Articles | Volume 15, issue 2
https://doi.org/10.5194/essd-15-921-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-15-921-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
27 Feb 2023
Data description paper |
| 27 Feb 2023
| 27 Feb 2023
OceanSODA-MDB: a standardised surface ocean carbonate system dataset for model–data intercomparisons
Plymouth Marine Laboratory, Prospect Place, West Hoe, Plymouth, PL1
3DH, UK
Helen S. Findlay
Plymouth Marine Laboratory, Prospect Place, West Hoe, Plymouth, PL1
3DH, UK
Jamie D. Shutler
Centre for Geography and Environmental Science, University of Exeter,
Penryn, Cornwall, TR10 9FE, UK
Jean-Francois Piolle
IFREMER, Brest, France
Richard Sims
Centre for Geography and Environmental Science, University of Exeter,
Penryn, Cornwall, TR10 9FE, UK
Hannah Green
Centre for Geography and Environmental Science, University of Exeter,
Penryn, Cornwall, TR10 9FE, UK
Plymouth Marine Laboratory, Prospect Place, West Hoe, Plymouth, PL1
3DH, UK
Vassilis Kitidis
Plymouth Marine Laboratory, Prospect Place, West Hoe, Plymouth, PL1
3DH, UK
Alexander Polukhin
Shirshov Institute of Oceanology, 36, Nakhimovskiy prospect, Moscow,
117997, Russia
Irina I. Pipko
V.I. Il'ichev Pacific Oceanological Institute FEB RAS, Vladivostok,
690041, Russia
Related authors
Catarina V. Guerreiro, Bror F. Jonsson, Peter Land, Javier Arístegui, Jan-Berend Stuut, Afonso Ferreira, Gavin H. Tilstone, Vanda Brotas, and Steve B. Groom
EGUsphere, https://doi.org/10.5194/egusphere-2025-5789, https://doi.org/10.5194/egusphere-2025-5789, 2025
This preprint is open for discussion and under review for Biogeosciences (BG).
Short summary
Short summary
This study examines how winds, ocean currents, and Saharan dust affect the movement of carbon-rich material from surface waters to the deep ocean off Northwest Africa. By tracing surface seawater pathways and quantifying sinking particles throughout the year, the work shows that winter-spring upwelling drive this transfer, while summer dust helps carry organic matter downward. These findings can be used to improve forecasts of how the ocean will store carbon in the future.
Richard P. Sims, Thomas M. Holding, Peter E. Land, Jean-Francois Piolle, Hannah L. Green, and Jamie D. Shutler
Earth Syst. Sci. Data, 15, 2499–2516, https://doi.org/10.5194/essd-15-2499-2023, https://doi.org/10.5194/essd-15-2499-2023, 2023
Short summary
Short summary
The flow of carbon between the land and ocean is poorly quantified with existing measurements. It is not clear how seasonality and long-term variability impact this flow of carbon. Here, we demonstrate how satellite observations can be used to create decadal time series of the inorganic carbonate system in the Amazon and Congo River outflows.
Catarina V. Guerreiro, Bror F. Jonsson, Peter Land, Javier Arístegui, Jan-Berend Stuut, Afonso Ferreira, Gavin H. Tilstone, Vanda Brotas, and Steve B. Groom
EGUsphere, https://doi.org/10.5194/egusphere-2025-5789, https://doi.org/10.5194/egusphere-2025-5789, 2025
This preprint is open for discussion and under review for Biogeosciences (BG).
Short summary
Short summary
This study examines how winds, ocean currents, and Saharan dust affect the movement of carbon-rich material from surface waters to the deep ocean off Northwest Africa. By tracing surface seawater pathways and quantifying sinking particles throughout the year, the work shows that winter-spring upwelling drive this transfer, while summer dust helps carry organic matter downward. These findings can be used to improve forecasts of how the ocean will store carbon in the future.
Daniel J. Ford, Jamie D. Shutler, Katy L. Sheen, Gavin H. Tilstone, and Vassilis Kitidis
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-463, https://doi.org/10.5194/essd-2025-463, 2025
Preprint under review for ESSD
Short summary
Short summary
Mesoscale eddies are abundant in the global oceans affect the physical, chemical and biological properties of the ocean. These changes can modify the air-sea CO2 fluxes. Here, we present a dataset of air-sea CO2 fluxes for 5996 long lived mesoscale eddies trajectories in the global ocean between 1993 to 2022. These trajectories can be used to understand the processes modifying and controlling the air-sea CO2 fluxes in mesoscale eddies which are supported by a comprehensive uncertainty budget.
Daniel J. Ford, Gemma Kulk, Shubha Sathyendranath, and Jamie D. Shutler
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-389, https://doi.org/10.5194/essd-2025-389, 2025
Revised manuscript under review for ESSD
Short summary
Short summary
Chlorophyll-a is routinely monitored using ocean colour satellites, however, these data records have gaps. Here we present a methodology to provide a spatially and temporally complete chlorophyll-a record, using Biogeochemical Argo floats as a constraint on wintertime chlorophyll-a, and a statistical kriging approach to fill cloud gaps. Thereby, providing a complete record at monthly 0.25° resolution between 1997 and 2023, consistent to the underlying climate data record.
Andrea J. McEvoy, Angus Atkinson, Ruth L. Airs, Rachel Brittain, Ian Brown, Elaine S. Fileman, Helen S. Findlay, Caroline L. McNeill, Clare Ostle, Tim J. Smyth, Paul J. Somerfield, Karen Tait, Glen A. Tarran, Simon Thomas, Claire E. Widdicombe, E. Malcolm S. Woodward, Amanda Beesley, David V. P. Conway, James Fishwick, Hannah Haines, Carolyn Harris, Roger Harris, Pierre Hélaouët, David Johns, Penelope K. Lindeque, Thomas Mesher, Abigail McQuatters-Gollop, Joana Nunes, Frances Perry, Ana M. Queiros, Andrew Rees, Saskia Rühl, David Sims, Ricardo Torres, and Stephen Widdicombe
Earth Syst. Sci. Data, 15, 5701–5737, https://doi.org/10.5194/essd-15-5701-2023, https://doi.org/10.5194/essd-15-5701-2023, 2023
Short summary
Short summary
Western Channel Observatory is an oceanographic time series and biodiversity reference site within 40 km of Plymouth (UK), sampled since 1903. Differing levels of reporting and formatting hamper the use of the valuable individual datasets. We provide the first summary database as monthly averages where comparisons can be made of the physical, chemical and biological data. We describe the database, illustrate its utility to examine seasonality and longer-term trends, and summarize previous work.
