Articles | Volume 17, issue 2
https://doi.org/10.5194/essd-17-719-2025
© Author(s) 2025. 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-17-719-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
24 Feb 2025
Data description paper |
| 24 Feb 2025
| 24 Feb 2025
A global monthly 3D field of seawater pH over 3 decades: a machine learning approach
Guorong Zhong
Key Laboratory of Marine Ecology and Environmental Sciences, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, 266071, China
Laboratory for Marine Ecology and Environmental Science, Qingdao Marine Science and Technology Center, Qingdao, 266237, China
University of Chinese Academy of Sciences, Beijing, 101407, China
Center for Ocean Mega-Science, Chinese Academy of Sciences, Qingdao, 266071, China
Key Laboratory of Marine Ecology and Environmental Sciences, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, 266071, China
Laboratory for Marine Ecology and Environmental Science, Qingdao Marine Science and Technology Center, Qingdao, 266237, China
University of Chinese Academy of Sciences, Beijing, 101407, China
Center for Ocean Mega-Science, Chinese Academy of Sciences, Qingdao, 266071, China
Jinming Song
CORRESPONDING AUTHOR
Key Laboratory of Marine Ecology and Environmental Sciences, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, 266071, China
Laboratory for Marine Ecology and Environmental Science, Qingdao Marine Science and Technology Center, Qingdao, 266237, China
University of Chinese Academy of Sciences, Beijing, 101407, China
Center for Ocean Mega-Science, Chinese Academy of Sciences, Qingdao, 266071, China
Baoxiao Qu
Key Laboratory of Marine Ecology and Environmental Sciences, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, 266071, China
Laboratory for Marine Ecology and Environmental Science, Qingdao Marine Science and Technology Center, Qingdao, 266237, China
University of Chinese Academy of Sciences, Beijing, 101407, China
Center for Ocean Mega-Science, Chinese Academy of Sciences, Qingdao, 266071, China
Fan Wang
Key Laboratory of Marine Ecology and Environmental Sciences, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, 266071, China
Laboratory for Marine Ecology and Environmental Science, Qingdao Marine Science and Technology Center, Qingdao, 266237, China
University of Chinese Academy of Sciences, Beijing, 101407, China
Center for Ocean Mega-Science, Chinese Academy of Sciences, Qingdao, 266071, China
Yanjun Wang
Key Laboratory of Marine Ecology and Environmental Sciences, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, 266071, China
Center for Ocean Mega-Science, Chinese Academy of Sciences, Qingdao, 266071, China
Bin Zhang
Key Laboratory of Marine Ecology and Environmental Sciences, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, 266071, China
Center for Ocean Mega-Science, Chinese Academy of Sciences, Qingdao, 266071, China
Lijing Cheng
Center for Ocean Mega-Science, Chinese Academy of Sciences, Qingdao, 266071, China
Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China
Jun Ma
Key Laboratory of Marine Ecology and Environmental Sciences, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, 266071, China
Laboratory for Marine Ecology and Environmental Science, Qingdao Marine Science and Technology Center, Qingdao, 266237, China
University of Chinese Academy of Sciences, Beijing, 101407, China
Center for Ocean Mega-Science, Chinese Academy of Sciences, Qingdao, 266071, China
Huamao Yuan
Key Laboratory of Marine Ecology and Environmental Sciences, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, 266071, China
Laboratory for Marine Ecology and Environmental Science, Qingdao Marine Science and Technology Center, Qingdao, 266237, China
University of Chinese Academy of Sciences, Beijing, 101407, China
Center for Ocean Mega-Science, Chinese Academy of Sciences, Qingdao, 266071, China
Liqin Duan
Key Laboratory of Marine Ecology and Environmental Sciences, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, 266071, China
Laboratory for Marine Ecology and Environmental Science, Qingdao Marine Science and Technology Center, Qingdao, 266237, China
University of Chinese Academy of Sciences, Beijing, 101407, China
