilisKörtzingerArneKozyrAlexKrasakopoulouEvangeliaKuwataAkiraLandschützerPeterLauvsetSiv K.LefèvreNathalieLo MonacoClaireMankeAnsleyMathisJeremy T.MerlivatLilianeMilleroFrank J.MonteiroPedro M. S.MunroDavid R.https://orcid.org/0000-0002-1373-7402MurataAkihikohttps://orcid.org/0000-0002-5931-2784NewbergerTimothyOmarAbdirahman M.OnoTsuneoPatersonKristinaPearceDavidPierrotDenisRobbinsLisa L.SaitoShuSalisburyJoehttps://orcid.org/0000-0002-5894-6240SchlitzerReinerSchneiderBerndSchweitzerRolandSiegerRainerhttps://orcid.org/0000-0002-9175-884XSkjelvanIngunnSullivanKevin F.SutherlandStewart C.SuttonAdrienne J.https://orcid.org/0000-0002-7414-7035TadokoroKazuakiTelszewskiMaciejTumaMatthiasvan HeuvenSteven M. A. C.https://orcid.org/0000-0003-2001-8710VandemarkDougWardBrianWatsonAndrew J.https://orcid.org/0000-0002-9654-8147XuSuqingCentre for Ocean and Atmospheric Sciences, School of Environmental
Sciences, University of East Anglia, Norwich NR4 7TJ, UKGeophysical Institute, University of Bergen, 5020 Bergen, NorwayBjerknes Centre for Climate Research, 5007 Bergen, NorwaySorbonne Universités (UPMC, Univ Paris 06), CNRS, IRD, MNHN,
LOCEAN/IPSL Laboratory, 75005 Paris, FrancePacific
Marine Environmental Laboratory, National Oceanic and Atmospheric
Administration, Seattle, WA 98115, USAJoint
Institute for the Study of the Atmosphere and Ocean, University of
Washington, Seattle, WA 98105, USANational Institute for
Environmental Studies, Tsukuba, Ibaraki, 305-8506, JapanCollege
of Life and Environmental Sciences, University of Exeter, Exeter EX4 4QE, UKGEOMAR Helmholtz Centre for Ocean Research Kiel, 24105 Kiel,
GermanyCooperative Institute for Research in Environmental
Sciences, University of Colorado, Boulder, CO 80309, USAEarth System Research Laboratory, National Oceanic and Atmospheric
Administration, Boulder, CO 80305-3337, USALamont
Doherty Earth Observatory, Columbia University, Palisades, NY 10964, USA CSIRO Oceans and Atmosphere, Hobart, Tasmania 7001, AustraliaAntarctic Climate and Ecosystems Cooperative Research Centre,
University of Tasmania, Hobart, Tasmania 7001, AustraliaAtlantic Oceanographic and Meteorological Laboratory, National
Oceanic and Atmospheric Administration, Miami, FL 33149, USADepartemento Oceanografía, Servicio de Hidrografía
Naval, C1270ABV Buenos Aires, ArgentinaCooperative Institute for
Marine and Atmospheric Studies, Rosenstiel School for Marine and Atmospheric
Science, University of Miami, Miami, FL 33149-1098, USA Bermuda
Institute of Ocean Sciences, Ferry Reach, St. Georges, GE01, Bermuda Ocean and Earth Science, University of Southampton, Southampton
SO14 3ZH, UKCentro de Estudos e Ensaios em Risco e Modelagem
Ambiental, Universidade Federal de Pernambuco, 50740-550 Recife, BrazilSorbonne Universités, UPMC Univ Paris 06, CNRS, Adaptation et
Diversité en Milieu Marin (UMR7144), Station Biologique de Roscoff, 29680
Roscoff, FranceSchool of Marine Science and Policy, University
of Delaware, Newark, DE 19716, USAKey Laboratory of Global
Change and Marine-Atmospheric Chemistry, Third Institute of Oceanography,
State Oceanic Administration, Xiamen, 361005, ChinaChinese
Arctic and Antarctic Administration, Beijing, 100860, ChinaInstitute of Marine Research, 9294 Tromsø, NorwayDepartment of Marine Sciences, University of Gothenburg, 40530
Gothenburg, SwedenNational Institute of Water and Atmospheric
Research, Dunedin 9054, New Zealand Ocean Acidification Research
Center, University of Alaska Fairbanks, Fairbanks, AK 99775-7220, USAHakai Institute, British Columbia V0P 1H0, CanadaNorwegian Polar Institute, Fram Centre, 9296 Tromsø, NorwayIMAGES_ESPACE-DEV, Université de Perpignan, 66860 Perpignan,
FranceUMR ESPACE-DEV, Maison de la teledétection, 34000
Montpellier, FranceCentre for Environment, Fisheries and
Aquaculture Science, Lowestoft NR33 0HT, UKOcean Systems and
Climate, CSIR-CHPC, Cape Town, 7700, South AfricaCSIRO Oceans
and Atmosphere, Floreat, Western Australia 6014, AustraliaUniversity of Hawaii at Manoa, Department of Oceanography,
Honolulu, HI 96822, USAAlfred Wegener Institute Helmholtz Centre
for Polar and Marine Research, 27515 Bremerhaven, GermanyOcean
Process Analysis Laboratory, University of New Hampshire, Durham, NH 03824,
USAIRD – Institut de Recherche pour le Développement, Lago
Sul, 71640-230 Brasilia, BrazilUni Research Climate, Bjerknes
Centre for Climate Research, 5007 Bergen, NorwayUniversity of
California, San Diego, CA 92093, USAPlymouth Marine Laboratory,
Plymouth PL1 3DH, UKCarbon Dioxide Information Analysis Center,
Environmental Sciences Division, Oak Ridge National
Laboratory, Oak Ridge, TN 37831-6290, USAUniversity of the
Aegean, Department of Marine Sciences, 81100, Mytilene, Lesvos, GreeceTohoku National Fisheries Research Institute, Japan Fisheries
Research and Education Agency, Shiogama, Miyagi, 985-0001, JapanMax Planck Institute for Meteorology, 20146 Hamburg, GermanyDepartment of Ocean Sciences, Rosenstiel School of Marine and
Atmospheric Science, University of Miami, Miami, FL 33149-1031, USADepartment of Atmospheric and Oceanic Sciences and Institute of
Arctic and Alpine Research, University of Colorado, Boulder,
CO 80309-0450, USAJapan Agency for Marine-Earth Science and
Technology, Yokosuka, Kanagawa, 237-0061, JapanNational Research
Institute for Fisheries Science, Japan Fisheries Research and Education
Agency, Yokohama, Kanagawa, 236-8648, JapanUS Geological Survey,
Saint Petersburg, FL 33701, USAMarine Division, Global
Environment and Marine Department, Japan Meteorological Agency,
Tokyo 100-8122, JapanLeibniz Institute for Baltic
Sea Research, 18119 Rostock (Warnemünde), GermanyWeathertop
Consulting LLC, College Station, TX 77845, USAInternational
Ocean Carbon Coordination Project, Institute of Oceanology of the Polish
Academy of Sciences, 81-712 Sopot, PolandWCRP Joint Planning
Staff, World Meteorological Organization, 1211 Geneva 2, SwitzerlandRoyal Netherlands Institute for Sea Research, 1797 SZ 't Horntje,
Texel, the NetherlandsAirSea Laboratory, School of Physics and
Ryan Institute, National University of Ireland, Galway, IrelandDorothee C. E. Bakker (d.bakker@uea.ac.uk)15September20168238341326April201625May201622July201622July2016This work is licensed under a Creative Commons Attribution 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/3.0/This article is available from https://essd.copernicus.org/articles/8/383/2016/essd-8-383-2016.htmlThe full text article is available as a PDF file from https://essd.copernicus.org/articles/8/383/2016/essd-8-383-2016.pdf
The Surface Ocean CO2 Atlas (SOCAT) is a synthesis
of quality-controlled fCO2 (fugacity of carbon dioxide) values for the
global surface oceans and coastal seas with regular updates. Version 3 of
SOCAT has 14.7 million fCO2 values from 3646 data sets covering the
years 1957 to 2014. This latest version has an additional 4.6 million
fCO2 values relative to version 2 and extends the record from 2011 to
2014. Version 3 also significantly increases the data availability for 2005
to 2013. SOCAT has an average of approximately 1.2 million surface water
fCO2 values per year for the years 2006 to 2012. Quality and
documentation of the data has improved. A new feature is the data
set quality control (QC) flag of E for data from alternative sensors and
platforms. The accuracy of surface water fCO2 has been defined for all
data set QC flags. Automated range checking has been carried out for all
data sets during their upload into SOCAT. The upgrade of the interactive
Data Set Viewer (previously known as the Cruise Data Viewer) allows better
interrogation of the SOCAT data collection and rapid creation of
high-quality figures for scientific presentations. Automated data upload has
been launched for version 4 and will enable more frequent SOCAT releases in
the future. High-profile scientific applications of SOCAT include
quantification of the ocean sink for atmospheric carbon dioxide and its
long-term variation, detection of ocean acidification, as well as evaluation
of coupled-climate and ocean-only biogeochemical models. Users of SOCAT data
products are urged to acknowledge the contribution of data providers, as
stated in the SOCAT Fair Data Use Statement. This ESSD (Earth System Science Data) “living data” publication documents the methods and data sets used for
the assembly of this new version of the SOCAT data collection and compares
these with those used for earlier versions of the data collection (Pfeil et
al., 2013; Sabine et al., 2013; Bakker et al., 2014). Individual data set files, included in the synthesis product, can be downloaded here: 10.1594/PANGAEA.849770.
The gridded products are available here: 10.3334/CDIAC/OTG.SOCAT_V3_GRID.
Data coverage and parameter measured
Repository references:
Individual data set files and synthesis product: 10.1594/PANGAEA.849770
The oceans represent a vast reservoir for carbon, mainly in the form of
dissolved inorganic carbon (DIC), made up of the species bicarbonate,
carbonate and dissolved carbon dioxide (CO2). This carbon reservoir is
in contact with the much smaller reservoir of CO2 in the atmosphere via
air–sea gas exchange.
Emissions of CO2 by human activity, such as fossil fuel burning, cement
manufacturing and changes in land use, are rapidly increasing the
atmospheric concentration of this long-lived greenhouse gas. The oceans are
taking up about 26 % of the global CO2 emissions with ocean uptake
estimated at 2.6 ± 0.5 Pg C yr-1 for the time period 2005 to 2014
(Le Quéré et al., 2015b). This ocean carbon sink slows down the rate
of climate change caused by human activity. Ocean carbon uptake changes
ocean carbonate chemistry, notably by reducing ocean pH and the carbonate ion
concentration, a process known as ocean acidification and sometimes referred
to as “the other CO2 problem” (Turley, 2005; Henderson, 2006; Doney et
al., 2009a). These changes in ocean chemistry are expected to affect key
physiological processes of marine organisms, such as calcification, growth,
development and survival (Kroeker et al., 2013). Ocean acidification is
likely to have far-reaching impacts on marine organisms and marine
biodiversity, with the effects expected to first be felt in the polar
oceans (Orr et al., 2005).
The annual change in marine carbonate chemistry resulting from net ocean
carbon uptake is small in comparison to its natural variation. A mean annual
increase of 1.5 µatm has been estimated in surface ocean
fCO2 (fugacity of CO2) for the period from 1970 to 2007
(Takahashi et al., 2009), which is superimposed on large seasonal variation,
here defined as the difference between winter and summer values, of, for
example, 120 µatm in the seasonally ice covered Southern Ocean and
160 µatm in Georgia Basin (E. M. Jones et al., 2015). The annual
increase also occurs against a background of large spatial variation of, for
example, 140 µatm in different regions of the Southern Ocean in
spring (Bakker et al., 2008; E. M. Jones et al., 2015). Similarly, seasonal
variation of 0.04 in surface pH in the subtropical North Atlantic Ocean
(González-Dávila et al., 2007) is 20 times the mean annual decrease
in surface ocean pH at a rate of -0.002 yr-1 (Feely et al., 2009;
Lauvset et al., 2015).
Seasonal and spatial variation in surface water fCO2 and pH tend to be
larger in coastal waters than in the open ocean, as a result of relatively strong tidal forces, large
temperature changes, freshwater and other terrestrial inputs, and strong
primary production in coastal waters (e.g. Simpson and Sharples, 2012). This
is illustrated by an fCO2 decrease of 250 µatm from winter
to summer at a coastal site near Antarctica (Legge et al., 2015) and spatial
variation of up to 200 µatm within the North Sea (Thomas et al.,
2004; Omar et al., 2010). Arctic coastal and shelf seas equally have large
spatial (> 500 µatm within the region in summer), seasonal
(300 µatm) and year-to-year variation (100 µatm) in
surface water fCO2 (Fransson et al., 2006, 2009). Surface water
fCO2 may range from less than 200 to 800 µatm (or even
1200 µatm) over short time (days) and space scales (less than 10
nm) in the upwelling system of the US west coast (Hales et al., 2005, 2012;
Harris et al., 2013, supplemental figure.)