Richard P. Sims, Thomas M. Holding, Peter E. Land, Jean-Francois Piolle, Hannah L. Green, and Jamie D. Shutler
Earth Syst. Sci. Data, 15, 2499–2516, https://doi.org/10.5194/essd-15-2499-2023, https://doi.org/10.5194/essd-15-2499-2023, 2023
Short summary
Short summary
The flow of carbon between the land and ocean is poorly quantified with existing measurements. It is not clear how seasonality and long-term variability impact this flow of carbon. Here, we demonstrate how satellite observations can be used to create decadal time series of the inorganic carbonate system in the Amazon and Congo River outflows.
Richard P. Sims, Mohamed M. M. Ahmed, Brian J. Butterworth, Patrick J. Duke, Stephen F. Gonski, Samantha F. Jones, Kristina A. Brown, Christopher J. Mundy, William J. Williams, and Brent G. T. Else
Ocean Sci., 19, 837–856, https://doi.org/10.5194/os-19-837-2023, https://doi.org/10.5194/os-19-837-2023, 2023
Short summary
Short summary
Using a small research vessel based out of Cambridge Bay in the Kitikmeot Sea (Canadian Arctic Archipelago), we were able to make measurements of surface ocean pCO2 shortly after sea ice breakup for 4 consecutive years. We compare our measurements to previous underway measurements and the two ongoing ocean carbon observatories in the region. We identify high interannual variability and a potential bias in previous estimates due to lower pCO2 in bays and inlets.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Luke Gregor, Judith Hauck, Corinne Le Quéré, Ingrid T. Luijkx, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Ramdane Alkama, Almut Arneth, Vivek K. Arora, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Henry C. Bittig, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Wiley Evans, Stefanie Falk, Richard A. Feely, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Lucas Gloege, Giacomo Grassi, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Atul K. Jain, Annika Jersild, Koji Kadono, Etsushi Kato, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Peter Landschützer, Nathalie Lefèvre, Keith Lindsay, Junjie Liu, Zhu Liu, Gregg Marland, Nicolas Mayot, Matthew J. McGrath, Nicolas Metzl, Natalie M. Monacci, David R. Munro, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin O'Brien, Tsuneo Ono, Paul I. Palmer, Naiqing Pan, Denis Pierrot, Katie Pocock, Benjamin Poulter, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Carmen Rodriguez, Thais M. Rosan, Jörg Schwinger, Roland Séférian, Jamie D. Shutler, Ingunn Skjelvan, Tobias Steinhoff, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Shintaro Takao, Toste Tanhua, Pieter P. Tans, Xiangjun Tian, Hanqin Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Guido R. van der Werf, Anthony P. Walker, Rik Wanninkhof, Chris Whitehead, Anna Willstrand Wranne, Rebecca Wright, Wenping Yuan, Chao Yue, Xu Yue, Sönke Zaehle, Jiye Zeng, and Bo Zheng
Earth Syst. Sci. Data, 14, 4811–4900, https://doi.org/10.5194/essd-14-4811-2022, https://doi.org/10.5194/essd-14-4811-2022, 2022
Short summary
Short summary
The Global Carbon Budget 2022 describes the datasets and methodology used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, the land ecosystems, and the ocean. These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Brent G. T. Else, Araleigh Cranch, Richard P. Sims, Samantha Jones, Laura A. Dalman, Christopher J. Mundy, Rebecca A. Segal, Randall K. Scharien, and Tania Guha
The Cryosphere, 16, 3685–3701, https://doi.org/10.5194/tc-16-3685-2022, https://doi.org/10.5194/tc-16-3685-2022, 2022
Short summary
Short summary
Sea ice helps control how much carbon dioxide polar oceans absorb. We compared ice cores from two sites to look for differences in carbon chemistry: one site had thin ice due to strong ocean currents and thick snow; the other site had thick ice, thin snow, and weak currents. We did find some differences in small layers near the top and the bottom of the cores, but for most of the ice volume the chemistry was the same. This result will help build better models of the carbon sink in polar oceans.
Daniel J. Ford, Gavin H. Tilstone, Jamie D. Shutler, and Vassilis Kitidis
Biogeosciences, 19, 4287–4304, https://doi.org/10.5194/bg-19-4287-2022, https://doi.org/10.5194/bg-19-4287-2022, 2022
Short summary
Short summary
This study explores the seasonal, inter-annual, and multi-year drivers of the South Atlantic air–sea CO2 flux. Our analysis showed seasonal sea surface temperatures dominate in the subtropics, and the subpolar regions correlated with biological processes. Inter-annually, the El Niño–Southern Oscillation correlated with the CO2 flux by modifying sea surface temperatures and biological activity. Long-term trends indicated an important biological contribution to changes in the air–sea CO2 flux.
Richard P. Sims, Michael Bedington, Ute Schuster, Andrew J. Watson, Vassilis Kitidis, Ricardo Torres, Helen S. Findlay, James R. Fishwick, Ian Brown, and Thomas G. Bell
Biogeosciences, 19, 1657–1674, https://doi.org/10.5194/bg-19-1657-2022, https://doi.org/10.5194/bg-19-1657-2022, 2022
Short summary
Short summary
The amount of carbon dioxide (CO2) being absorbed by the ocean is relevant to the earth's climate. CO2 values in the coastal ocean and estuaries are not well known because of the instrumentation used. We used a new approach to measure CO2 across the coastal and estuarine zone. We found that CO2 and salinity were linked to the state of the tide. We used our CO2 measurements and model salinity to predict CO2. Previous studies overestimate how much CO2 the coastal ocean draws down at our site.