Center for Ocean Mega-Science, Chinese Academy of Sciences, Qingdao, 266071, China
Ning Li
Key Laboratory of Marine Ecology and Environmental Sciences, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, 266071, China
Laboratory for Marine Ecology and Environmental Science, Qingdao Marine Science and Technology Center, Qingdao, 266237, China
University of Chinese Academy of Sciences, Beijing, 101407, China
Center for Ocean Mega-Science, Chinese Academy of Sciences, Qingdao, 266071, China
Qidong Wang
Key Laboratory of Marine Ecology and Environmental Sciences, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, 266071, China
Laboratory for Marine Ecology and Environmental Science, Qingdao Marine Science and Technology Center, Qingdao, 266237, China
University of Chinese Academy of Sciences, Beijing, 101407, China
Center for Ocean Mega-Science, Chinese Academy of Sciences, Qingdao, 266071, China
Jianwei Xing
Key Laboratory of Marine Ecology and Environmental Sciences, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, 266071, China
Laboratory for Marine Ecology and Environmental Science, Qingdao Marine Science and Technology Center, Qingdao, 266237, China
University of Chinese Academy of Sciences, Beijing, 101407, China
Center for Ocean Mega-Science, Chinese Academy of Sciences, Qingdao, 266071, China
Jiajia Dai
Key Laboratory of Marine Ecology and Environmental Sciences, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, 266071, China
Laboratory for Marine Ecology and Environmental Science, Qingdao Marine Science and Technology Center, Qingdao, 266237, China
University of Chinese Academy of Sciences, Beijing, 101407, China
Center for Ocean Mega-Science, Chinese Academy of Sciences, Qingdao, 266071, China
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A predictor selection algorithm was constructed to decrease the predicting error in the surface ocean partial pressure of CO2 (pCO2) mapping by finding better combinations of pCO2 predictors in different regions. Compared with previous research using the same combination of predictors in all regions, using different predictors selected by the algorithm in different regions can effectively decrease pCO2 predicting errors.
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Guorong Zhong, Xuegang Li, Jinming Song, Baoxiao Qu, Fan Wang, Yanjun Wang, Bin Zhang, Xiaoxia Sun, Wuchang Zhang, Zhenyan Wang, Jun Ma, Huamao Yuan, and Liqin Duan
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A predictor selection algorithm was constructed to decrease the predicting error in the surface ocean partial pressure of CO2 (pCO2) mapping by finding better combinations of pCO2 predictors in different regions. Compared with previous research using the same combination of predictors in all regions, using different predictors selected by the algorithm in different regions can effectively decrease pCO2 predicting errors.
Karina von Schuckmann, Lijing Cheng, Matthew D. Palmer, James Hansen, Caterina Tassone, Valentin Aich, Susheel Adusumilli, Hugo Beltrami, Tim Boyer, Francisco José Cuesta-Valero, Damien Desbruyères, Catia Domingues, Almudena García-García, Pierre Gentine, John Gilson, Maximilian Gorfer, Leopold Haimberger, Masayoshi Ishii, Gregory C. Johnson, Rachel Killick, Brian A. King, Gottfried Kirchengast, Nicolas Kolodziejczyk, John Lyman, Ben Marzeion, Michael Mayer, Maeva Monier, Didier Paolo Monselesan, Sarah Purkey, Dean Roemmich, Axel Schweiger, Sonia I. Seneviratne, Andrew Shepherd, Donald A. Slater, Andrea K. Steiner, Fiammetta Straneo, Mary-Louise Timmermans, and Susan E. Wijffels
Earth Syst. Sci. Data, 12, 2013–2041, https://doi.org/10.5194/essd-12-2013-2020, https://doi.org/10.5194/essd-12-2013-2020, 2020
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Understanding how much and where the heat is distributed in the Earth system is fundamental to understanding how this affects warming oceans, atmosphere and land, rising temperatures and sea level, and loss of grounded and floating ice, which are fundamental concerns for society. This study is a Global Climate Observing System (GCOS) concerted international effort to obtain the Earth heat inventory over the period 1960–2018.