The annual changes in surface ocean fCO2 and pH exhibit spatial and
temporal variation. Basin-specific rates in the fCO2 increase vary from
1.2 to 2.1 µatm yr-1 for the years 1970 to 2007 (Takahashi et
al., 2009), with higher rates of 2.3 to 3.3 µatm yr-1 at
different mooring sites in the equatorial Pacific Ocean for the more recent
period of 1997 to 2011 (Sutton et al., 2014a). The annual pH decreases at
rates of -0.0013 yr-1 in the South Pacific Ocean (for 1998 to
2012) to -0.0026 yr-1 in the Irminger Sea (for 1982 to 2006)
(Bates et al., 2014), while annual pH changes vary from -0.0018 to
-0.0026 yr-1 for moorings in the equatorial Pacific Ocean for 1997
to 2011 (Sutton et al., 2014a). Here it is worth noting that such rates of
change vary with the start date and period used for the calculation as a
result of interannual to decadal variability (McKinley et al., 2011).
Modelling has long been a primary tool for quantification of the ocean
carbon sink (e.g. Le Quéré et al., 2014) and ocean acidification
(Orr et al., 2005). The availability of large surface ocean CO2 data
synthesis products, such as the Lamont Doherty Earth Observatory (LDEO)
surface ocean pCO2 (partial pressure of CO2) database (Takahashi
et al., 2009, 2014) and the Surface Ocean CO2 Atlas (SOCAT) (Pfeil et
al., 2013; Sabine et al., 2013; Bakker et al., 2014; this study), now
enables data-based estimates of the ocean carbon sink, as well as direct
model-to-data comparison for surface ocean fCO2 and ocean carbon sink
estimates (Le Quéré et al., 2014, 2015a, b; Séférian et
al., 2014; Turi et al., 2014). A challenge for data-based estimates of the
ocean carbon sink is the gap-filling required for times and locations
without surface ocean fCO2 data. Different techniques and assumptions
are applied for doing this; however, the resulting estimates of the ocean
carbon sink differ considerably between the methods, especially in data-sparse regions, such as the South Pacific Ocean (Rödenbeck et al.,
2015). Recent data-based studies highlight large year-to-year, decadal and
longer-term variation in surface ocean fCO2 with consequent variation
in the global ocean CO2 sink (Fay and McKinley, 2013; Fay et al., 2014;
Landschützer et al., 2014, 2015; Rödenbeck et al., 2014, 2015).
Several model-to-data comparison studies suggest that models underestimate
the spatial and temporal variation in surface ocean fCO2 and the ocean
carbon sink (Séférian et al., 2014; Turi et al., 2014; Rödenbeck
et al., 2015). Such results could only be achieved because of the huge
progress that has been made in data collection efforts like SOCAT.
The Global Carbon Budget provides an annual estimate of the carbon sinks and
sources for the atmosphere (Le Quéré et al., 2014, 2015a, b).
The land carbon sink is determined as a residual of the other terms in the
budget, namely the atmospheric and ocean components and land-use change. Thus, quantification of
the ocean carbon sink is critical to resolving the Global Carbon Budget.
Ocean carbon sink estimates based on the LDEO and SOCAT synthesis products
have been included in recent versions of the Global Carbon Budget (Sect. 7.3) (Le
Quéré et al., 2014, 2015a, b).
The above highlights the need for long-term sustained, accurate observations
over the entire surface ocean and synthesis of the marine carbonate
chemistry measurements for quantification of trends in the ocean carbon sink
and ocean acidification. This has been eloquently expressed for in situ
observations of the climate system by Carl Wunsch and colleagues (Wunsch et
al., 2013):
No substitute exists for adequate observations. […] Models
will evolve and improve, but, without data, will be untestable, and
observations not taken today are lost forever. […] Today's
climate models will likely prove of little interest in 100 years. But
adequately sampled, carefully calibrated, quality controlled, and archived
data for key elements of the climate system will be useful indefinitely.
In 2007, the international marine carbon community decided to create a
quality-controlled, publicly available synthesis product of surface ocean
CO2 for the global oceans and coastal seas (IOCCP, 2007; Doney et al.,
2009b). The Surface Ocean CO2 Atlas provides regular updates of (1) a synthesis product of surface ocean fCO2 measurements and (2) a gridded product of surface ocean fCO2 values (without interpolation
to grid cells with no measurements).
Both SOCAT data products cover the global oceans and coastal seas. Version 1
of SOCAT was made available in 2011 (Pfeil et al., 2013; Sabine et al.,
2013), followed by the release of version 2 in 2013 (Bakker et al., 2014)
and of version 3 in 2015 (this study). The Surface Ocean CO2 Atlas
(http://www.socat.info/) provides a key synthesis data set of
surface ocean fCO2 for global and regional scientific studies of the
ocean carbon sink and ocean acidification.
The SOCAT data collection only contains original surface water CO2
data, as reported by the data originator, as input values. Thus, the SOCAT
data collection does not contain CO2 values processed by secondary data
sources. The SOCAT data products only contain surface water fCO2 values
from xCO2 (mole fraction), pCO2 or fCO2 measurements (Pfeil et al., 2013). SOCAT does
not include surface water fCO2 calculated from the other seawater
carbonate system parameters, such as pH, dissolved inorganic carbon or total
alkalinity. Almost all fCO2 values in SOCAT have been collected on
ships by determination of the CO2 concentration in the headspace of an
equilibrator with a continuous seawater flow (Pfeil et al., 2013; Bakker et
al., 2014). Shipboard systems for equilibrators generally use gas
chromatography or infrared detection to determine the CO2 concentration
in headspace air (Pierrot et al., 2009). SOCAT versions 2 and 3 also have
data sets from fixed moorings and drifting buoys with measurements made by
an equilibrator system with infrared detection or by a membrane
spectrophotometer. The SOCAT data collection includes a small number of
historical, discrete surface water fCO2 measurements.
Two large surface ocean CO2 data synthesis products, the LDEO and SOCAT
synthesis products, are now available (Takahashi et al., 2009, 2014; Pfeil
et al., 2013; Sabine et al., 2013; Bakker et al., 2014; this study). While
there is substantial overlap in the data sets they contain, the LDEO and
SOCAT synthesis products are independent and differ in their data treatment
and quality control. There is no intention to merge the LDEO and SOCAT
synthesis products, which from a SOCAT perspective would not meet its aim of
full documentation and coherence of data treatment and quality control. That
said, the SOCAT data managers regularly check which data sets are in the
LDEO data product, but are not (yet) included in SOCAT, and invite the data
providers to submit their original data sets to SOCAT. In reverse, SOCAT
expects data providers to make their original data sets public as part of
the submission to SOCAT or upon publication of the SOCAT version of which
these data sets are part (Sect. 6.1). The frequent SOCAT releases therefore
increase the data availability in general, including for the LDEO data
product. Overall, both data products reinforce each other. Furthermore, the
existence of the two data products with slightly different time lines
enables the use of independent data from the LDEO data set (i.e. data not
(yet) included in SOCAT) in testing interpolation methods built using SOCAT
(Landschützer et al., 2015) and vice versa.
SOCAT version 3 was made public during the SOCAT and SOCOM (Surface Ocean
pCO2 Mapping Intercomparison) Event on 7 September 2015 (SOCAT and
SOCOM, 2015). The event was part of the Surface Ocean Lower Atmosphere Study
(SOLAS) Open Science Conference in Kiel, Germany. This manuscript documents
SOCAT version 3, while highlighting the key differences with respect to
version 2 (Sect. 2). The SOCAT Fair Data Use Statement is presented in
Sect. 3. This is followed by a description of data upload, quality control
(Sect. 4) and the data products available for version 3 (Sect. 5). We also
look forward towards ongoing developments affecting future SOCAT versions,
notably automated data upload, inclusion of additional parameters and annual
releases (Sect. 6). The article ends with an assessment of the impact and
scientific applications of SOCAT to date (Sect. 7) and concluding remarks
(Sect. 8). This publication will be updated regularly using the format of
the ESSD (Earth System Science Data) “living data” to document the SOCAT
versions and significant changes in the data collection, data upload,
quality control and data products. This is the first version of the SOCAT
“living data” and is closely associated with earlier ESSD publications
describing SOCAT versions 1 (Pfeil et al., 2013; Sabine et al., 2013) and 2
(Bakker et al., 2014).
Characteristics of SOCAT version 3 and key differences to version
2
Global distribution of (a) all and (b) newly added surface water
fCO2 values (µatm) and (c) the timing of the newly added data
sets in SOCAT version 3 with data set flags of A to E. Version 3 has data
sets from 1957 to 2014.
(a) Number of surface water fCO2 values per year and (b) the
base 10 logarithm of this number per year for 1957 to 2014 in SOCAT versions
1, 2 and 3 (after Bakker et al., 2014).
Key differences between SOCAT versions 2 and 3. See text and Table 2
for further detail and an explanation of cross-overs and
standard operating procedures (SOPs). Calculation of “recommended
fCO2” (fCO2rec) is explained in Sect. 4.2.
Version 2Version 3DescriptionBakker et al. (2014)This study.Fair Data Use StatementData policy on web pages.Renamed to Fair Data Use Statement. Phrased more strongly and given more prominence on the SOCAT web sites.Data coverage1968 to 2011, 10.1 million surface water fCO2 values, 2660 data sets with a WOCE flag of 2.1957 to 2014, 14.7 million surface water fCO2 values from 3646 data sets (3640 with a WOCE flag of 2 and 6 with a flag of 3).Time stampThe time stamp includes seconds for all data sets. When equal time stamps occurred, evenly distributed artificial seconds were added to time stamps.Artificial seconds were added for concurrent entries. A WOCE flag of 4 was given to duplicate times in data sets with less than 50 equal time stamps (Table 7).Upload DashboardNot available.Single platform for data upload, fCO2rec calculation and automated data checks.Data uploadBulk data upload on quality control system.All data sets in versions 1, 2 and 3 were uploaded on the Upload Dashboard.Calculation of fCO2recIn Matlab, prior to bulk data upload.On the Upload Dashboard with Ferret scripts for all data in versions 1, 2 and 3.Automated data checks Not available.Automated checks after calculation of fCO2rec for all new and updated data sets. WOCE flags of 4 were assigned in specific cases (Table 7).Quality Control EditorAs in version 1.After automated checks. Upgraded search options and graphical interface. Data set QC flag needs to match QC criteria (tick boxes).Data set QC flags in data productsFlags of A–D.Flags of A–E. Revised data set QC criteria (Table 2) applied to all new and updated data sets.Flag ANeeds a cross-over (an acceptable comparison with other data).Needs a high-quality cross-over.Flags A, BAccuracy equilibrator pressure ≤ 0.5 hPa. Six other SOP criteria apply.Accuracy equilibrator pressure ≤ 2 hPa. Six other SOP criteria apply.Flag CDid not follow approved methods or SOP criteriaDid or did not follow approved methods or SOP criteria.Flags C, DAccuracy fCO2rec not specified.Accuracy fCO2rec ≤ 5 µatm.Flag ENot available.Accuracy fCO2rec ≤ 10 µatm, mainly for alternative sensors and platforms with in situ calibration and full documentation.WOCE flags for fCO2recFlag of 2 (good) as a default. Manual entry of flags of 3 (questionable) and 4 (bad).Flag of 2 as a default. Flags of 4 given during automated data checks (Table 7). Quality control comment added during manual entry of flags of 3 and 4.ParameterNCEP (2012) atmospheric pressure, atmospheric CO2 mole fraction from GLOBALVIEW-CO2 (2012).NCEP (2014) atmospheric pressure, atmospheric CO2 mole fraction from GLOBALVIEW-CO2 (2014).Synthesis productsData sets with flags of A–D and fCO2rec with a WOCE flag of 2 in synthesis and gridded files and as default elsewhere.Data sets with flags of A–E made public (Table 8). Data sets with flags of A–D and fCO2rec with a WOCE flag of 2 in synthesis and gridded files. Data sets with a flag of E and fCO2rec with a flag of 2 in a separate synthesis file. Contents of files downloadable from the Data Set Viewer have been streamlined (Table 9).Gridded products Missing grid cells in cruise-weighted gridded products (versions 1 and 2). A gridded product of means per climatological month is available.Correction of data-set-weighted gridded products (version 3). No gridded product of means per climatological month. Data Set Viewer and Gridded Data ViewerOn different software platforms.On a single software platform with a powerful graphical interface, following the move of the Data Set Viewer.TerminologyTerms in version 1: cruises, ships, Cruise Data Viewer, Table of Cruises, cruise-weighted means.New terms to accommodate sensors and platforms: data sets, platforms, Data Set Viewer, Table of Datasets, data-set-weighted means.