Daniel J. Ford, Gavin H. Tilstone, Jamie D. Shutler, and Vassilis Kitidis
Biogeosciences, 19, 93–115, https://doi.org/10.5194/bg-19-93-2022, https://doi.org/10.5194/bg-19-93-2022, 2022
Short summary
Short summary
This study identifies the most accurate biological proxy for the estimation of seawater pCO2 fields, which are key to assessing the ocean carbon sink. Our analysis shows that the net community production (NCP), the balance between photosynthesis and respiration, was more accurate than chlorophyll a within a neural network scheme. The improved pCO2 estimates, based on NCP, identified the South Atlantic Ocean as a net CO2 source, compared to a CO2 sink using chlorophyll a.
Zixia Liu, Martin Osborne, Karen Anderson, Jamie D. Shutler, Andy Wilson, Justin Langridge, Steve H. L. Yim, Hugh Coe, Suresh Babu, Sreedharan K. Satheesh, Paquita Zuidema, Tao Huang, Jack C. H. Cheng, and James Haywood
Atmos. Meas. Tech., 14, 6101–6118, https://doi.org/10.5194/amt-14-6101-2021, https://doi.org/10.5194/amt-14-6101-2021, 2021
Short summary
Short summary
This paper first validates the performance of an advanced aerosol observation instrument POPS against a reference instrument and examines any biases introduced by operating it on a quadcopter drone. The results show the POPS performs relatively well on the ground. The impact of the UAV rotors on the POPS is small at low wind speeds, but when operating under higher wind speeds, larger discrepancies occur. It appears that the POPS measures sub-micron aerosol particles more accurately on the UAV.
Yuanxu Dong, Mingxi Yang, Dorothee C. E. Bakker, Vassilis Kitidis, and Thomas G. Bell
Atmos. Chem. Phys., 21, 8089–8110, https://doi.org/10.5194/acp-21-8089-2021, https://doi.org/10.5194/acp-21-8089-2021, 2021
Short summary
Short summary
Eddy covariance (EC) is the most direct method for measuring air–sea CO2 flux from ships. However, uncertainty in EC air–sea CO2 fluxes has not been well quantified. Here we show that with the state-of-the-art gas analysers, instrumental noise no longer contributes significantly to the CO2 flux uncertainty. Applying an appropriate averaging timescale (1–3 h) and suitable air–sea CO2 fugacity threshold (at least 20 µatm) to EC flux data enables an optimal analysis of the gas transfer velocity.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Judith Hauck, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Corinne Le Quéré, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone Alin, Luiz E. O. C. Aragão, Almut Arneth, Vivek Arora, Nicholas R. Bates, Meike Becker, Alice Benoit-Cattin, Henry C. Bittig, Laurent Bopp, Selma Bultan, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Wiley Evans, Liesbeth Florentie, Piers M. Forster, Thomas Gasser, Marion Gehlen, Dennis Gilfillan, Thanos Gkritzalis, Luke Gregor, Nicolas Gruber, Ian Harris, Kerstin Hartung, Vanessa Haverd, Richard A. Houghton, Tatiana Ilyina, Atul K. Jain, Emilie Joetzjer, Koji Kadono, Etsushi Kato, Vassilis Kitidis, Jan Ivar Korsbakken, Peter Landschützer, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Zhu Liu, Danica Lombardozzi, Gregg Marland, Nicolas Metzl, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin O'Brien, Tsuneo Ono, Paul I. Palmer, Denis Pierrot, Benjamin Poulter, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Adam J. P. Smith, Adrienne J. Sutton, Toste Tanhua, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Guido van der Werf, Nicolas Vuichard, Anthony P. Walker, Rik Wanninkhof, Andrew J. Watson, David Willis, Andrew J. Wiltshire, Wenping Yuan, Xu Yue, and Sönke Zaehle
Earth Syst. Sci. Data, 12, 3269–3340, https://doi.org/10.5194/essd-12-3269-2020, https://doi.org/10.5194/essd-12-3269-2020, 2020
Short summary
Short summary
The Global Carbon Budget 2020 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Cited articles
AMAP: AMAP Assessment 2018: Arctic Ocean Acidification, viii + 99 pp-viii
+ 99 pp., https://doi.org/10.1016/j.techfore.2013.08.036, 2018.
Argo: Argo float data and metadata from Global Data Assembly Centre (Argo GDAC), SEANOE, https://doi.org/10.17882/42182, [data set], last access: 7 January 2021.
Bakker, D. C. E., Pfeil, B., Landa, C. S., Metzl, N., O'Brien, K. M., Olsen, A., Smith, K., Cosca, C., Harasawa, S., Jones, S. D., Nakaoka, S., Nojiri, Y., Schuster, U., Steinhoff, T., Sweeney, C., Takahashi, T., Tilbrook, B., Wada, C., Wanninkhof, R., Alin, S. R., Balestrini, C. F., Barbero, L., Bates, N. R., Bianchi, A. A., Bonou, F., Boutin, J., Bozec, Y., Burger, E. F., Cai, W.-J., Castle, R. D., Chen, L., Chierici, M., Currie, K., Evans, W., Featherstone, C., Feely, R. A., Fransson, A., Goyet, C., Greenwood, N., Gregor, L., Hankin, S., Hardman-Mountford, N. J., Harlay, J., Hauck, J., Hoppema, M., Humphreys, M. P., Hunt, C. W., Huss, B., Ibánhez, J. S. P., Johannessen, T., Keeling, R., Kitidis, V., Körtzinger, A., Kozyr, A., Krasakopoulou, E., Kuwata, A., Landschützer, P., Lauvset, S. K., Lefèvre, N., Lo Monaco, C., Manke, A., Mathis, J. T., Merlivat, L., Millero, F. J., Monteiro, P. M. S., Munro, D. R., Murata, A., Newberger, T., Omar, A. M., Ono, T., Paterson, K., Pearce, D., Pierrot, D., Robbins, L. L., Saito, S., Salisbury, J., Schlitzer, R., Schneider, B., Schweitzer, R., Sieger, R., Skjelvan, I., Sullivan, K. F., Sutherland, S. C., Sutton, A. J., Tadokoro, K., Telszewski, M., Tuma, M., van Heuven, S. M. A. C., Vandemark, D., Ward, B., Watson, A. J., and Xu, S.: A multi-decade record of high-quality fCO2 data in version 3 of the Surface Ocean CO2 Atlas (SOCAT), Earth Syst. Sci. Data, 8, 383–413, https://doi.org/10.5194/essd-8-383-2016, 2016.