Lijing Cheng, Kevin E. Trenberth, Matthew D. Palmer, Jiang Zhu, and John P. Abraham
Ocean Sci., 12, 925–935, https://doi.org/10.5194/os-12-925-2016, https://doi.org/10.5194/os-12-925-2016, 2016
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A new method of observing ocean heat content throughout the entire ocean depth is provided. The new method is compared with simulated ocean heat content changes from climate models. The comparisons are carried out in various depth layers of the ocean waters. It is found that there is excellent agreement between the models and the observations. Furthermore, we propose that changes to ocean heat content be used as a fundamental metric to evaluate climate models.
L. Cheng, J. Zhu, and R. L. Sriver
Ocean Sci., 11, 719–741, https://doi.org/10.5194/os-11-719-2015, https://doi.org/10.5194/os-11-719-2015, 2015
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1. Argo floats were used to examine tropical cyclone (TC) induced ocean thermal changes on the global scale by comparing temperature profiles before and after TC passage.
2. Global average of the vertical structure of the average ocean thermal response for two different categories: tropical storms/depressions (TS/TD) and hurricanes were presented.
3. Significant differences between weak storm (TS/TD) and strong storm (hurricane) were found.
L. Cheng, J. Zhu, and R. L. Sriver
Ocean Sci. Discuss., https://doi.org/10.5194/osd-11-2907-2014, https://doi.org/10.5194/osd-11-2907-2014, 2014
Preprint withdrawn
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1. TCs are responsible for 1.87 PW (11.05 W/m2) of heat transfer annually from the global ocean to the atmosphere during storm passage (0-3 days) on a global scale. Of this total, 1.05±0.20 PW (4.80±0.85 W/m2) is caused by TS/TD and 0.82±0.21 PW (6.25±1.5 W/m2) is caused by hurricanes.
2.The net ocean heat uptake caused by all storms is 0.34 PW (4-20 days mean). Hurricanes induce 0.75±0.25 PW (5.98±2.1 W/m2) net heat gain, and TS/TD leads to 0.41±0.21 PW (1.90±0.96 W/m2) net heat loss.
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A database of marine macronutrient, temperature and salinity measurements made around the highly productive island of South Georgia, the Scotia Sea and the Antarctic Peninsula between 1980 and 2009
GLODAPv2.2022: the latest version of the global interior ocean biogeochemical data product
Oil slicks in the Gulf of Guinea – 10 years of Envisat Advanced Synthetic Aperture Radar observations
Léa Olivier, Jacqueline Boutin, Gilles Reverdin, Christopher Hunt, Thomas Linkowski, Alison Chase, Nils Haentjens, Pedro C. Junger, Stéphane Pesant, and Douglas Vandemark
Earth Syst. Sci. Data, 17, 3583–3598, https://doi.org/10.5194/essd-17-3583-2025, https://doi.org/10.5194/essd-17-3583-2025, 2025
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The air–sea CO2 flux in coastal waters plays a key role in the global carbon budget but remains poorly understood. In 2021, the Tara schooner collected 14 000 km of CO2 fugacity (fCO2) data along the South American coast. This dataset improves our understanding of fCO2 in the under-sampled Brazilian coastal region and provides a unique insight into the complex biogeochemistry of the Amazon River–ocean continuum.
Arianna Olivelli, Rossella Arcucci, Mark Rehkämper, and Tina van de Flierdt
Earth Syst. Sci. Data, 17, 3679–3699, https://doi.org/10.5194/essd-17-3679-2025, https://doi.org/10.5194/essd-17-3679-2025, 2025
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In this study, we use machine learning models to produce the first global maps of Pb concentrations and isotope compositions in the ocean. In line with observations, we find that (i) the surface Indian Ocean has the highest levels of pollution, (ii) pollution from previous decades is sinking in the North Atlantic and Pacific oceans, and (iii) waters carrying Pb pollution are spreading from the Southern Ocean throughout the Southern Hemisphere at intermediate depths.