Version 3 of the Surface Ocean CO2 Atlas includes 14.7 million surface
water fCO2 values over the time period 1957 to 2014 for the oceans and
coastal seas around the world (Figs. 1 and 2; Table 1). The fCO2 values
are from 3646 data sets, collected on ships (3504 cruises), moorings (123)
and drifters (19). The 3646 data sets include 3640 data sets with a WOCE
(World Ocean Circulation Experiment) flag of 2 (good), available in all data
products, as well as six data sets with a WOCE flag of 3 (questionable), only
available in some data products, if selected. Version 3 is an update of
version 2 with an additional 4.6 million fCO2 values from 986 data
sets. Version 3 takes the start of the data record backwards from 1968 to
1957 by adding four historic cruises. It also extends the data collection
forward by adding 1.8 million fCO2 values for 2012 and 2013, as well as
a small number of values from 2014 (Fig. 2). Version 3 also increases the
number of fCO2 values for many years between 1989 and 2011. It adds
50 % more fCO2 values for 2008 to 2010, while doubling the available
data for 2011. The year 2006 has the largest number of fCO2 values,
closely followed by 2009 and 2011.
Data set quality control (QC) flags in version 3 (Wanninkhof et al.,
2013b; Olsen et al., 2015). All criteria need to be met for assigning a flag
of A to E. Data sets with flags of A to E have been made public. Data sets
with a flag of A to D are included in the global synthesis and gridded
products (Table 8). Changes relative to versions 1 and 2 are in bold. Flag
(ID) refers to the data set quality control flag with its numerical
identifier (ID) provided between brackets. Calculation of “recommended
fCO2” (fCO2rec) is explained in Sect. 4.2.
Flag (ID)Criteria for version 3A (11)(1) Accuracy of calculated fCO2rec (at SST) is better than 2 µatm. (2) A high-quality cross-over1,2with another data set is available.
(3) Followed approved methods/SOP3 criteria. (4) Metadata documentation complete. (5) Data set QC was deemed acceptable.B (12)(1) Accuracy of calculated fCO2rec (at SST) is better than 2 µatm. (2) Followed approved methods/SOP criteria. (3) Metadata documentation complete. (4) Data set QC was deemed acceptable.C (13)(1) Accuracy of calculatedfCO2rec (at SST) is better than 5µatm.(2) Did or did not follow approved methods/SOP criteria.
(3) Metadata documentation complete. (4) Data set QC was deemed acceptable.D (14)(1) Accuracy of calculated fCO2rec (at SST) is better than 5µatm.
(2) Did or did not follow approved methods/SOP criteria. (3) Metadata documentation incomplete. (4) Data set QC was deemed acceptable.E (17)Primarily for alternative sensors(1) Accuracy of calculated fCO2rec (at SST) is better than 10µatm.(2) Did not follow approved methods/SOP criteria.(3) Metadata documentation complete.(4) Data set QC was deemed acceptable.S (15) (Suspend)(1) More information is needed for data set before flag can be assigned. (2) Data set QC revealed non-acceptable data. (3) Data are being updated (part or the entire data set).X (15) (Exclude)The data set duplicates another data set in SOCAT.N (No flag)No data set flag has yet been given to this data set.U (Update)The data set has been updated. No data set flag has yet been given to the revised data.
1 A cross-over between two data sets is defined as an
equivalent distance of less than 80 (Pfeil et al., 2013). This criterion
combines distance and time as ([Δx2+ (Δt× 30)2]0.5)≤ 80 with distance x in kilometres and
time t in hours. One day of separation in time is equivalent
(heuristically) to 30 km of separation in space.
2 A high-quality cross-over is defined as a cross-over between two data
sets with a maximum cross-over equivalent distance of 80 km, a maximum
difference in sea surface temperature of 0.3 ∘C and a maximum
fCO2rec difference of 5 µatm. Inconclusive cross-overs with the
temperature or fCO2rec difference between the data sets exceeding
0.3 ∘C or 5 µatm, respectively, do not receive a flag of A.
High-quality cross-overs are rare in coastal waters, near sea ice and in
regions of freshwater influence, as a result of high spatial variation, not
for lack of measurement quality (Sect. 4.4).
3 Seven approved methods or SOP (standard operating procedure) criteria
need to be fulfilled for a data set quality control flag of A and B (Sect. 4.4) (after Pfeil et al., 2013). In version 3, the accuracy requirement for
equilibrator pressure has been relaxed to 2.0 hPa from 0.5 hPa in earlier
SOCAT versions. The six other criteria are the same in SOCAT versions 1, 2
and 3.
New in version 3 is an accuracy criterion for all surface ocean fCO2
values, described by data set quality control (QC) flags of A to E, for
accuracies of 2 (A, B), 5 (C, D) and 10 µatm (E) (Table 2) (Sect. 4.4)
(Wanninkhof et al., 2013b; Olsen et al., 2015). Flag A now also requires a
high-quality cross-over with another data set. The introduction of a lower-accuracy, data set quality control flag of E (accuracy of fCO2 values
better than 10 µatm) enables the inclusion of calibrated
fCO2 measurements made by alternative sensors and on alternative
platforms (Wanninkhof et al., 2013b; Olsen et al., 2015). Version 3 has
significantly more data sets from fixed moorings (123 data sets) and
drifting buoys (19) than version 2 (28 and 3 data sets, respectively). These
measurements were made by an equilibrator system with infrared detection
(e.g. Johengen, 2010; Sutton et al., 2014b) or a membrane spectrophotometer
(e.g. Boutin and Merlivat, 2009; Merlivat et al., 2015).
Overall, the quality of the data is comparable to that of version 2, with a
small improvement in the documentation of the individual data sets. In
version 3, 14 % of the data sets (509 data sets) received a quality
control flag of A, 35 % (1260 data sets) a flag of B, 23 % (840) a flag
of C and 27 % (990) a flag of D. This compares to 17 % (454 data sets),
31 % (834), 18 % (491) and 33 % (881), respectively, in version 2. The
percentage of data sets receiving a flag of A or B is remarkably similar
between both versions (49 % in version 3, 48 % in version 2). The small
reduction in the percentage of data sets with a flag of D (27 % in version
3, 33 % in version 2), which implies incomplete metadata, highlights an
improvement in the documentation accompanying individual data sets. A total
of 41 data sets (1 %) received a flag of E; most of these are sensor data,
but they also include a small number of valuable historic data sets with an
accuracy deemed better than 10 µatm.
Version 3 represents a major step towards the automation of the SOCAT data
and metadata upload and quality control in future versions. A new interface,
the SOCAT Upload Dashboard, hosts data and metadata upload,
(re)calculation of fCO2, automated data checks,
data visualisation and submission to the quality control system in a single
application (Table 1). A prototype of the SOCAT Upload Dashboard was used for
data upload for version 3 (Sect. 4.1) and (re)calculation of fCO2
(Sect. 4.2). All data sets were run across a newly developed, automated data
checker for identification of values that were out of range (Sect. 4.3). As a
result, issues identified during data upload were already corrected prior to
entry on the quality control system. The search capabilities and graphical
interface of the quality control system and the associated Data Set Viewer
(previously known as the Cruise Data Viewer) were upgraded (Sects. 4.4 and
5.4). Version 4 will see enhanced implementation of SOCAT automation by
enabling data providers to upload their data using the SOCAT Upload Dashboard
and submission onto the SOCAT QC Editor (Sect. 6.1).
The publicly accessible, user-friendly and interactive Data Set Viewer now
allows selection of fCO2 values by data set, year, month, region, data
provider, vessel or platform name, country of the vessel's or platform's
flag, data set quality control flag, WOCE flag and SOCAT version, as well as setting of limits on data ranges. The graphical tools of the Data Set Viewer
(access via http://www.socat.info/) for SOCAT version 3 have been extended
(Figs. 1, 3 and 4). Users can now set fixed colour scales and create
high-quality, publishable images.
Decadal distribution of surface water fCO2 (µatm) for
the global oceans and coastal seas in SOCAT version 3: (a) 1957 through 1969,
(b) 1970s, (c) 1980s, (d) 1990s, (e) 2000s, and (f) 2010 through 2014. Similar
figures are available for versions 1 and 2 (Pfeil et al., 2013;
Brévière et al., 2015).
A small error was detected in the gridded data products of SOCAT versions 1
and 2 (Sect. 5.5). In short, the data-set-weighted fCO2 values
(formerly known as cruise-weighted fCO2 values) in these products were
found to have missing values for a small number of grid cells, as a result
of an inconsistency between the algorithms used for computing the weighted
and unweighted gridded products. This was both in time and in position. This
error was corrected in the gridded data products for version 3. Note that
this error remains present in the gridded products for versions 1 and 2.
In summary, SOCAT version 3 is a significant update of version 2. It
provides a 58-year record (1957–2014) of 14.7 million surface ocean
fCO2 values for the global oceans and coastal seas. It has higher-quality data with better documentation than version 2. Addition of a flag of
E has enabled inclusion of calibrated fCO2 values from alternative
sensors and platforms. All surface ocean fCO2 values now have an
accuracy estimate, embedded in the data set QC flag. Automated quality
control checks during version 3 data upload have identified outliers. The
graphical interface of the Data Set Viewer has been vastly improved. These
characteristics of version 3 are described in more detail in Sects. 4 to
6.
Fair Data Use Statement for SOCAT version 3
The Surface Ocean CO2 Atlas provides access to a vast amount of surface
ocean CO2 data from the global oceans and coastal seas, painstakingly
collected by marine carbon scientists around the world over 58 years. These
data sets represent an important scientific output by these scientists.
Individual researchers and the marine carbon community make these data
public in SOCAT, such that they are available for scientific research and
for informing policy (Sects. 7 and 8). Nonetheless, it is important that the
data providers receive credit for the data that they collected. This will
provide data providers with vital evidence of how their data are being used,
enabling successful funding applications for future data collection.
Seasonal distribution of surface water fCO2 (µatm) for
the months (a) January through March, (b) April through June, (c) July through
September and (d) October through December in the years 2000 through 2009 in
SOCAT version 3 for data sets with flags of A to E (after Bakker et al.,
2014).
Activities and participants in SOCAT version 3 and the automation
(after Bakker et al., 2014). Regional group leads are in Table 4.
ActivityParticipantsGlobal groupBakker (chair), Currie, Kozyr, Metzl, O'Brien, Olsen, Pfeil, Pierrot, TelszewskiData retrieval, upload, fCO2 calculationLanda, Pfeil, Olsen, SmithLive Access Server for data upload, quality control and data viewersSmith, O'Brien, Manke, Hankin, SchweitzerInclusion of sensorsWanninkhof, Steinhoff, Bakker, Bates, Boutin, Olsen, SuttonAutomation (version 3)O'Brien, Smith, S. D. Jones, Landa, Manke, Olsen, Pfeil, Schweitzer, BakkerAutomation (metadata, version 4)As automation for version 3, plus Shrestha, RanjeetQuality controlAlin, Bakker, Barbero, Bonou, Castle, Cosca, Currie, Evans, Featherstone, Greenwood, Harasawa, Hauck, Humphreys, Hunt, Ibánhez, Lefèvre, Metzl, Nakaoka, Paterson, Schuster, Skjelvan, Steinhoff, Sullivan, Sutton, Tilbrook, WadaData products, archivingPfeil, Smith, Kozyr, Manke, O'Brien, Schlitzer, SiegerMatlab code for reading productsPierrot, LandschützerWebsitePfeil, Bakker, Landa, MetzlMeetingsBakker, Cosca, O'Brien, Steinhoff, Telszewski
Regions with their leads in version 3 (after Bakker et al., 2014).
The regions are the same as in version 2.
RegionDefinitionLead(s)Coastal and marginal seas< 400 km from land; 70∘ N to 30∘ S for 100∘ W to 43∘ E; 66∘ N to 30∘ S elsewhereAlinArctic OceanNorth of 70∘ N for 100∘ W to 43∘ E; north of 66∘ N elsewhere, incl. coastal watersMathisNorth Atlantic70 to 30∘ NSchusterNorth Pacific66 to 30∘ NNojiriTropical Atlantic30∘ N to 30∘ SLefèvreTropical Pacific30∘ N to 30∘ SCoscaIndian OceanNorth of 30∘ SSarmaSouthern OceanSouth of 30∘ S, incl. coastal watersTilbrook, Metzl
Meetings for SOCAT version 3 and the ongoing SOCAT automation. The
meeting reports are available on the SOCAT website
(http://www.socat.info/meetings.html).