Banzon, V., Smith, T. M., Chin, T. M., Liu, C., and Hankins, W.: A long-term record of blended satellite and in situ sea-surface temperature for climate monitoring, modeling and environmental studies, Earth Syst. Sci. Data, 8, 165–176, https://doi.org/10.5194/essd-8-165-2016, 2016.
Bates, N. R., Astor, Y. M., Church, M. J., Currie, K., Dore, J. E.,
González-Dávila, M., Lorenzoni, L., Muller-Karger, F., Olafsson, J.,
and Santana-Casiano, J. M.: A time-series view of changing surface ocean
chemistry due to ocean uptake of anthropogenic CO2 and ocean acidification,
Oceanography, 27, 126–141, https://doi.org/10.5670/oceanog.2014.16, 2014.
BEC: BEC Arctic v3 SSS Product Description V1.0, Barcelona Expert Center, https://doi.org/10.20350/digitalCSIC/12620, 2021.
Boutin, J., Vergely, J., Reul, N., Catany, R., Koehler, J., Martin, A.,
Rouffi, F., Arias, M., Chakroun, M., Corato, G., Estella-Perez, V.,
Guimbard, S., Hasson, A., Josey, S., Khvorostyanov, D., Kolodziejczyk, N.,
Mignot, J., Olivier, L., Reverdin, G., Stammer, D., Supply, A.,
Thouvenin-Masson, C., Turiel, A., Vialard, J., Cipollini, P., and Donlon,
C.: ESA Sea Surface Salinity Climate Change Initiative (Sea_Surface_Salinity_cci): weekly and monthly sea
surface salinity products, v2. 31, for 2010 to 2019, Centre for
Environmental Data Analysis [data set], https://doi.org/10.5285/5920a2c77e3c45339477acd31ce62c3c, 2020.
Boutin, J., Reul, N., Köhler, J., Martin, A., Catany, R., Guimbard, S.,
Rouffi, F., Vergely, J.-L., Arias, M., and Chakroun, M.: Satellite-Based Sea
Surface Salinity Designed for Ocean and Climate Studies, J.
Geophys. Res.-Oceans, 126, e2021JC017676, https://doi.org/10.1029/2021JC017676, 2021.
Boyer, T. P., Garcia, H. E., Locarnini, R. A., Zweng, M. M., Mishonov, A. V., Reagan, J. R., Weathers, K. A., Baranova, O. K., Seidov, D., and Smolyar, I. V.: World Ocean Atlas 2018. NOAA National Centers for Environmental Information [data set], https://www.ncei.noaa.gov/archive/accession/NCEI-WOA18 (last access: 20 February 2023), 2018.
Bruevich, S. V.: Determination of alkalinity in small volumes of seawater by
direct titration, Instruction of Chemical Examination of Seawater, p. 83, 1944.
Chau, T. T., Gehlen, M., and Chevallier, F.: Global Ocean Surface Carbon
Product MULTIOBS_GLO_BIO_CARBON_SURFACE_REP_015_008, EU Copernicus Marine Service Information [data set], https://doi.org/10.48670/moi-00047, 2020.
Claustre, H., Johnson, K. S., and Takeshita, Y.: Observing the Global Ocean
with Biogeochemical-Argo, Annu. Rev. Marine Sci., 12, 23-48, https://doi.org/10.1146/annurev-marine-010419-010956, 2020.
Clayton, T. D. and Byrne, R. H.: Spectrophotometric seawater pH
measurements: total hydrogen ion concentration scale calibration of m-cresol
purple and at-sea results, Deep-Sea Res. Pt. I, 40, 2115–2129, https://doi.org/10.1016/0967-0637(93)90048-8, 1993.
Cross, J., Mathis, J. T., Monacci, N., Mordy, C., Stabeno, P. J., and
Sullivan, M. E.: Dissolved inorganic carbon (DIC), total alkalinity and
other hydrographic and chemical variables collected from discrete samples
and profile observations during the R/V Knorr cruise KN195 (EXPOCODE
316N20090614) in Bering Sea from 2009-06-14 to 2009-07-30, NOAA National
Centers for Environmental Information [data set], https://doi.org/10.25921/sqkj-f093, 2019.
Cross, J., Monacci, N., Bell, S. W., Grebmeier, J. M., Mordy, C., Pickart,
R. S., and Stabeno, P. J.: Dissolved inorganic carbon (DIC), total
alkalinity (TA) and other variables collected from discrete samples and
profile observations from United States Coast Guard Cutter (USCGC) Healy
cruise HLY1702 (EXPOCODE 33HQ20170826) in the Bering and Chukchi Sea along
transect lines in the Distributed Biological Observatory (DBO) from
2017-08-26 to 2017-09-15 (NCEI Accession 0208337), NOAA National Centers for
Environmental Information [data set], https://doi.org/10.25921/pks4-4p43, 2020.
Denvil-Sommer, A., Gehlen, M., Vrac, M., and Mejia, C.: LSCE-FFNN-v1: a two-step neural network model for the reconstruction of surface ocean pCO2 over the global ocean, Geosci. Model Dev., 12, 2091–2105, https://doi.org/10.5194/gmd-12-2091-2019, 2019.
Dickson, A. G.: Thermodynamics of the dissociation of boric acid in
synthetic seawater from 273.15 to 318.15 K, Deep-Sea Res. Pt. A, 37, 755–766, 1990.