Yongkai Chang, Ehui Tan, Dengzhou Gao, Cheng Liu, Zongxiao Zhang, Zhixiong Huang, Jianan Liu, Yu Han, Zifu Xu, Bin Chen, and Shuh-Ji Kao
Earth Syst. Sci. Data, 17, 3521–3540, https://doi.org/10.5194/essd-17-3521-2025, https://doi.org/10.5194/essd-17-3521-2025, 2025
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Denitrification and anaerobic ammonium oxidation (anammox) are two important nitrogen removal pathways that convert reactive nitrogen into dinitrogen gas. Here, we construct a global database on actual nitrogen loss rates, covering over 30 years of observations, measured in coastal and marine sediments. This work provides a global overview of the biogeography and potential controlling factors of denitrification and anammox and highlights the potential applications of this database.
Brendan R. Carter, Jörg Schwinger, Rolf Sonnerup, Andrea J. Fassbender, Jonathan D. Sharp, Larissa M. Dias, and Daniel E. Sandborn
Earth Syst. Sci. Data, 17, 3073–3088, https://doi.org/10.5194/essd-17-3073-2025, https://doi.org/10.5194/essd-17-3073-2025, 2025
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We infer ocean gas exchange and circulation from ocean tracer measurements and use this to create code to estimate the amount of carbon dioxide dissolved in the ocean that is there due to human emissions of CO2 into the atmosphere. The code works across the ocean depths for the past, present, or future from information about the location, temperature, and salinity of the seawater. We produce a data product with estimates throughout the ocean throughout the last ~300 and the next ~500 years.
Xiang Yu, Huadong Guo, Jiahua Zhang, Yi Ma, Xiaopeng Wang, Guangsheng Liu, Mingming Xing, Nuo Xu, and Ayalkibet M. Seka
Earth Syst. Sci. Data, 17, 2735–2759, https://doi.org/10.5194/essd-17-2735-2025, https://doi.org/10.5194/essd-17-2735-2025, 2025
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Mapping the 3D distribution of oceanic nitrate is challenging. We developed a continual-learning-based multilayer perceptron, integrating prior knowledge from numerical models and BGC-Argo validation to reconstruct a pan-European 3D nitrate field from 2010 to 2023 (0–2000 m depth, monthly, 0.25° horizontal resolution) using sea surface environmental features. This dataset helps bridge observational gaps and enhances understanding of the ocean's interior environment.
Nicolas Metzl, Jonathan Fin, Claire Lo Monaco, Claude Mignon, Samir Alliouane, Bruno Bombled, Jacqueline Boutin, Yann Bozec, Steeve Comeau, Pascal Conan, Laurent Coppola, Pascale Cuet, Eva Ferreira, Jean-Pierre Gattuso, Frédéric Gazeau, Catherine Goyet, Emilie Grossteffan, Bruno Lansard, Dominique Lefèvre, Nathalie Lefèvre, Coraline Leseurre, Sébastien Petton, Mireille Pujo-Pay, Christophe Rabouille, Gilles Reverdin, Céline Ridame, Peggy Rimmelin-Maury, Jean-François Ternon, Franck Touratier, Aline Tribollet, Thibaut Wagener, and Cathy Wimart-Rousseau
Earth Syst. Sci. Data, 17, 1075–1100, https://doi.org/10.5194/essd-17-1075-2025, https://doi.org/10.5194/essd-17-1075-2025, 2025
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This work presents a new synthesis of 67 000 total alkalinity and total dissolved inorganic carbon observations obtained between 1993 and 2023 in the global ocean, coastal zones, and the Mediterranean Sea. We describe the data assemblage and associated quality control and discuss some potential uses of this dataset. The dataset is provided in a single format and includes the quality flag for each sample.