TimingMeetingLocationReferenceMay 2012Automation planning meetingNOAA-PMEL, Seattle, USASOCAT (2012a)July 2012Progress meetingEpochal Centre, Tsukuba, JapanSOCAT (2012b)June 2013SOCAT side event, release of version 29th International Carbon Dioxide Conference, Beijing, ChinaSOCAT (2013b)June 2014Community eventIMBER Open Science Conference, Bergen, NorwaySOCAT (2014a)October 2014Automation meetingNOAA-PMEL, Seattle, USASOCAT (2014b)September 2015SOCAT and SOCOM event, release of version 3, launch of automation system, SOCOM science.SOLAS Open Science Conference, Kiel, GermanySOCAT and SOCOM (2015)
Furthermore, the assembly, quality control and archiving of SOCAT data
products involve many data managers and scientists (Tables 3 and 4).
Planning meetings and community events have proved effective in informing
SOCAT contributors and users, in discussing SOCAT progress and in setting
SOCAT strategy (Table 5).
The SOCAT Fair Data Use Statement therefore contains an urgent request to
generously acknowledge the contribution by SOCAT data contributors and
investigators. Ideally users will invite large data providers to contribute
to regional studies and, if they do, to co-author relevant papers. Citation
of relevant scientific articles by data providers is a good scientific
practice. The following Fair Data Use Statement applies to SOCAT data
products (SOCAT, 2016): the synthesis and gridded SOCAT products are a
result of scientific effort by data providers, data managers and quality
controllers. It is important that users of the SOCAT products fairly
acknowledge this effort. This will help generate funding for continuation of
observational products and promote further sharing of data.
We expect the following from users of SOCAT data products:
To generously acknowledge the contribution of SOCAT data providers and
investigators in the form of invitation to co-authorship, reference to
relevant scientific articles by data providers or by naming the data
providers in the acknowledgements. Specifically, in regional studies, users
should invite large data providers, who frequently possess valuable expert
knowledge on data and region, to collaborate at an early stage, which may
lead to an invitation of co-authorship. We recognise that co-authorship is
only justified in the case of a
significant scientific contribution to a publication and that provision of
data on its own does not warrant co-authorship.
To cite SOCAT and its data products as follows:
version 3: this study;
version 2: Bakker et al. (2014);
version 1 (synthesis data products): Pfeil et al. (2013);
version 1 (gridded data products): Sabine et al. (2013) and Pfeil et al.
(2013).
To include the following text in the acknowledgements: “The Surface Ocean CO2 Atlas (SOCAT)
is an international effort, endorsed by the International Ocean Carbon
Coordination Project (IOCCP), the Surface Ocean Lower Atmosphere Study
(SOLAS), and the Integrated Marine Biogeochemistry and Ecosystem Research
program (IMBER), to deliver a uniformly quality-controlled surface ocean
CO2 database. The many researchers and funding agencies responsible for
the collection of data and quality control are thanked for their
contributions to SOCAT.”
To report problems to submit@socat.info.
To inform submit@socat.info of publications in which SOCAT is
used.
The Fair Data Use Statement (SOCAT, 2016) replaces the earlier “SOCAT Data
Policy” (SOCAT, 2013a; Bakker et al., 2014). The text has been phrased more
strongly and examples of the application of the Fair Data Use Statement have
been added. The Fair Data Use Statement is available in full on the SOCAT
web pages (e.g. http://www.socat.info/SOCAT_fair_data_use_statement.htm).
The revision follows concerns raised by SOCAT data providers and discussions
among SOCAT scientists at two recent community events (SOCAT, 2014a; SOCAT
and SOCOM, 2015).
Data assembly and quality control in version 3Data retrieval and data upload on the SOCAT Upload Dashboard
In version 3, new and updated data sets were obtained from the Carbon
Dioxide Information Analysis Centre (CDIAC), PANGAEA® and public websites. In addition, many data sets were directly submitted
to SOCAT. As well as 887 new data sets, version 3 also contains 1258 updated
version of data sets previously submitted to versions 1 and 2, with revised
metadata or data. Some of these were updates of data sets previously
suspended from SOCAT (e.g. Table 10 in Bakker et al., 2014).
As in previous versions, all new and updated data sets were put in a uniform
format (Pfeil et al., 2013). Similar to version 2, an expocode was assigned
to all data sets, including moorings and drifters (Bakker et al., 2014). In
general, an expocode consists of 12 characters, describing the country, the
vessel or platform, and the data set start day (Swift, 2008). The expocode
320620090306, for example, indicates a data set collected on the US (32)
ship R/V Nathaniel B. Palmer (06) with the first day of the cruise on 6 March 2009. There are
a few exceptions to this. If two American mooring data sets (which always
start with 3164) have the same start date, they will end with “-1” and “-2”,
corresponding to an expocode of 14 characters.
In version 3, the SOCAT data managers used the new SOCAT Upload Dashboard
for upload of data and metadata (Table 1). All data sets previously included
in versions 1 and 2 were also uploaded, automatically screened for obvious
outliers and added to version 3 via the SOCAT Upload Dashboard (Table 1).
This new capability is an important step in the ongoing SOCAT automation
effort and integrates data and metadata upload, (re)calculation of
fCO2, automated data checks, data visualisation and data submission
in a single application which is tightly coupled to the SOCAT QC Editor.
Once fully operational in version 4, the Upload Dashboard will allow data
providers to upload, verify and submit their data for SOCAT quality control.
Not all data sets had time stamps which included seconds. In such cases,
multiple occurrences of a time stamp were often present. Artificial seconds
were added to data sets with 50 or more duplicate time stamps. For these data
sets, evenly distributed artificial seconds were added for each equal time
stamp. However, if there were less than 50 duplicate times in a data set, a
WOCE flag of 4 was generated for the fCO2rec values (or
“recommended” fCO2 values; see Sect. 4.2) with duplicate time stamps
during the automated data checks (Sect. 4.3). Adding artificial seconds is
time-consuming and there was insufficient time available for adding
artificial seconds to all duplicate times in all data sets.
(Re)calculation of fCO2
Data providers reported CO2 values as xCO2, pCO2 and/or
fCO2, at the equilibration temperature (Tequ) and/or the sea surface
temperature (SST or intake temperature). In order to ensure a coherent SOCAT
synthesis product, surface water fCO2 values at sea surface temperature
were recalculated from the reported CO2 values using a strict
calculation protocol with the following procedure (quoting Pfeil et al.,
2013):
when possible, (re)calculate fCO2;
the preferred starting point for the calculations is xCO2, then
pCO2, and finally fCO2;
minimise the use of external data required to complete the calculations.
Algorithms and surface water CO2 parameters used in the
calculation of recommended fCO2 (fCO2rec) at sea surface
temperature in version 3 (after Pfeil et al., 2013). Algorithm 1 was the
preferred method, followed by algorithm 2 and so forth. The algorithm used
for each data set is stated in the output files (Table 9). In the case of
incomplete reporting, NCEP (National Centers for Environmental Prediction)
atmospheric pressure (Kalnay et al., 1996; NCEP, 2014) and WOA (World Ocean
Atlas) 2005 salinity (Antonov et al., 2006) were applied.
1 Atmospheric pressure was not reported in the original data file.
2 Salinity was not reported in the original data file.
In total, 14 algorithms were used for (re)calculating these “recommended”
fCO2 (fCO2rec) values from the xCO2, pCO2 and/or
fCO2 values reported by the data providers (Table 6). The particular
algorithm used for a given data set is included in the data products
(Sect. 5). Equations recommended by Dickson et al. (2007) were applied for
the conversion of the dry CO2 mole fraction to pCO2, for the
calculation of the water vapour pressure and for the correction of
pCO2 to fCO2 (Pfeil et al., 2013). The temperature correction
suggested by Takahashi et al. (1993) was used to correct for temperature
change between the seawater intake and the equilibrator. Atmospheric pressure
from reanalysis and climatological values of salinity were used in the
calculation if in situ values had not been reported (Table 6). The 2014
version of the atmospheric pressure data product was used (NCEP, 2014), which
is an update of the 2012 data product used in the previous SOCAT version
(NCEP, 2012). Sea surface salinity was from the World Ocean Atlas (WOA) 2005
(Antonov et al., 2006). Full details on the external pressure and salinity
products are in the footnotes of Table 9. Note that the use of external
atmospheric pressure data would rule out data set quality control flags of A
and B during subsequent quality control, while use of external salinity
values would not affect the data set quality control flag (Sect. 4.4).
An important change relative to earlier versions is that the
(re)calculation in version 3 took place using Ferret scripts on the new
SOCAT Upload Dashboard after data upload (Sect. 4.1), rather than in Matlab
before the bulk upload of the data (Table 1). The implementation of the
Ferret scripts enables full integration of SOCAT data submission,
(re)calculation of fCO2 and quality control on a single software
platform. This streamlines and simplifies the SOCAT data flow. The Matlab
code used for the (re)calculation in versions 1 and 2 was transferred to
Ferret scripts on the Upload Dashboard for version 3. The new Ferret scripts
were checked by comparing fCO2rec values in version 2 calculated using
Matlab and new values calculated using Ferret. Almost all new values were
within 0.01 µatm of the value calculated in Matlab, if not identical
to it. Significant changes (smaller than 5 µatm) for less than 200
data points were attributed to changes in atmospheric pressure from
reanalysis (Table 1).
Automated data checks
Criteria for the automated data checks and the action taken in
version 3. In the case of duplicate time stamps, artificial seconds were
generated. If there were less than 50 duplicate times in the data set, a
WOCE flag of 4 was given. For other parameters, a flag of 4 was
automatically assigned to the fCO2rec value if their values were
outside a specified range. Criteria not directly affecting fCO2rec
values will be revised for version 4 (Sect. 4.3).
ParameterUnitCriteriaActionTime–Duplicate timesArtificial seconds added; flag of 4 if < 50 duplicate times in data set.Sampling depth, waterm<-20 or > 20flag of 4Salinity–< 0 or > 50flag of 4Sea surface temperature∘C<-8 or > 50flag of 4Equilibrator temperature∘C<-10 or > 45flag of 4Atmospheric pressurembar< 800 or > 1200flag of 4Equilibrator pressurembar< 800 or > 1200flag of 4xCO2, pCO2, fCO2 waterµmol mol-1 or µatm< 0 or > 10 000flag of 4xCO2, pCO2, fCO2 airµmol mol-1 or µatm< 0 or > 10 000flag of 4ΔxCO2, ΔpCO2, ΔfCO2µmol mol-1 or µatm<-10 000 or > 10 000flag of 4xH2O equilibrationmmol mol-1< 0 or > 200flag of 4WOCE flag, from PI–< 1 or > 9flag of 4Air temperature∘C<-35 or > 60flag of 4Relative humidity%< 0 or > 100flag of 4Specific humidity–< 0 or > 40flag of 4Wind direction∘< 0 or > 360flag of 4Wind speedm s-1< 0 or > 50flag of 4Ship direction∘< 0 or > 360flag of 4Ship speed, from PIkm h-1< 0 or > 100flag of 4Ship speed, calculatedkm h-1> 720flag of 4 for following point
A newly developed, automated data checker performed checks on parameters
directly influencing the position, time or calculation of fCO2rec
values (Tables 1 and 7). A WOCE flag of 4 (meaning a bad data point) was
assigned to all fCO2rec values with an incorrect position or time stamp
or otherwise identified as inaccurate. These automated checks were carried
out on all data in version 3 after (re)calculation of fCO2rec and
before submission to the quality control system.
Unintentionally, WOCE flags of 4 were also assigned for values which were out
of range in parameters which do not directly affect fCO2rec values,
such as wind speed and ship direction (Table 7). This resulted in a WOCE
flag of 4 being given to some good-quality fCO2rec values in newly
added and updated data sets in version 3. The criteria for the automated
checks will be reconsidered for version 4.
Automated data checks were also performed for data sets previously included
in versions 1 and 2 (and not updated in version 3). For these data sets all
WOCE flags of 4 assigned by the automated data checker, other than for
duplicate time stamps, were removed to preserve the data sets as reported
for version 2.
Secondary quality control
Secondary quality control is a key part of the creation of a high-quality
data synthesis product. During secondary quality control, scientists, also
known as quality controllers, assess the quality of each new and updated
data set by following a checklist of specific criteria, while also
examining the documentation of the data, known as metadata, for
completeness. The quality controllers assign a data set quality control flag
to each data set, based on their findings (Table 2).