Dickson, A. G. and Goyet, C.: Handbook of methods for the analysis of the
various parameters of the carbon dioxide system in sea water, Version 2, Oak
Ridge National Lab., TN, United States, 1994.
Dickson, A. G., Afghan, J. D., and Anderson, G. C.: Reference materials for
oceanic CO2 analysis: a method for the certification of total alkalinity,
Marine Chem., 80, 185–197, 2003.
Dickson, A. G., Sabine, C. L., and Christian, J. R.: Guide to best practices
for ocean CO2 measurements, PICES Special Publication 3, North Pacific Marine
Science Organization, https://www.nodc.noaa.gov/ocads/oceans/Handbook_2007.html (last access: 20 February 2023), 2007.
Doney, S. C., Busch, D. S., Cooley, S. R., and Kroeker, K. J.: The impacts
of ocean acidification on marine ecosystems and reliant human communities,
Annu. Rev. Environ. Resour., 45, 83–112, https://doi.org/10.1146/annurev-environ-012320-083019, 2020.
Edmond, J. M.: High precision determination of titration alkalinity and
total carbon dioxide content of sea water by potentiometric titration, Deep Sea Research and Oceanographic Abstracts, 17,
737–750, 1970.
Gaillard, F., Reynaud, T., Thierry, V., Kolodziejczyk, N., and von
Schuckman, K.: ISAS-13 re-analysis: Climatology and inter-annual variability
deduced from Global Ocean Observing Systems, J. Climate, 29,
1305–1323, 2016.
Garcia, H. E., Weathers, K. W., Paver, C. R., Smolyar, I., Boyer, T. P.,
Locarnini, M., Zweng, M. M., Mishonov, A. V., Baranova, O. K., and Seidov,
D.: World Ocean Atlas 2018, Volume 3: Dissolved Oxygen, Apparent Oxygen
Utilization, and Dissolved Oxygen Saturation, NOAA Atlas NESDIS 83 [data set], 38 pp., https://archimer.ifremer.fr/doc/00651/76337/ (last access: 20 February 2023), 2019a.
Garcia, H. E., Weathers, K. W., Paver, C. R., Smolyar, I., Boyer, T. P.,
Locarnini, M. M., Zweng, M. M., Mishonov, A. V., Baranova, O. K., and
Seidov, D.: World Ocean Atlas 2018. Vol. 4: Dissolved Inorganic Nutrients
(phosphate, nitrate and nitrate+ nitrite, silicate), NOAA Atlas NESDIS 84 [data set], 35 pp., https://archimer.ifremer.fr/doc/00651/76336/ (last access: 20 February 2023), 2019b.
Gattuso, J. P., Magnan, A., Billé, R., Cheung, W. W. L., Howes, E. L.,
Joos, F., Allemand, D., Bopp, L., Cooley, S. R., Eakin, C. M.,
Hoegh-Guldberg, O., Kelly, R. P., Pörtner, H. O., Rogers, A. D., Baxter,
J. M., Laffoley, D., Osborn, D., Rankovic, A., Rochette, J., Sumaila, U. R.,
Treyer, S., and Turley, C.: Contrasting futures for ocean and society from
different anthropogenic CO2 emissions scenarios, Science, 349, 6243, https://doi.org/10.1126/science.aac4722, 2015.
Gattuso, J., Epitalon, J., Lavigne, H., and Orr, J.: seacarb: Seawater
Carbonate Chemistry, R package version 3.2.12,
https://CRAN.R-project.org/package=seacarb (last access: 20 February 2023), 2021.
Good, S. A., Embury, O., Bulgin, C. E., and Mittaz, J.: ESA Sea Surface
Temperature Climate Change Initiative (SST_cci): Level 4
Analysis Climate Data Record, version 2.1, Centre for Environmental Data Analysis [data set], https://doi.org/10.5285/62c0f97b1eac4e0197a674870afe1ee6, 2019.
Gregor, L. and Gruber, N.: OceanSODA-ETHZ: A global gridded data set of the
surface ocean carbonate system for seasonal to decadal studies of ocean
acidification (v2021) (NCEI Accession 0220059), Version 2.2, , NOAA National Centers for Environmental Information [data set], https://doi.org/10.25921/m5wx-ja34, 2020.
Gregor, L. and Gruber, N.: OceanSODA-ETHZ: a global gridded data set of the surface ocean carbonate system for seasonal to decadal studies of ocean acidification, Earth Syst. Sci. Data, 13, 777–808, https://doi.org/10.5194/essd-13-777-2021, 2021.
Huang, B., Liu, C., Banzon, V., Freeman, E., Graham, G., Hankins, B., Smith,
T., and Zhang, H.-M.: Improvements of the Daily Optimum Interpolation Sea
Surface Temperature (DOISST) Version 2.1, J. Climate, 34, 2923–2939, https://doi.org/10.1175/JCLI-D-20-0166.1, 2021.
Jiang, L.-Q., Feely, R. A., Wanninkhof, R., Greeley, D., Barbero, L., Alin, S., Carter, B. R., Pierrot, D., Featherstone, C., Hooper, J., Melrose, C., Monacci, N., Sharp, J. D., Shellito, S., Xu, Y.-Y., Kozyr, A., Byrne, R. H., Cai, W.-J., Cross, J., Johnson, G. C., Hales, B., Langdon, C., Mathis, J., Salisbury, J., and Townsend, D. W.: Coastal Ocean Data Analysis Product in North America (CODAP-NA) – an internally consistent data product for discrete inorganic carbon, oxygen, and nutrients on the North American ocean margins, Earth Syst. Sci. Data, 13, 2777–2799, https://doi.org/10.5194/essd-13-2777-2021, 2021.
Key, R. M., Olsen, A., van Heuven, S., Lauvset, S. K., Velo, A., Lin, X.,
Schirnick, C., Kozyr, A., Tanhua, T., and Hoppema, M.: Global ocean data
analysis project, version 2 (GLODAPv2), Ornl/Cdiac-162, Ndp-093, Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, US Department of Energy, Oak Ridge, Tennessee, https://doi.org/10.3334/CDIAC/OTG.NDP093_GLODAPv2, 2015.