Wen Yi, Xiaotong Wang, Tingkun He, Huan Liu, Zhenyu Luo, Zhaofeng Lv, and Kebin He
Earth Syst. Sci. Data, 17, 277–292, https://doi.org/10.5194/essd-17-277-2025, https://doi.org/10.5194/essd-17-277-2025, 2025
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This study presents a detailed global dataset on ship emissions, covering the years 2013 and 2016–2021, using advanced modeling techniques. The dataset includes emissions data for four types of greenhouse gases and five types of air pollutants. The data, available for research, offer valuable insights into ship emission spatiotemporal patterns by vessel type and age, providing a solid data foundation for fine-scale scientific research and shipping emission mitigation.
Zelun Wu, Wenfang Lu, Alizée Roobaert, Luping Song, Xiao-Hai Yan, and Wei-Jun Cai
Earth Syst. Sci. Data, 17, 43–63, https://doi.org/10.5194/essd-17-43-2025, https://doi.org/10.5194/essd-17-43-2025, 2025
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This study addresses the lack of comprehensive sea surface partial pressure of CO2 (pCO2) data in the North American Atlantic Coastal Ocean Margin (NAACOM) by developing the Reconstructed Coastal Acidification Database (ReCAD-NAACOM-pCO2). The product reconstructed sea surface pCO2 from 1993 to 2021 using machine-learning and environmental data, capturing seasonal cycles, regional variations, and long-term trends of pCO2 for coastal carbon research.
Viktor Gouretski, Lijing Cheng, Juan Du, Xiaogang Xing, Fei Chai, and Zhetao Tan
Earth Syst. Sci. Data, 16, 5503–5530, https://doi.org/10.5194/essd-16-5503-2024, https://doi.org/10.5194/essd-16-5503-2024, 2024
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High-quality observations are crucial to understanding ocean oxygen changes and their impact on marine biota. We developed a quality control procedure to ensure the high quality of the heterogeneous ocean oxygen data archive and to prove data consistency. Oxygen data obtained by means of oxygen sensors on autonomous Argo floats were compared with reference data based on the chemical analysis, and estimates of the residual offsets were obtained.
Riccardo Martellucci, Michele Giani, Elena Mauri, Laurent Coppola, Melf Paulsen, Marine Fourrier, Sara Pensieri, Vanessa Cardin, Carlotta Dentico, Roberto Bozzano, Carolina Cantoni, Anna Lucchetta, Alfredo Izquierdo, Miguel Bruno, and Ingunn Skjelvan
Earth Syst. Sci. Data, 16, 5333–5356, https://doi.org/10.5194/essd-16-5333-2024, https://doi.org/10.5194/essd-16-5333-2024, 2024
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As part of the ATL2MED demonstration experiment, two autonomous surface vehicles undertook a 9-month mission from the northeastern Atlantic to the Adriatic Sea. Biofouling affected the measurement of variables such as conductivity and dissolved oxygen. COVID-19 limited the availability of discrete samples for validation. We present correction methods for salinity and dissolved oxygen. We use model products to correct salinity and apply the Argo floats in-air correction method for oxygen
Malek Belgacem, Katrin Schroeder, Siv K. Lauvset, Marta Álvarez, Jacopo Chiggiato, Mireno Borghini, Carolina Cantoni, Tiziana Ciuffardi, and Stefania Sparnocchia
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-365, https://doi.org/10.5194/essd-2024-365, 2024
Revised manuscript accepted for ESSD
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Having consistent dissolved Oxygen (O2) data is crucial for understanding the health of our oceans. By monitoring O2 levels, we can spot changes in water quality. Reliable data helps scientist and policymakers make informed decisions to protect marine environments, ensuring practices that benefit both wildlife and people. The Mediterranean Sea is particularly sensitive to climate change. O2WMED dataset- a compilation of data that provides a clear picture of O2 changes over the past 20 years.