The SOCAT quality control system has been upgraded (Table 1), as part of the
ongoing SOCAT automation. In particular, the ease of use, search options and
visualisation tools have been improved. Other modifications are that the
quality control criteria used for setting the data set quality control flag
now must be specified (by a tick box system) and that a comment needs to be
entered when assigning a WOCE flag (Table 1). Text relating to the tick
boxes and the comments accompanying WOCE flags are incorporated into the
quality control comments.
The definitions of the data set quality control flags in version 3 have been
revised relative to versions 1 and 2 (Tables 1 and 2) (Wanninkhof et al.,
2013b; Olsen et al., 2015). These revised QC criteria were applied to all
new and updated data sets in version 3, but not retrospectively to data sets
included in earlier versions, unless data providers had updated these.
Version 3 has data set quality control flags of A to E and WOCE flags of 2,
3 and 4 for individual fCO2rec values. For a data set to obtain a data
set quality control flag, it needs to meet all the criteria of that specific
data set flag (Table 2).
All data set flags now have an accuracy requirement for the fCO2rec
values. Previously, flags of C and D did not have an accuracy requirement
(Pfeil et al., 2013; Bakker et al., 2014). In version 3, requirements are an
accuracy of better than 2 µatm for flags of A and B, and of better than 5 µatm for flags of C and D and of better than 10 µatm for a
flag of E (Table 2). The accuracy requirement takes precedent over the
criteria that follow (Wanninkhof et al., 2013b; Olsen et al., 2015),
implying that, if the accuracy requirement is not met, a data set is given a
data set flag with a lower accuracy requirement, appropriate to the accuracy
of the data set.
Seven approved methods or SOP (standard operating procedure) criteria need
to be met for a data set quality control flag of A and B (after Pfeil et
al., 2013):
The data are based on xCO2 analysis, not fCO2 calculated from the
other carbon parameters pH, total alkalinity and dissolved inorganic carbon.
Continuous CO2 measurements have been made, not discrete CO2
measurements.
The CO2 detection is based on an equilibrator system and is performed
by infrared analysis or gas chromatography.
The calibration has included at least two non-zero gas standards, traceable
to World Meteorological Organization (WMO) standards.
The equilibrator temperature has been measured to within 0.05 ∘C
accuracy.
The intake seawater temperature has been measured to within 0.05 ∘C
accuracy.
The equilibrator pressure has been measured to within 2.0 hPa accuracy.
The requirement regarding the accuracy of the equilibrator pressure has been
relaxed to an accuracy of 2.0 hPa in version 3, replacing the earlier
requirement of 0.5 hPa, as an accuracy of 2.0 hPa in pressure is sufficient
for achieving an accuracy of 2.0 µatm in fCO2 (Wanninkhof et
al., 2013b; Olsen et al., 2015). The six other criteria are the same in all
SOCAT versions.
In version 3, a high-quality cross-over has become a prerequisite for a data
set flag of A, replacing the earlier requirement of “an acceptable
comparison (or cross-over) with other data” (Wanninkhof et al., 2013b; Olsen
et al., 2015). As in previous versions, a cross-over is defined by an
equivalent distance of less than 80 km between two data sets (Pfeil et al.,
2013). This criterion combines distance and time as ([Δx2+
(Δt×30)2]0.5)≤80 with distance x in kilometres
and time t in days. One day (or 24 h) of separation in time is equivalent
(heuristically) to 30 km of separation in space. According to this
definition, the maximum time separation (at a spatial distance of 0 km) is
64 h for a cross-over to occur. The new definition of a high-quality
cross-over between two data sets requires that differences in sea surface
temperature and fCO2rec between the data sets do not exceed
0.3 ∘C and 5 µatm, respectively. These criteria reflect
the test for a high-quality cross-over between two data sets with a flag of A
or B, i.e. each with an accuracy for fCO2rec of better than
2 µatm or a joint accuracy of better than 4 µatm with
1 µatm added to account for differences in time and space. A
temperature difference of 0.3 ∘C roughly corresponds to an
fCO2 difference of 5 µatm. “Inconclusive” cross-overs,
where differences in temperature or fCO2rec exceed these values, do
not qualify for a data set flag of A in version 3.
It is worth noting that meaningful high-quality cross-overs are rarely found
in coastal waters, near sea ice and in regions of freshwater influence
(ROFIs), as a result of high spatial variation in sea surface temperature
and fCO2rec, not for lack of measurement quality. Even if a small
number of sea surface temperature and fCO2rec values are within
0.3 ∘C and 5 µatm, this tends to be a coincidence rather
than a meaningful correspondence between data sets. This can be illustrated
for the US research ships Nathaniel B. Palmer and the Lawrence M. Gould, which have frequent high-quality
cross-overs in the open Southern Ocean but few high-quality cross-overs
near Palmer station, where they both make port calls.
In version 3, a data set with a flag of C “did or did not follow approved
methods or SOP criteria” (Wanninkhof et al., 2013b; Olsen et al., 2015).
This is an amendment from the earlier requirement that the data set “did not
follow approved methods or SOP criteria” (Pfeil et al., 2013; Bakker et al.,
2014). The new flag of E enables inclusion of fCO2 values from
calibrated alternative sensors and platforms (Wanninkhof et al., 2013b;
Olsen et al., 2015). A flag of E requires complete metadata and a
demonstrable accuracy for fCO2rec of better than 10 µatm by in
situ calibration of the sensor. The WOCE flags for individual fCO2rec
values are defined as 2 (good), 3 (questionable) and 4 (bad) in versions 1,
2 and 3 (Pfeil et al., 2013). New is the requirement to add a comment when
assigning WOCE flags of 3 and 4 (Table 1).
As in version 2, five additional guidelines were considered for open-ocean
fCO2rec values, away from sea ice. The guidelines were used for
assigning data set quality control flags and WOCE flags (after Pfeil et al.,
2013, and Bakker et al., 2014):
warming between the seawater intake and the equilibrator should be less than
3 ∘C;
warming rate should be less than 1 ∘C h-1, unless a sharp
temperature front is apparent;
warming outliers should be less than 0.3 ∘C, compared to
background data;
cooling between the seawater intake and the equilibrator is unlikely in
high-latitude oceans for an indoor measurement system;
zero or constant temperature difference between the equilibrator and
seawater intake usually indicates the absence of SST values.
As for SOCAT version 2, quality controllers were organised into eight regions,
each with a group lead (Table 4). The eight regions included the coastal and
marginal seas, the Arctic Ocean, the North and tropical Atlantic, the North
and tropical Pacific, the Indian Ocean, and the Southern Ocean. The quality
controllers gave data sets a quality control flag for each region they
crossed. As a final step, the data set quality control flags for the
different regions had to be reconciled.
Data products in version 3Overview of data products
Key characteristics of the SOCAT data products in version 3 (Sect. 5) (after Bakker et al., 2014). Data products differ in whether they include
data sets with flags of A to D or A to E and fCO2rec values with
a WOCE flag of 2 only or 2 to 4. Two data products provide access to
metadata. Quality control comments are available via the Table of Datasets
in the Data Set Viewer. The SOCAT website (http://www.socat.info) and the
web links in the footnotes provide access to the data products.
Data productCharacteristicsData set QC flagWOCE flagMetadataQC entriesFormat and accessIndividual data set filesAll original CO2 values and (re)calculated fCO2 values for data sets with flags of A–E.A–E2–4YesNoText files1Synthesis data set (i)Global and regional synthesis files.A–D only2 onlyNoNoText files2Synthesis data set (ii)Global synthesis file.E only2 onlyNoNoText file2Synthesis data set (iii)Global synthesis file.A–D only2 onlyOptionalNoODV3Subset of synthesis data set (j)Interactive. Data sets with flags of A–E and fCO2 values with flags of 2–4 can be selected.A–E default2 default; 2–4 if selectedNoNoText and NetCDF files4Subset of synthesis data set (jj)All original CO2 values and calculated fCO2 values for data sets with flags of A–E.A–E default2 default; 2–4 if selectedYesYesText and NetCDF files5Gridded data setGridded unweighted and data-set-weighted means of fCO2 values on a 1∘× 1∘ grid without any interpolation. Means are per decade, per year and per month. A monthly 0.25∘× 0.25∘ gridded data set exists for coastal regions.A–D only2 onlyNoNoNetCDF files6,7, ODV3
1 PANGAEA®: https://doi.org/10.1594/PANGAEA.849770.
2 CDIAC: http://cdiac.ornl.gov/ftp/oceans/SOCATv3/.
3 Ocean Data View: https://odv.awi.de/en/data/ocean/socat_fCO2_data/.
4 Data Set Viewer: http://ferret.pmel.noaa.gov/SOCAT_Data_Viewer/; select “Data Set”, then “Cruise data” and “SOCAT v3 data
collection”.
5 Table of Datasets via the Data Set Viewer4; select “Table of
Datasets”.
6 CDIAC: http://cdiac.ornl.gov/ftp/oceans/SOCATv3/SOCATv3_Gridded_Dat/.
7 Gridded Data Viewer: http://ferret.pmel.noaa.gov/SOCAT_Data_Viewer/; select “Data Set”, then “Current Version Gridded (v3)”.
Content of the individual data set files (IF) and the synthesis
files in SOCAT version 3 (after Bakker et al., 2014). The global synthesis
product is available as zip text files (ZIP) at CDIAC and in Ocean Data View
(ODV) format (Table 8). Subsets of the global synthesis data set can be
created via the Data Set Viewer (DSV), both in the main menu and via the
Table of Datasets. The first column lists column headers for the parameters
in the files.
Column headerIFZIPDSVODVUnitDescriptionExpocode/Cruise–√√√–Twelve-character expocodeVersion–√–√–Most recent SOCAT version in which data set was added (N) or updated (U)SOCAT_DOI–√√√–Digital object identifier for the individual data set and metadataQC_Flag–√√√–Data set quality control flags A, B, C, D and EDate/Time/Datetime√–√√–yyyy-mm-dd / hh:mm:ss (ISO8859 and other formats)yr/Year–√√–YearYear (UTC)*mon–√√–MonthMonth (UTC)*day–√√–DayDay (UTC)*hh/Hour–√√–HourHour (UTC)*mm/Minute–√√–MinuteMinute (UTC)*ss/Second–√√–SecondsSeconds (may include decimals)*Day of Year–––√Day of yearDay of year (UTC) with 1 January, 00:00, as 1.0.Longitude√√√√∘ E, ∘ WLongitude (0 to 360/-180 to 180)*Latitude√√√√∘ N, ∘ SLatitude (-90 to 90)*Depth water/Depth√√√√mWater sampling depth*1Sal/Salinity√√√√–Salinity on practical salinity scale*Temp/SST√√√√∘CSea surface temperature*Tequ/Temperature_Equi√√√√∘CEquilibrator chamber temperature*PPPP/Pressure_Atm√√√√hPaAtmospheric pressure*Pequ/Pressure_Equi√√√√hPaEquilibrator chamber pressure*Sal interp/WOA_SSS√√√√–Salinity from WOA2PPPP interp/NCEP_SLP√√√√hPaNCEP atmospheric pressure3Bathy_depth/ETOPO2_depth√√√√mETOPO2 bathymetry4Distance/dist-to-land√√√√kmDistance to major land massxCO2air_interp/GVCO2√√√√µmol mol-1Atmospheric xCO2 from GLOBALVIEW-CO2 (2014)5xCO2water_equ_dry√–––µmol mol-1xCO2 (water) at equilibrator temperature (dry air)*fCO2water_SST_wet√–––µatmfCO2 (water) at sea surface temperature (air at 100 % humidity)*pCO2water_SST_wet√–––µatmpCO2 (water) at sea surface temperature (air at 100 % humidity)*xCO2water_SST_dry√–––µmol mol-1xCO2 (water) at sea surface temperature (dry air)*fCO2water_equ_wet√–––µatmfCO2 (water) at equilibrator temperature (air at 100 % humidity)*pCO2water_equ_wet√–––µatmpCO2 (water) at equilibrator temperature (air at 100 % humidity)*fCO2rec√√√√µatmRecommended fCO2 calculated following the SOCAT protocolAlgorithm/fCO2_source√√√√–Algorithm for calculating fCO2rec (0: not generated; algorithm 1–14, Table 6)Flag/WOCE_CO2_Water√√√––WOCE flag for fCO2rec (2: good; 3: questionable; 4: bad)6fCO2 in wet air–––√µatmfCO2 (air) calculated for sea surface temperature and 100 % humidity from GVCO2Ocean – Air fCO2 Difference–––√µatmfCO2 difference between water and airVessel–––√–Name of vessel or platform
√ Available.