Kitidis, V., Brown, I., Hardman-Mountford, N., and Lefèvre, N.: Surface
ocean carbon dioxide during the Atlantic Meridional Transect (1995–2013);
evidence of ocean acidification, Prog. Oceanogr., 158, 65–75, 2017.
Kolodziejczyk, N., Prigent-Mazella, A., and Gaillard, F.: ISAS temperature
and salinity gridded fields, SEANOE [data set], https://doi.org/10.17882/52367, 2021.
Kroeker, K. J., Kordas, R. L., Crim, R., Hendriks, I. E., Ramajo, L., Singh,
G. S., Duarte, C. M., and Gattuso, J. P.: Impacts of ocean acidification on
marine organisms: quantifying sensitivities and interaction with warming,
Glob. Chang. Biol., 19, 1884–1896, https://doi.org/10.1111/gcb.12179, 2013.
Land, P. E. and Piollé, J.: OceanSODA standardised surface ocean
carbonate system matchup dataset (3.4), IFREMER, France [data set], https://doi.org/10.12770/0dc16d62-05f6-4bbe-9dc4-6d47825a5931, 2022.
Landschützer, P., Gruber, N., and Bakker, D. C. E.: Decadal variations
and trends of the global ocean carbon sink, Global Biogeochem. Cycles,
30, 1396–1417, https://doi.org/10.1002/2015GB005359, 2016.
Lauvset, S., Currie, K., Metzl, N., Nakaoka, S.-i., Bakker, D., Sullivan,
K., Sutton, A., O'Brien, K., and Olsen, A.: SOCAT Quality Control Cookbook:
for SOCAT version 7,
https://www.socat.info/wp-content/uploads/2020/12/2018_SOCAT_QC_Cookbook_final_with-v2021-contact-details.pdf (last access: 20 February 2023), 2018.
Lauvset, S. K., Lange, N., Tanhua, T., Bittig, H. C., Olsen, A., Kozyr, A., Álvarez, M., Becker, S., Brown, P. J., Carter, B. R., Cotrim da Cunha, L., Feely, R. A., van Heuven, S., Hoppema, M., Ishii, M., Jeansson, E., Jutterström, S., Jones, S. D., Karlsen, M. K., Lo Monaco, C., Michaelis, P., Murata, A., Pérez, F. F., Pfeil, B., Schirnick, C., Steinfeldt, R., Suzuki, T., Tilbrook, B., Velo, A., Wanninkhof, R., Woosley, R. J., and Key, R. M.: An updated version of the global interior ocean biogeochemical data product, GLODAPv2.2021, Earth Syst. Sci. Data, 13, 5565–5589, https://doi.org/10.5194/essd-13-5565-2021, 2021.
Locarnini, M., Mishonov, A. V., Baranova, O. K., Boyer, T. P., Zweng, M. M.,
Garcia, H. E., Seidov, D., Weathers, K., Paver, C., and Smolyar, I.: World
ocean atlas 2018, volume 1: Temperature, NOAA Atlas NESDIS 81 [data set], 52 pp., https://archimer.ifremer.fr/doc/00651/76338/ (last access: 20 February 2023), 2018.
Martínez, J., Gabarró, C., and Turiel, A.: Arctic Sea Surface
Salinity L2 orbits and L3 maps (V. 3.1), DIGITAL.CSIC [data set], https://doi.org/10.20350/digitalCSIC/12620, 2020a.
Martínez, J., Gabarró, C., Turiel, A., and Catany, R.: Arctic+
Salinity: Algorithm Theoretical Baseline Document, European Space Agency, https://doi.org/10.13140/RG.2.2.12195.58401, 2020b.
Mathis, J. T., Liu, X., Byrne, R. H., and Monacci, N.: Total alkalinity, pH
on total scale, water temperature, salinity and dissolved oxygen
concentration collected from discrete sample and profile observations during
the United States Coast Guard Cutter (USCGC) Healy cruise HLY1103 (EXPOCODE
33HQ20111003) in the Arctic Ocean, Beaufort Sea and Northwestern Passages
from 2011-10-03 to 2011-10-27 (NCEI Accession 0157310), NOAA National
Centers for Environmental Information [data set], https://doi.org/10.3334/cdiac/otg.clivar_33hq20111003, 2016a.
Mathis, J. T., Stabeno, P. J., Bates, N. R., and Mordy, C.: Dissolved
inorganic carbon (DIC), total alkalinity and other hydrographic and chemical
variables collected from discrete samples and profile observations during
the USCGC Healy HLY0802; BEST '08 Spring cruise (EXPOCODE 33HQ20080329) in
the Bering Sea from 2008-03-29 to 2008-05-06 (NCEI Accession 0144549), NOAA
National Centers for Environmental Information [data set], https://doi.org/10.3334/cdiac/otg.best08spr_33hq20080329, 2016b.
Mathis, J. T., Stabeno, P. J., Bates, N. R., and Mordy, C.: Dissolved
inorganic carbon (DIC), total alkalinity and other hydrographic and chemical
variables collected from discrete samples and profile observations during
the USCGC Healy HLY0803; BEST '08 Summer cruise (EXPOCODE 33HQ20080703) in
the Bering Sea from 2008-07-03 to 2008-07-31 (NCEI Accession 0144981), NOAA
National Centers for Environmental Information [data set], https://doi.org/10.25921/px3e-rb18, 2016c.
Meissner, T. and Wentz, F. J.: Remote Sensing Systems SMAP Ocean Surface
Salinities, Version 4.0 validated release, Remote Sensing Systems, Santa
Rosa, CA, USA, 2019.
Merchant, C. J., Embury, O., Bulgin, C. E., Block, T., Corlett, G. K.,
Fiedler, E., Good, S. A., Mittaz, J., Rayner, N. A., and Berry, D.:
Satellite-based time-series of sea-surface temperature since 1981 for
climate applications, Sci. Data, 6, 1–18, 2019.