Shengqian Zhou, Ying Chen, Shan Huang, Xianda Gong, Guipeng Yang, Honghai Zhang, Hartmut Herrmann, Alfred Wiedensohler, Laurent Poulain, Yan Zhang, Fanghui Wang, Zongjun Xu, and Ke Yan
Earth Syst. Sci. Data, 16, 4267–4290, https://doi.org/10.5194/essd-16-4267-2024, https://doi.org/10.5194/essd-16-4267-2024, 2024
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Dimethyl sulfide (DMS) is a crucial natural reactive gas in the global climate system due to its great contribution to aerosols and subsequent impact on clouds over remote oceans. Leveraging machine learning techniques, we constructed a long-term global sea surface DMS gridded dataset with daily resolution. Compared to previous datasets, our new dataset holds promise for improving atmospheric chemistry modeling and advancing our comprehension of the climate effects associated with oceanic DMS.
Seyed Reza Saghravani, Michael Ernst Böttcher, Wei-Li Hong, Karol Kuliński, Aivo Lepland, Arunima Sen, and Beata Szymczycha
Earth Syst. Sci. Data, 16, 3419–3431, https://doi.org/10.5194/essd-16-3419-2024, https://doi.org/10.5194/essd-16-3419-2024, 2024
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A comprehensive study conducted in 2021 examined the distributions of dissolved nutrients and carbon in the western Spitsbergen fjords during the high-melting season. Significant spatial variability was observed in the water column and pore water concentrations of constituents, highlighting the unique biogeochemical characteristics of each fjord and their potential impact on ecosystem functioning and oceanographic processes.
Li-Qing Jiang, Tim P. Boyer, Christopher R. Paver, Hyelim Yoo, James R. Reagan, Simone R. Alin, Leticia Barbero, Brendan R. Carter, Richard A. Feely, and Rik Wanninkhof
Earth Syst. Sci. Data, 16, 3383–3390, https://doi.org/10.5194/essd-16-3383-2024, https://doi.org/10.5194/essd-16-3383-2024, 2024
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In this paper, we unveil a data product featuring ten coastal ocean acidification variables. These indicators are provided on 1°×1° spatial grids at 14 standardized depth levels, ranging from the surface to a depth of 500 m, along the North American ocean margins.
Amanda R. Fay, David R. Munro, Galen A. McKinley, Denis Pierrot, Stewart C. Sutherland, Colm Sweeney, and Rik Wanninkhof
Earth Syst. Sci. Data, 16, 2123–2139, https://doi.org/10.5194/essd-16-2123-2024, https://doi.org/10.5194/essd-16-2123-2024, 2024
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Presented here is a near-global monthly climatological estimate of the difference between atmosphere and ocean carbon dioxide concentrations. The ocean's ability to take up carbon, both now and in the future, is defined by this difference in concentrations. With over 30 million measurements of surface ocean carbon over the last 40 years and utilization of an extrapolation technique, a mean estimate of surface ocean ΔfCO2 is presented.
Siv K. Lauvset, Nico Lange, Toste Tanhua, Henry C. Bittig, Are Olsen, Alex Kozyr, Marta Álvarez, Kumiko Azetsu-Scott, Peter J. Brown, Brendan R. Carter, Leticia Cotrim da Cunha, Mario Hoppema, Matthew P. Humphreys, Masao Ishii, Emil Jeansson, Akihiko Murata, Jens Daniel Müller, Fiz F. Pérez, Carsten Schirnick, Reiner Steinfeldt, Toru Suzuki, Adam Ulfsbo, Anton Velo, Ryan J. Woosley, and Robert M. Key
Earth Syst. Sci. Data, 16, 2047–2072, https://doi.org/10.5194/essd-16-2047-2024, https://doi.org/10.5194/essd-16-2047-2024, 2024
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GLODAP is a data product for ocean inorganic carbon and related biogeochemical variables measured by the chemical analysis of water bottle samples from scientific cruises. GLODAPv2.2023 is the fifth update of GLODAPv2 from 2016. The data that are included have been subjected to extensive quality controlling, including systematic evaluation of measurement biases. This version contains data from 1108 hydrographic cruises covering the world's oceans from 1972 to 2021.