* If reported by the data originator.
1 If the intake depth has not been reported by the data originator, an
intake depth of 5 m has been assumed.
2 Sea surface salinity on the practical salinity scale extracted from
the World Ocean Atlas (WOA) 2005 (Antonov et al., 2006), available at
http://www.nodc.noaa.gov/OC5/WOA05/woa05nc.html, using the data
set s0112an1.nc from the “monthly” link at http://data.nodc.noaa.gov/opendap/woa/WOA05nc/ (last access: 1 September
2015). This data set is identical to that SOCAT version 2.
3 Atmospheric pressure extracted from the NCEP/NCAR (National Centers
for Environmental Prediction/National Center for Atmospheric Research)
40-Year Reanalysis Project on a 6-hourly, global, 2.5∘ latitude by
2.5∘ longitude grid (Kalnay et al., 1996; NCEP, 2014). This is an
update relative to the 2012 data set (NCEP, 2012) used in SOCAT version 2.
4 Bathymetry extracted from ETOPO2 (2006) 2 min Gridded Global
Relief Data. This data set is identical to that in SOCAT version 2.
5 GLOBALVIEW-CO2 (2014), downloading the “surface” reference type gives
the sine function of latitude versus time for the reference marine boundary
layer. This is an update relative to the 2012 version used in SOCAT version 2.
6 Individual data set files contain all fCO2rec data. Synthesis
files at CDIAC and via ODV contain data sets with a flag of A–D and
fCO2rec values with a WOCE flag of 2 (Table 6).
Gridded products and parameters reported for each grid cell in
SOCAT version 3 (after Sabine et al., 2013). Version 3 does not have a
monthly climatology.
ParameterUnitDecadalAnnualMonthlyMonthly 1/4∘× 1/4∘meanmeanmeancoastalNumber of data sets–√√√√Number of observations–√√√√fCO2 unweighted meanµatm√√√√fCO2 data-set-weighted meanµatm√√√√fCO2 maxµatm√√√√fCO2 minµatm√√√√fCO2 SD unweightedµatm––√√fCO2 SD weightedµatm––√√Latitudinal average offset from cell centre∘ N––√√Longitudinal average offset from cell centre∘ E––√√
In essence, the data products and data platforms are the same as for earlier
SOCAT versions with some modifications (Table 8). Improvements include a
major upgrade of the search and visualisation capabilities of the Data Set
Viewer (previously known as the Cruise Data Viewer) and uniform contents for
the files downloadable from the Data Set Viewer (Tables 1 and 9). Access to
the data products is via the SOCAT website (http://www.socat.info/) and the web addresses for the individual data
platforms (Table 8).
Quality-controlled recommended surface ocean fCO2 measurements in a
uniform format are available in individual data set files, in regional and
global synthesis files and in gridded form (Table 8). These three data
products can be accessed via the user-friendly, interactive online Data Set
Viewer and Gridded Data Viewer, by downloading data files, or in Ocean Data
View (Schlitzer, 2015). Similar to earlier versions, data sets with a
quality control flag of A to D and recommended fCO2 values with a WOCE
flag of 2 (good) are included in the synthesis files and gridded products.
Data sets with a flag of E are available in a separate synthesis file. Data
set flags of A to E and a WOCE flag of 2 for fCO2 values is the default
setting for the Data Set Viewer. Quality control comments can be accessed
via the Data Set Viewer (Table 8). While the SOCAT data products include
seawater temperature and salinity, as these are required for
(re)calculation of fCO2, these two parameters have not been quality-controlled to the high standards required by the physical oceanographic
community (SOCAT, 2014a).
As in earlier versions, each individual data set has a digital object
identifier (DOI), which provides a direct link to the metadata, including
the name and affiliation of the data provider. This DOI for the data set is
available for each recommended surface ocean fCO2 value in the
synthesis files. This enables users to easily identify the data provider and
to gain access to the original data set and to detailed information on the
data set, including any relevant peer-reviewed journal articles that we are
aware of. The Data Set Viewer now enables to search the data collection by
data provider. Data providers are also prominently displayed in the Table of
Datasets (access via the Data Set Viewer) (Table 8). A more detailed
description of the data products follows.
Individual data set files
Individual data set files are available for all data sets with flags of A, B,
C, D and E. Each individual data set has a DOI. The files contain all
original CO2 measurements and recommended fCO2 values with a WOCE
flag of 2, 3 and 4 (Table 8), as set by the data originator, by the automated
range checker or during the secondary quality control. The files also contain
other parameters, such as atmospheric pressure from reanalysis,
climatological salinity and the atmospheric CO2 mole fraction. Metadata
reported by the data provider accompany the files and links to the original
data sets are provided. The files are available in text format at
PANGAEA®
(https://doi.org/10.1594/PANGAEA.849770).
Global synthesis product
The global and regional synthesis files contain recommended fCO2 values
with a WOCE flag of 2 (good) for data sets with flags of A, B, C and D
(Table 8). A separate synthesis file is available for data sets with a flag
of E. Each line of the global and regional synthesis files contains the DOI
for the corresponding individual data set, as archived at
PANGAEA®, thus enabling retrieval of metadata,
name of the data provider and the original CO2 values reported by the
data provider (Table 9) (Sect. 5.2). Global and regional files are available
as compressed zip text files via CDIAC (http://cdiac.ornl.gov/ftp/oceans/SOCATv3/). Matlab code is available for
reading these text files. Regional files for the SOCAT regions (Table 4)
only contain data for a specific region with no overlap, so that many data
sets on moving ships are split between several regional files. The global
synthesis product for data sets with flags of A to D is also available in
Ocean Data View format (https://odv.awi.de/en/data/ocean/socat_fCO2_data) (Schlitzer, 2015).
Subsetting the global synthesis product
The interactive Data Set Viewer
(http://ferret.pmel.noaa.gov/SOCAT_Data_Viewer/) has powerful search
capabilities and an attractive graphical interface following the upgrade for
version 3 (Tables 1 and 8). The SOCAT Data Viewer now hosts the Data Set
Viewer and the Gridded Data Viewer on a single software platform. The move of
the Data Set Viewer onto this platform in version 3 streamlines access to the
SOCAT synthesis and gridded products via a Live Access Server (LAS). The move and upgrade of the Data Set Viewer accompany that of
the closely associated SOCAT quality control system (Sects. 2 and 4.4).
The Data Set Viewer enables subsetting of the global SOCAT data collection.
The default setting is for data sets with flags of A to E and “valid”
fCO2 values with a WOCE flag of 2 for years 1957 to 2014, corresponding
to 3640 data sets for version 3. Recommended fCO2 values with flags of
3 and 4 can also be selected. In the Data Set Viewer, the user can select
data sets by, for example, year, month, region, platform/vessel, “valid”
values, data provider, data set flag, WOCE flag and SOCAT version. It is
also possible to define limits for the values shown. Maps of surface ocean
fCO2 demonstrate the data distribution, as well as temporal and spatial
variation in surface ocean fCO2 for the selected data sets (Figs. 1, 3
and 4). High-quality figures can be rapidly created for scientific
presentations to fellow scientists, funding agencies and policy makers.
Scatter plots or property–property plots, available via the Correlation
Viewer, can be used to depict any two variables of a data set or data sets,
enabling further investigation. Examples are figures of fCO2 or sea
surface temperature as a function of time, salinity or latitude.
The data shown on the Data Set Viewer have been subsampled for system
efficiency, such that only part of the data are shown. Visual display of
these data sets on maps in the Data Set Viewer is subject to further
improvement, as the interpolation of sparse data ignores topographic
features. As a result cruise tracks occasionally appear to cross land. This
issue does not affect the data sets themselves. The Table of Datasets
(previously known as the Table of Cruises) can be accessed from the Data Set
Viewer. It provides access to the original CO2 measurements; fCO2
values with a WOCE flag of 2, 3 and 4; metadata; comments entered during
quality control; and thumbnail plots (Table 8) (Sect. 4.4). Thumbnail plots
consist of a series of scatter plots for key parameters in an individual
data set and are useful for obtaining a quick overview of a data set. Both
the Data Set Viewer and the Table of Datasets allow download of data sets in
NetCDF and text format (Tables 8 and 9). All downloadable files now contain
the same parameters (Table 9).
The performance speed of the Data Set Viewer may be slower if the full SOCAT
data collection is accessed. Subsetting the data collection by decade or
region considerably improves the system speed of the Data Set Viewer.
Updates of web browsers occasionally result in less than perfect web access
to the Data Set Viewer. In such cases, another web browser may provide
better access. The web manager (socat.support@noaa.gov) may
have useful advice.
Gridded products
The protocol for the creation of gridded fCO2 products in version 3
follows that for versions 1 and 2, as described by Sabine et al. (2013). The
gridded products have a 1∘ latitude by 1∘ longitude
resolution with a higher resolution of 0.25∘ latitude by
0.25∘ longitude for coastal seas. Recommended surface ocean
fCO2 values from 1970 to 2014 with a WOCE flag of 2 from data sets with
flags of A to D have been used for the gridded products. The gridded
products have no interpolation – i.e. there is no gap-filling and grid cells
without fCO2 values are empty. No correction is made for the long-term
increase in surface ocean fCO2.
Gridded fCO2 values are reported as unweighted means and as data-set-weighted means (Sabine et al., 2013). In an unweighted mean, all
fCO2 values in a grid cell have equal weight for calculating the mean.
In a data-set-weighted mean, averages of the fCO2 values are calculated
per data set for each grid cell, before calculating averages of these data
set means. In version 3, a small error was corrected in the procedure for
creating the gridded data products. This resulted in a small reduction in
the number of grid cells with data in the data-set-weighted product for
versions 1 and 2. This problem was corrected in gridded files in version 3
with the revised gridded data set made public on 2 November 2015.
Gridded products are available per decade, per year and monthly per year
(Table 10). A monthly climatological fCO2 product has not been made
available for version 3, out of concern, that such a product without a
correction for the long-term increase in fCO2 could be misinterpreted.
Gridded fCO2 values may have temporal bias, for example, if only summertime fCO2 values are available for a grid cell in the annual gridded
product. Several auxiliary variables are reported per grid cell, for
example the number of data sets and observations and the standard deviation
in the unweighted and weighted fCO2 mean values (Table 10).
Gridded products are available in NetCDF format at CDIAC (http://cdiac.ornl.gov/ftp/oceans/SOCATv3/SOCATv3_Gridded_Dat/) (Table 8). Matlab code is available for
reading the files. The Gridded Data Viewer (http://www.socat.info/; select “Gridded Data Viewer”) provides easy access
to the gridded data products, as well as comparison to gridded products from
earlier versions. Figures 5 and 6 have been made with the gridded data
product.
Bar plots of the number of decadal mean fCO2 values per 4 µatm range for data-set-weighted gridded fCO2 values in version
3. Red bars indicate the mean atmospheric value (µmol mol-1) at
Mauna Loa, Hawaii, for each decade (Tans and Keeling, 2016). Note the
changing scale on the y axis. Similar figures have been made for versions 1
and 2 (Olsen et al., 2013; Sabine et al., 2013).
(a) Number of unique months and (b) total number of months with
fCO2 values per 1∘× 1∘ grid cell for 1970 through
2014 in SOCAT version 3. Similar figures are available for versions 1 and 2
(Sabine et al., 2013; Bakker et al., 2014). The higher resolution of
0.25∘× 0.25∘, available for coastal seas (Sect. 5.5),
is not shown.
Future developmentsDirect data upload and annual SOCAT releases
The SOCAT automation system was formally launched on 7 September 2015 (SOCAT
and SOCOM, 2015). Data providers can now directly upload, check and submit
their data on the SOCAT quality control system for future SOCAT versions.
The SOCAT automation was first discussed at the 2011 Data2Flux Workshop in
Paris (SOCAT, 2011). The automation system was designed at the 2012
Automation Planning Meeting (SOCAT, 2012a) and approved shortly afterwards
by global and regional group leads (SOCAT, 2012b) (Table 5). The automation
system has been implemented in the background, with all the work for the
biannual SOCAT releases of versions 2 and 3 taking place in the foreground
(Bakker et al., 2014, this study). This considerable achievement has been
made possible by the hard work and planning of the NOAA-PMEL and University
of Washington Live Access Server team and other members of the SOCAT
automation team (Table 3).