Mol, J., Thomas, H., Myers, P. G., Hu, X., and Mucci, A.: Inorganic carbon fluxes on the Mackenzie Shelf of the Beaufort Sea, Biogeosciences, 15, 1011–1027, https://doi.org/10.5194/bg-15-1011-2018, 2018.
Olmedo, E., Gabarró, C., González-Gambau, V., Martínez, J.,
Ballabrera-Poy, J., Turiel, A., Portabella, M., Fournier, S., and Lee, T.:
Seven years of SMOS sea surface salinity at high latitudes: Variability in
Arctic and Sub-Arctic regions, Remote Sensing, 10, 1772, https://doi.org/10.3390/rs10111772, 2018.
Olsen, A., Key, R. M., van Heuven, S., Lauvset, S. K., Velo, A., Lin, X., Schirnick, C., Kozyr, A., Tanhua, T., Hoppema, M., Jutterström, S., Steinfeldt, R., Jeansson, E., Ishii, M., Pérez, F. F., and Suzuki, T.: The Global Ocean Data Analysis Project version 2 (GLODAPv2) – an internally consistent data product for the world ocean, Earth Syst. Sci. Data, 8, 297–323, https://doi.org/10.5194/essd-8-297-2016, 2016.
Olsen, A., Lange, N., Key, R. M., Tanhua, T., Bittig, H. C., Kozyr, A., Álvarez, M., Azetsu-Scott, K., Becker, S., Brown, P. J., Carter, B. R., Cotrim da Cunha, L., Feely, R. A., van Heuven, S., Hoppema, M., Ishii, M., Jeansson, E., Jutterström, S., Landa, C. S., Lauvset, S. K., Michaelis, P., Murata, A., Pérez, F. F., Pfeil, B., Schirnick, C., Steinfeldt, R., Suzuki, T., Tilbrook, B., Velo, A., Wanninkhof, R., and Woosley, R. J.: An updated version of the global interior ocean biogeochemical data product, GLODAPv2.2020, Earth Syst. Sci. Data, 12, 3653–3678, https://doi.org/10.5194/essd-12-3653-2020, 2020.
Orr, J. C., Epitalon, J.-M., Dickson, A. G., and Gattuso, J.-P.: Routine uncertainty propagation for the marine carbon dioxide system, Marine Chem., 207, 84–107, https://doi.org/10.1016/j.marchem.2018.10.006, 2018.
Pavlova, G. Y., Tishchenko, P. Y., Volkova, T. I., Dickson, A., and
Wallmann, K.: Intercalibration of Bruevich's method to determine the total
alkalinity in seawater, Oceanology, 48, 438–443, https://doi.org/10.1134/S0001437008030168, 2008.
Pipko, I. I., Pugach, S. P., Semiletov, I. P., Anderson, L. G., Shakhova, N. E., Gustafsson, Ö., Repina, I. A., Spivak, E. A., Charkin, A. N., Salyuk, A. N., Shcherbakova, K. P., Panova, E. V., and Dudarev, O. V.: The spatial and interannual dynamics of the surface water carbonate system and air–sea CO2 fluxes in the outer shelf and slope of the Eurasian Arctic Ocean, Ocean Sci., 13, 997–1016, https://doi.org/10.5194/os-13-997-2017, 2017.
Pitzer, K. S.: Ion Interaction Approach: Theory and Data Correlation, in: Activity Coefficients in Electrolyte Solutions, 2nd edn., edited by: Pitzer, K. S., CRC Press, Boca Raton, Florida 33431, 75–153, ISBN 0-8493-5415-3, 1991.
Polukhin, A.: The role of river runoff in the Kara Sea surface layer
acidification and carbonate system changes, Environ. Res. Lett.,
14, 105007, https://doi.org/10.1088/1748-9326/ab421e, 2019.
Remote Sensing Systems: SMAP Sea Surface Salinity Products. Ver. 4.0,
PO.DAAC [data set], https://doi.org/10.5067/SMP40-2SOCS, 2019.
Reynolds, R. W., Smith, T. M., Liu, C., Chelton, D. B., Casey, K. S., and
Schlax, M. G.: Daily high-resolution-blended analyses for sea surface
temperature, J. Climate, 20, 5473–5496, 2007.
Rödenbeck, C., Bakker, D. C. E., Gruber, N., Iida, Y., Jacobson, A. R., Jones, S., Landschützer, P., Metzl, N., Nakaoka, S., Olsen, A., Park, G.-H., Peylin, P., Rodgers, K. B., Sasse, T. P., Schuster, U., Shutler, J. D., Valsala, V., Wanninkhof, R., and Zeng, J.: Data-based estimates of the ocean carbon sink variability – first results of the Surface Ocean pCO2 Mapping intercomparison (SOCOM), Biogeosciences, 12, 7251–7278, https://doi.org/10.5194/bg-12-7251-2015, 2015.
Sasse, T. P., McNeil, B. I., and Abramowitz, G.: A novel method for diagnosing seasonal to inter-annual surface ocean carbon dynamics from bottle data using neural networks, Biogeosciences, 10, 4319–4340, https://doi.org/10.5194/bg-10-4319-2013, 2013.
Sathyendranath, S., Brewin, R. J. W., Brockmann, C., Brotas, V., Calton, B.,
Chuprin, A., Cipollini, P., Couto, A. B., Dingle, J., and Doerffer, R.: An
ocean-colour time series for use in climate studies: the experience of the
ocean-colour climate change initiative (OC-CCI), Sensors, 19, 4285, https://doi.org/10.3390/s19194285, 2019.
Sathyendranath, S., Jackson, T., Brockmann, C., Brotas, V., Calton, B.,
Chuprin, A., Clements, O., Cipollini, P., Danne, O., Dingle, J., Donlon, C.,
Grant, M., Groom, S., Krasemann, H., Lavender, S., Mazeran, C., Mélin,
F., Müller, D., Steinmetz, F., Valente, A., Zühlke, M., Feldman, G.,
Franz, B., Frouin, R., Werdell, J., and Platt, T.: ESA Ocean Colour Climate
Change Initiative (Ocean_Colour_cci): Global
chlorophyll-a data products gridded on a geographic projection, Version 5.0,
NERC EDS Centre for Environmental Data Analysis [data set], https://doi.org/10.5285/1dbe7a109c0244aaad713e078fd3059a, 2021.
Sulpis, O., Lauvset, S. K., and Hagens, M.: Current estimates of K
Szekely, T., Gourrion, J., Pouliquen, S., Reverdin, G., and Merceur, F.:
CORA, coriolis ocean dataset for reanalysis, https://doi.org/10.17882/46219, 2019.
Takahashi, T., Sutherland, S. C., Wanninkhof, R., Sweeney, C., Feely, R. A.,
Chipman, D. W., Hales, B., Friederich, G., Chavez, F., Sabine, C., Watson,
A., Bakker, D. C. E., Schuster, U., Metzl, N., Yoshikawa-Inoue, H., Ishii,
M., Midorikawa, T., Nojiri, Y., Körtzinger, A., Steinhoff, T., Hoppema,
M., Olafsson, J., Arnarson, T. S., Tilbrook, B., Johannessen, T., Olsen, A.,
Bellerby, R., Wong, C. S., Delille, B., Bates, N. R., and de Baar, H. J. W.:
Climatological mean and decadal change in surface ocean pCO2, and net
sea–air CO2 flux over the global oceans, Deep-Sea Res. Pt. II, 56, 554–577, https://doi.org/10.1016/j.dsr2.2008.12.009, 2009.
Takahashi, T., Sutherland, S. C., Chipman, D. W., Goddard, J. G., Ho, C.,
Newberger, T., Sweeney, C., and Munro, D. R.: Climatological distributions
of pH, pCO2, total CO2, alkalinity, and CaCO3 saturation in the global
surface ocean, and temporal changes at selected locations, Marine Chem.,
164, 95–125, 2014.
Takahashi, T., Sutherland, S. C., and Kozyr, A.: Global Ocean Surface Water
Partial Pressure of CO2 Database: Measurements Performed During 1957–2019
(LDEO Database Version 2019) (NCEI Accession 0160492), Version 9.9, NCEI [data set], https://doi.org/10.3334/CDIAC/OTG.NDP088(V2015), 2020.
Tishchenko, P. Y., Wong, C., Pavlova, G. Y., Johnson, W. K., Kang, D. J.,
and Kim, K. R.: The measurement of pH values in seawater using a cell
without a liquid junction, OCEANOLOGY C/C OF OKEANOLOGIIA, 41, 813–822,
2001.
Tishchenko, P. Y., Kang, D.-J., Chichkin, R. V., Lazaryuk, A. Y., Wong, C.
S., and Johnson, W. K.: Application of potentiometric method using a cell
without liquid junction to underway pH measurements in surface seawater,
Deep-Sea Res. Pt. I, 58, 778–786, 2011.
Wallhead, P. J., Bellerby, R. G. J., Silyakova, A., Slagstad, D., and
Polukhin, A. A.: Bottom water acidification and warming on the western
Eurasian Arctic shelves: dynamical downscaling projections, J.
Geophys. Res.-Oceans, 122, 8126–8144, 2017.
Watson, A. J., Schuster, U., Shutler, J. D., Holding, T., Ashton, I. G. C.,
Landschützer, P., Woolf, D. K., and Goddijn-Murphy, L.: Revised
estimates of ocean-atmosphere CO2 flux are consistent with ocean carbon
inventory, Nat. Commun., 11, 1–6, https://doi.org/10.1038/s41467-020-18203-3, 2020.
Williams, N. L., Juranek, L. W., Feely, R. A., Johnson, K. S., Sarmiento, J.
L., Talley, L. D., Dickson, A. G., Gray, A. R., Wanninkhof, R., Russell, J.
L., Riser, S. C., and Takeshita, Y.: Calculating surface ocean pCO2 from
biogeochemical Argo floats equipped with pH: An uncertainty analysis, Global
Biogeochem. Cycles, 31, 591–604, https://doi.org/10.1002/2016GB005541, 2017.
Wisdom, S.: Physical, chemical, biological, geophysical, and meteorological
data collected in the Arctic Ocean and Chukchi Sea in support of the Chukchi
Sea Environmental Studies Program (CSESP) from 2007 to 2014 (NCEI Accession
0124308), NOAA National Centers for Environmental Information [data set], https://www.ncei.noaa.gov/archive/accession/0124308 (last access: 20 February 2023),
2014.
Woolf, D. K., Land, P. E., Shutler, J. D., Goddijn-Murphy, L. M., and
Donlon, C. J.: On the calculation of air-sea fluxes of CO2 in the presence
of temperature and salinity gradients, J. Geophys. Res.-Oceans, 121, 1229–1248, https://doi.org/10.1002/2015JC011427, 2016.
Zhang, Y., Yamamoto-Kawai, M., and Williams, W. J.: Two decades of ocean
acidification in the surface waters of the Beaufort Gyre, Arctic Ocean:
Effects of sea ice melt and retreat from 1997–2016, Geophys. Res.
Lett., 47, e60119, https://doi.org/10.1029/2019GL086421, 2020.
Zweng, M. M., Seidov, D., Boyer, T., Locarnini, M., Garcia, H., Mishonov,
A., Baranova, O. K., Weathers, K., Paver, C. R., and Smolyar, I.: World
ocean atlas 2018, volume 2: Salinity, NOAA Atlas NESDIS 82 [data set], 50 pp., https://archimer.ifremer.fr/doc/00651/76339/ (last access: 20 February 2023), 2019.
Short summary
Measurements of the ocean’s carbonate system (e.g. CO2 and pH) have increased greatly in recent years, resulting in a need to combine these data with satellite measurements and model results, so they can be used to test predictions of how the ocean reacts to changes such as absorption of the CO2 emitted by humans. We show a method of combining data into regions of interest (100 km circles over a 10 d period) and apply it globally to produce a harmonised and easy-to-use data archive.
Measurements of the ocean’s carbonate system (e.g. CO2 and pH) have increased greatly in...
Altmetrics
Final-revised paper
Preprint