The new automation system allows data providers to upload their data, to
check their data with the automated data checker and to visualise their
data. Finally, if the data provider deems the data of good quality, he or
she can submit them to the SOCAT quality control system. As part of the data
submission to SOCAT, the data provider is encouraged to make the original
data set public, for example at CDIAC (SOCAT and SOCOM, 2015), either
immediately or upon the release of the SOCAT version of which the data set
is part. The automation system will enable annual SOCAT releases. The
timetable for future SOCAT versions envisages that data upload will end in
late January of each year and quality control in late March for a release in
summer later that year. With the new system it is now possible to upload and
submit data to SOCAT, while quality control of previously submitted data
sets is in progress. Thus, both data upload and quality control can now be
carried out in parallel. Data upload and quality control for the next SOCAT
version will start as soon as they have finished for the preceding version.
Thus, the automation system will enable rolling, continuous data upload and
quality control, as well as annual SOCAT releases. The system for automated
data upload is under continuous improvement. Metadata templates and upload
will be integrated into the SOCAT data upload system. Other planned
improvements include searchable information for funding agency and entry of
preliminary data set flags by the data provider. A number of additional
features are being considered for future SOCAT versions, some of which may
be implemented as early as version 4. These are discussed below.
Atmospheric CO2 values
Data providers can now submit measurements of atmospheric CO2 mole
fraction, made in parallel to surface water fCO2. A separate WOCE flag
will be created for measurements of the atmospheric CO2 mole fraction
in future SOCAT versions. Once quality control has been carried out on the
atmospheric CO2 measurements, such values will be included in the SOCAT
data products.
In future, atmospheric fCO2 will be calculated from atmospheric
xCO2 values, both from the measurements and from GLOBALVIEW-CO2 (2014)
values. New graphics will enable comparison of surface ocean fCO2
values to atmospheric fCO2 values. The graphs will become an important
quality control tool. Future data products will contain atmospheric
fCO2 values calculated from atmospheric measurements and from
GLOBALVIEW-CO2, in addition to the atmospheric mole fractions from
GLOBALVIEW-CO2 already part of the SOCAT data products (Table 9).
Additional surface water parameters
In 2014, SOCAT scientists decided to allow inclusion of additional surface
water parameters accompanying surface water fCO2 values in SOCAT data
output files (SOCAT, 2014a). Such additional parameters might include
dissolved inorganic carbon, total alkalinity, pH, nutrients, methane
(CH4) and nitrous oxide (N2O) concentrations. SOCAT scientists
will not carry out quality control on these additional parameters, but would
welcome collaboration with other communities taking responsibility for this.
These additional parameters will be made public in parallel to the official
SOCAT releases. The extra parameters will be posted in separate data files
to emphasise that they have not been quality-controlled. A SOCAT and MEMENTO
(MarinE MethanE and NiTrous Oxide; Bange et al., 2009) working group is
considering the way forward for surface water CH4 and N2O
measurements (SOCAT and SOCOM, 2015).
Impact and scientific highlights of SOCATA multi-decade record of surface ocean fCO2 values
SOCAT provides a record of the history of surface ocean CO2 research
(Fig. 3). Initial, exploratory surface water CO2 measurements in the
late 1950s, 1960s and 1970s were followed by more frequent CO2 data
collection on research ships in the 1980s and large (inter)national
research programs, such as the World Ocean Circulation Experiment (WOCE),
the Joint Global Ocean Flux Study (JGOFS) and the Tropical Atmosphere Ocean
(TAO) network in the 1990s. The operation of CO2 instruments on ships part of the Carbon
Voluntary Observing Ships (Carbon VOS) programme, also referred to as the Ships Of
Opportunity Programme (SOOP), strongly increased the number of available
fCO2 values from the 1990s onwards. Data availability in the SOCAT
collection has increased 4-fold from 0.2 to 0.4 million fCO2 values
per year for the years 1995 to 2000 to 1.0 to 1.2 million values per year
for 2005 to 2012. Nevertheless, large gaps are notable in the data
collection since the year 2000, e.g. in the Indian Ocean, the South Pacific
Ocean, the Mediterranean Sea, the East China Sea, the Malay Archipelago and
the Sea of Okhotsk. Elsewhere, in the Arctic Ocean, measurements are being
reported for the first time.
The seasonal distribution of surface ocean fCO2 values in the
relatively data-rich decade from 2000 to 2009 is shown in Fig. 4. This
figure highlights the lack of winter data in the high-latitude oceans, as
well as the opposing seasonal cycle of surface ocean fCO2 in the
subtropical and temperate oceans (Takahashi et al., 2002). The distribution
of surface ocean fCO2 values per decade clearly shows the long-term
increase in surface ocean fCO2 (Fig. 5), while suggesting that surface
ocean fCO2 has increased slower than the atmospheric CO2
concentration since the 1990s. Figure 6 visualises the data availability as
the number of months in each 1∘ latitude by 1∘ longitude
grid cell with fCO2 values since 1970, both as unique months and as
total months.
Impact of SOCAT
(a) Number of publications citing or naming SOCAT per year
by type of publication and (b) scientific applications of SOCAT in
peer-reviewed, scientific articles. The number of publications in 2016 only
includes publications before 22 April 2016. Types of publications are
peer-reviewed, scientific articles, PhD and MSc theses, high-impact reports,
book chapters and all other publications. Scientific applications in
peer-reviewed, scientific articles are grouped as reference (only) to the
SOCAT data synthesis; use of figures or tools based on SOCAT; use of surface
ocean fCO2 values for various environmental studies; modelling; trend
analysis in ocean acidification studies; fCO2 process studies; and
carbon budgeting of coastal seas, open ocean and land
systems. These scientific applications are discussed in Sects. 7.2 and 7.3. A
list of publications citing or naming SOCAT is available on the SOCAT website
(www.socat.info/publications.html).
SOCAT and its data products are cited or named in influential international
reports, in more than 100 peer-reviewed scientific publications, PhD and
master's theses, book chapters and numerous other publications, as listed on
the SOCAT website (http://www.socat.info/publications.html).
Figure 7 shows the rapid increase in such publications, since the initiation
of SOCAT in 2007 (IOCCP, 2007) and the first SOCAT release in 2011 (Pfeil et
al., 2013; Sabine et al., 2013). The SOCAT data collection forms the basis
of several data products (http://www.socat.info/products.html)
and diverse scientific applications. These include a dozen mapping products
of surface ocean pCO2 and air–sea CO2 fluxes for the global oceans
(see overview in Rödenbeck et al., 2015). The SOCAT gridded product and
one data product based on SOCAT (Landschützer et al., 2015) are
integrated with the ESMValTool (Eyring et al., 2016) for routine evaluation
of Earth system models. For the same purpose, the SOCAT gridded product is
currently being integrated into the Obs4MIPs (Observations for Model
Intercomparison Projects) data repository (Ferraro et al., 2015). Citation
of SOCAT in high-impact reports, scientific applications of SOCAT and
scientific findings based on SOCAT are discussed below.
The importance of the SOCAT synthesis is highlighted by its citation in
three categories of high-impact reports, notably reports on ocean observing
systems, assessments of climate change and global carbon budgeting,
including carbon observing strategies, and ocean acidification studies.
Reports on ocean observing systems include publications from OceanObs'09
(Borges et al., 2010; Monteiro et al., 2010), the Framework for Ocean
Observing (FOO, 2012), the Tropical Pacific Observing System 2020 (Mathis et
al., 2014) and the 2nd International Indian Ocean Expedition (Hood et
al., 2015).
Assessments of climate change and global carbon budgeting citing SOCAT are
the 2013 IPCC (Intergovernmental Panel on Climate Change) report (Ciais et
al., 2013) and the State of the Climate in 2014 (Blunden and Arndt, 2015).
Three reports describing a global carbon or climate observing system
highlight SOCAT, notably the GEO (Group on Earth Observations) Carbon
Strategy (Ciais et al., 2010), the Carbon Strategy for Carbon Observations
from Space (CEOS, 2014), and Status of the Global Observing System for Climate (GCOS, 2015).
A number of ocean acidification studies cite SOCAT, notably reports by the
International Council for the Exploration of the Sea (ICES, 2013), the Joint
OSPAR/ICES Ocean Acidification Study Group (ICES, 2014), the Global Ocean
Acidification Observing Network (Newton et al., 2014) and the Secretariat of
the Convention on Biodiversity (2014).
Scientific applications of SOCAT
SOCAT is used for a variety of scientific applications (Fig. 7b), some of
which imply a wider relevance for SOCAT data products than envisaged during
the creation of SOCAT (IOCCP, 2007). Scientific applications of SOCAT
include
figures of surface ocean CO2 observations;
use of SOCAT tools and protocols;
use of surface ocean fCO2 in diverse environmental studies;
model–data comparison, model evaluation and data assimilation;
detection of ocean acidification trends;
regional process studies of surface ocean fCO2;
quantification of coastal ocean carbon sinks and sources;
quantification of the ocean carbon sink and its variation;
quantification of the land carbon sink.
These applications are roughly listed in order of the increasing importance
of the SOCAT synthesis for the studies. The use of the SOCAT data collection
in peer-reviewed, scientific publications is evolving. Initial publications
made reference to the ongoing synthesis activity. Actual use of the SOCAT
data collection started as soon as version 1 was released in 2011 (Pfeil et
al., 2013; Sabine et al., 2013). Studies that heavily rely on SOCAT data
products, such as modelling, ocean acidification trend analysis and carbon
budgeting, represent one-third to half of the scientific publications citing
or naming SOCAT from 2013 onwards.
Examples of scientific applications of SOCAT are given below. There is no
strict separation between the different types of applications identified
here, with several studies belonging to more than one type of application.
Many of the studies use surface ocean pCO2 values, derived from the
fCO2 values reported in SOCAT data products.
Figures of surface ocean CO2observations.
Newly created figures based on the SOCAT data collection and existing
figures from SOCAT publications have been used in scientific publications.
Such figures generally highlight the availability or lack of surface ocean
CO2 data in specific regions or seasons or over time (Chierici et al.,
2012; Regnier et al., 2013; Wanninkhof et al., 2013a; Ciais et al., 2014;
Majkut et al., 2014a; Brévière et al., 2015; Hofmann et al., 2015).
Use of SOCAT tools and protocols. A variety of tools and protocols
has been developed in SOCAT. One of these is the definition of a continental
margin mask which defines coastal waters as waters within 400 km from land
(Pfeil et al., 2013). Evans and Mathis (2013) and Evans et al. (2015) use
this continental margin mask. Other studies have adopted SOCAT protocols for
calculation of fCO2 (Ulfsbo et al., 2014) and quality control (Sutton
et al., 2014b).
Use of surface ocean fCO2in diverse environmental studies. Regional fCO2 values from SOCAT are used in
diverse environmental studies with topics ranging from ocean acidification
to genomics, gas transfer velocity and evaluation of independent
measurements (Blomquist et al., 2014; Larsen et al., 2014; Holding et al.,
2015; Marrec et al., 2015; Bonou et al., 2016; Reum et al., 2016). Reum et
al. (2016) assess the co-variance between pCO2, pH and other
environmental parameters with the aim to improve the design of future ocean
acidification incubation experiments. Larsen et al. (2014) establish a
significant correlation between gene expression for the relative turnover
(synthesis or consumption) of CO2 and surface ocean fCO2. SOCAT
fCO2 values are also used for evaluation of surface ocean fCO2
estimates from eddy correlation (Blomquist et al., 2014) or from other
carbonate parameters (Bonou et al., 2016) and for evaluation of regression
parameterisations (Marrec et al., 2015; Xu et al., 2016).
Model-to-data comparison, model evaluation and data assimilation.
SOCAT data products are used for model-to-data comparison, model evaluation
and data assimilation in coupled and ocean-only biogeochemical models.
Model-to-data comparisons of surface water fCO2 have been carried out
for seasonal (Tjiputra et al., 2012; Arruda et al., 2015) to multi-year timescales (Tjiputra et al., 2014; McKinley et al., 2016). In several studies,
model data are subsampled to surface ocean pCO2 observations from SOCAT
(Séférian et al., 2014; Tjiputra et al., 2014; Turi et al., 2014).
Cooley et al. (2015) evaluate surface ocean pCO2 values from an
integrated assessment model with pCO2 observations from SOCAT and other
sources. SOCAT data products are supporting model evaluation in context of
the Coupled Model Intercomparison Project (CMIP) and beyond (Eyring et al.,
2016). The SOCAT data collection is used for assimilation of surface ocean
pCO2 values in global ocean biogeochemical models (While et al., 2012;
Simon and Bertino, 2013, as cited in Gehlen et al., 2015). Ocean
biogeochemical models have many applications, such as quantification and
attribution of trends in the ocean carbon sink (Le Quéré et al.,
2014, 2015a, b; Séférian et al., 2014) and forecasting
population dynamics of sea scallops, which are the basis of important commercial fisheries
(Cooley et al., 2015).
Detection of ocean acidification trends. A number of studies
estimate trends in surface ocean pH or the carbonate concentration by
combining SOCAT fCO2 values with another carbonate parameter (Lauvset
and Gruber, 2014; Freeman and Lovenduski, 2015; Lauvset et al., 2015).
Regional process studies of surface oceanfCO2.
Several authors investigate regional processes driving temporal or spatial
variation in surface ocean fCO2 and CO2 air–sea fluxes. Examples
are for the Subantarctic Indian Ocean (Lourantou and Metzl, 2011) and the
eastern equatorial Pacific Ocean (Walker Brown et al., 2015).
Quantification of coastal ocean carbon sinks and sources. SOCAT
data products are used for quantification of CO2 sources and sinks in
coastal seas. Such studies are regional or global in extent (Chen et al.,
2013; Signorini et al., 2013; Laruelle et al., 2014, 2015).
Quantification of the ocean carbon sink and its variation. An
important application of the SOCAT data collection is quantification of the
ocean carbon sink on seasonal to multi-year timescales with a mapping or
gap-filling method. Such studies may be regional or global in extent.
Studies tend to be either for the coastal seas (Signorini et al., 2013) or
for the open ocean (Rödenbeck et al., 2015). The studies interpolate
sparse pCO2 data from a SOCAT or LDEO synthesis product in time and
space by a gap-filling method. Approaches include statistical interpolation
(Rödenbeck et al., 2013; Goddijn-Murphy et al., 2015; S. D. Jones et al.,
2015), multiple linear regression (Schuster et al., 2013; Signorini et al.,
2013; Iida et al., 2015), neural network approaches (Landschützer et
al., 2013, 2014; Nakaoka et al., 2013; Sasse et al., 2013; Zeng et al.,
2014) and model-based regression and tuning (Valsala and Maksyutov, 2010;
Majkut et al., 2014b). Mapping methods may be specific to individual regions
(“biomes”) (Signorini et al., 2013; Landschützer et al., 2014) or may
apply to the full (global) domain (e.g. Rödenbeck et al., 2013; S. D. Jones et
al., 2015). Most of these approaches use additional parameters with good
data coverage during the gap-filling process, for example satellite-derived
sea surface temperature and chlorophyll a, as well as sea surface salinity
and mixed layer depth from reanalysis. Many mapping methods use a
time-dependent variable, such as time itself or the steadily increasing
atmospheric CO2 mole fraction, in order to be able to reproduce a
long-term increase in surface ocean pCO2.
The Surface Ocean pCO2 Mapping Intercomparison (http://www.bgc-jena.mpg.de/SOCOM/) compares the surface ocean pCO2
distribution and air–sea CO2 fluxes in 14 data-based mapping products,
10 of them using SOCAT (Rödenbeck et al., 2015). The methods vary in
their characteristics, making them suitable for different space and timescales. The SOCOM initiative aims to quantify uncertainties and to identify
common features in the gap-filling methods. The first SOCOM results
highlight considerable differences between mapping products, especially in
data-sparse regions (Rödenbeck et al., 2015).
The high-profile Global Carbon Budget uses ocean biogeochemical models for
estimating trends in the global ocean carbon sink (Le Quéré et al.,
2014, 2015a, b). Recent budgets also consider observation-based estimates of
the ocean carbon sink using the LDEO and SOCAT synthesis products (Park et
al., 2010; Landschützer et al., 2014, 2015; Rödenbeck et al., 2014).
The 2015 Global Carbon Budget assesses the uncertainty in the ocean carbon
sink by comparing model results to observation-based estimates (Le
Quéré et al., 2015b).
Quantification of the land carbon sink. Quantification of the ocean
carbon sink is critical to resolving the Global Carbon Budget and underpins
the estimate of the land carbon sink (Le Quéré et al., 2014, 2015a, b). In addition, quantification of ocean–atmosphere CO2 fluxes in
space and time provides priors for atmospheric inversion, thus improving
estimates of the land carbon sink (Rödenbeck et al., 2014; Van der Laan
et al., 2014; S. D. Jones et al., 2015).
Scientific findings obtained using the SOCAT data collection
This section provides an overview of scientific findings obtained using the
SOCAT data collection.
Model-to-data comparison. Schuster et al. (2013) carry out a
comparison of CO2 air–sea fluxes for the Atlantic Ocean from data-based
methods, ocean biogeochemical models, ocean inversion, and atmospheric
inversions. The seasonal cycle and year-to-year variation in the fluxes
differ between the various methods for most Atlantic regions.
Two studies subsample model pCO2 data to surface ocean pCO2
observations derived from SOCAT. The authors conclude that ocean
biogeochemical models on average underestimate the spatial and temporal
variation in regional and global surface ocean pCO2 by 10 to 40 %
(Séférian et al., 2014; Turi et al., 2014). This corroborates the
SOCOM finding that ocean biogeochemical models underestimate the
year-to-year and decadal variation in the global air–sea CO2 flux
(Rödenbeck et al., 2015). However, at least one model-to-data comparison
study concludes that the Community Earth System Model captures the annual to
30-year variability in the ocean carbon cycle at regional to global scales
(McKinley et al., 2016). Landschützer et al. (2015) demonstrate how
ocean carbon observations are delivering new insights into large and
globally significant decadal changes in the ocean carbon sink. The
variability in the ocean carbon sink in regions like the Southern Ocean is not apparent in modelled
estimates of ocean carbon uptake or from atmospheric inverse calculations (e.g. Lenton et al.,
2013).
Detection of ocean acidification trends. SOCAT-based research
indicates a decrease in global surface ocean pH at a rate of -0.0018 ± 0.0004 yr-1 for 1991 to 2011 with significant decreases in
70 % of all ocean regions (Lauvset et al., 2015).
Data-based carbon budgeting. Using SOCAT and other data sources,
Regnier et al. (2013) estimate that anthropogenic activities may have
increased open-ocean outgassing of land-derived carbon by 0.1 Pg C yr-1. The global CO2 sink in continental shelf seas has been
estimated as 0.4 Pg C yr-1 (Chen et al., 2013) and 0.19 ± 0.05 Pg C yr-1 (Laruelle et al., 2014).
Several mapping studies highlight large year-to-year variation in air–sea
CO2 fluxes in the tropical Pacific Ocean (Landschützer et al.,
2014; Rödenbeck et al., 2014, 2015). This variation is closely related
to the El Niño–Southern Oscillation (ENSO) (Feely et al., 1999, 2002;
Inoue et al., 2001; Rödenbeck et al., 2014). The variation in the
equatorial Pacific Ocean roughly corresponds to 40 % of the interannual
variation in the global ocean carbon sink (Rödenbeck et al., 2014),
which has been estimated as 0.31 Pg C yr-1 (Rödenbeck et al.,
2015).
The SOCOM comparison of mapping methods identifies an increase in global
ocean carbon sink by 1 Pg C decade-1 since 2000 (Rödenbeck et al.,
2015). About half of this increase in the global ocean carbon sink
originates south of 35∘ S in the Southern Ocean (Landschützer
et al., 2014, 2015).
Conclusions
SOCAT version 3 represents an important release of the SOCAT data
collection, by creating a 58-year data record and by adding many additional
data sets for recent years. The new data set flag of E in version 3 now
enables inclusion of calibrated surface ocean fCO2 measurements
from alternative sensors (with an accuracy of better than 10 µatm)
made on alternative platforms, such as moorings and drifters, in remote and
less remote ocean regions. This article provides an ESSD “living
data”
update of SOCAT version 3. The launch of the SOCAT automation system will
enable annual SOCAT releases from version 4 onwards.
The rapid growth of scientific publications using SOCAT (Fig. 7)
demonstrates the importance of this synthesis activity by the international
marine carbon community. The SOCAT data collection is being used in
high-impact, scientific applications such as evaluation of ocean
biogeochemical models, carbon budgeting, and trend analysis of the ocean
carbon sink and ocean acidification. SOCAT-based studies have informed the
Paris climate negotiations, as the 2015 Global Carbon Budget was released at
the 21st Conference of the Parties of the United Nations Framework
Convention on Climate Change (Le Quéré et al., 2015b).
However, despite much progress in data synthesis, major uncertainties remain
in observation-based studies of the ocean carbon sink and ocean
acidification due to (1) inadequate spatial and seasonal data coverage, (2) short data records, and (3) uncertainty in the correction for “natural”,
pre-industrial oceanic outgassing of land-derived CO2 (Jacobson et al.,
2007) and any anthropogenic perturbation of this outgassing (Regnier et al.,
2013). Data coverage is particularly poor in the Indian Ocean, the Southern
Hemisphere oceans and coastal seas and in the high-latitude oceans, notably
in ice-covered regions and in winter (Figs. 3, 4 and 6).
The above reinforces the need for the continuing collection and synthesis of
accurate, well-calibrated and well-documented observations and investment in
high-quality surface ocean CO2 measurements on autonomous platforms.
Adequate resources need to continue to be made available for data
collection, quality control and data synthesis. Systems should be automated
whenever possible. The SOCAT data synthesis highlights the success of a
bottom-up approach with buy-in from the international marine carbon
community and endorsement by IOCCP, SOLAS and IMBER.
Data availability
This manuscript describes how the synthesis product has been created
(Sect. 4) and how the individual data set files, synthesis files and gridded
products can be accessed (Sect. 5) (Table 8). Individual data set files, all
combined forming the synthesis product, can be downloaded here:
10.1594/PANGAEA.849770. Global and regional files are available as
compressed zip text files via CDIAC
(http://cdiac.ornl.gov/ftp/oceans/SOCATv3/). The global synthesis
product for data sets with flags of A to D is also available in Ocean Data
View format (https://odv.awi.de/en/data/ocean/socat_fCO2_data). The
gridded products are available here: 10.3334/CDIAC/OTG.SOCAT_V3_GRID.
Further details are in Sects. 4 and 5.
Acknowledgements
Research vessel Tiglax in Columbia Bay, Alaska, is shown on the
website for SOCAT version 3. The Columbia Glacier can be seen at the head of
the bay, as well as calved ice from the glacier. The photo was taken by Wiley
Evans. Pete Brown (National Oceanography Centre Southampton, UK) designed the
SOCAT logo. IOCCP (via a US National Science Foundation grant (OCE-124 3377)
to the Scientific Committee on Oceanic Research), IOC-UNESCO (International
Oceanographic Commission of the United Nations Educational, Scientific and
Cultural Organization), SOLAS and IMBER provided travel and meeting support.
Funding was received from the University of East Anglia (UK), the Bjerknes
Centre for Climate Research (Norway), the Geophysical Institute at the
University of Bergen (Norway) and the University of Washington (US). The US
National Oceanic and Atmospheric Administration (NOAA) made important
financial contributions via the Climate Observation Division of the Climate
Program Office, the NOAA Ocean Acidification Program, the NOAA Pacific Marine
Environmental Laboratory (PMEL), the NOAA Atlantic Oceanographic and
Meteorological Laboratory (AOML) and the NOAA Earth System Research
Laboratory. Funding was also received from Oak Ridge National Laboratory
(US), PANGAEA® Data Publisher for Earth and
Environmental Science (Germany), the Alfred Wegener Institute Helmholtz
Centre for Polar and Marine Research (Germany), the Antarctic Climate and
Ecosystems Cooperative Research Centre (Australia), the National Institute
for Environmental Studies (Japan) and Uni Research (Norway). Research
projects making SOCAT possible included the European Union projects
CarboChange (FP7 264879), GEOCARBON (FP7 283080) and AtlantOS (633211), the
UK Ocean Acidification Research Programme (NE/H017046/1; funded by the
Natural Environment Research Council (NERC) and the Departments for Energy
and Climate Change and for Environment, Food and Rural Affairs (Defra)) and
the UK Shelf Sea Biogeochemistry Blue Carbon project (NE/K00168X/1; funded by
NERC and Defra). Numerous government and funding agencies financially
supported SOCAT, notably the Australian International Marine Observing
System, the U.S. Geological Survey, the National Aeronautics and Space
Administration (NASA) (US), the European Space Agency, the German Federal
Ministry of Education and Research (BMBF projects 01LK1224J, 01LK1101C,
01LK1101E, ICOS-D), the Japanese Ministry of the Environment, the Royal
Society of New Zealand via the New Zealand–Germany Science and Technology
Programme, the Norwegian Research Council (SNACS, 229752), the Swedish
Research Council (project 2004-4034) and the Swedish Research Council for
Environment, Agricultural Sciences and Spatial Planning (Formas, project
2004-797). This is PMEL contribution number 4441. Finally, we thank the two
anonymous reviewers for their thoughtful, constructive and insightful
reviews.Edited by: F. Schmitt
Reviewed by: two anonymous referees
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