Nico Lange, Björn Fiedler, Marta Álvarez, Alice Benoit-Cattin, Heather Benway, Pier Luigi Buttigieg, Laurent Coppola, Kim Currie, Susana Flecha, Dana S. Gerlach, Makio Honda, I. Emma Huertas, Siv K. Lauvset, Frank Muller-Karger, Arne Körtzinger, Kevin M. O'Brien, Sólveig R. Ólafsdóttir, Fernando C. Pacheco, Digna Rueda-Roa, Ingunn Skjelvan, Masahide Wakita, Angelicque White, and Toste Tanhua
Earth Syst. Sci. Data, 16, 1901–1931, https://doi.org/10.5194/essd-16-1901-2024, https://doi.org/10.5194/essd-16-1901-2024, 2024
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The Synthesis Product for Ocean Time Series (SPOTS) is a novel achievement expanding and complementing the biogeochemical data landscape by providing consistent and high-quality biogeochemical time-series data from 12 ship-based fixed time-series programs. SPOTS covers multiple unique marine environments and time-series ranges, including data from 1983 to 2021. All in all, it facilitates a variety of applications that benefit from the collective value of biogeochemical time-series observations.
Sébastien Petton, Fabrice Pernet, Valérian Le Roy, Matthias Huber, Sophie Martin, Éric Macé, Yann Bozec, Stéphane Loisel, Peggy Rimmelin-Maury, Émilie Grossteffan, Michel Repecaud, Loïc Quemener, Michael Retho, Soazig Manac'h, Mathias Papin, Philippe Pineau, Thomas Lacoue-Labarthe, Jonathan Deborde, Louis Costes, Pierre Polsenaere, Loïc Rigouin, Jérémy Benhamou, Laure Gouriou, Joséphine Lequeux, Nathalie Labourdette, Nicolas Savoye, Grégory Messiaen, Elodie Foucault, Vincent Ouisse, Marion Richard, Franck Lagarde, Florian Voron, Valentin Kempf, Sébastien Mas, Léa Giannecchini, Francesca Vidussi, Behzad Mostajir, Yann Leredde, Samir Alliouane, Jean-Pierre Gattuso, and Frédéric Gazeau
Earth Syst. Sci. Data, 16, 1667–1688, https://doi.org/10.5194/essd-16-1667-2024, https://doi.org/10.5194/essd-16-1667-2024, 2024
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Our research highlights the concerning impact of rising carbon dioxide levels on coastal areas. To better understand these changes, we've established an observation network in France. By deploying pH sensors and other monitoring equipment at key coastal sites, we're gaining valuable insights into how various factors, such as freshwater inputs, tides, temperature, and biological processes, influence ocean pH.
Christian Lønborg, Cátia Carreira, Gwenaël Abril, Susana Agustí, Valentina Amaral, Agneta Andersson, Javier Arístegui, Punyasloke Bhadury, Mariana B. Bif, Alberto V. Borges, Steven Bouillon, Maria Ll. Calleja, Luiz C. Cotovicz Jr., Stefano Cozzi, Maryló Doval, Carlos M. Duarte, Bradley Eyre, Cédric G. Fichot, E. Elena García-Martín, Alexandra Garzon-Garcia, Michele Giani, Rafael Gonçalves-Araujo, Renee Gruber, Dennis A. Hansell, Fuminori Hashihama, Ding He, Johnna M. Holding, William R. Hunter, J. Severino P. Ibánhez, Valeria Ibello, Shan Jiang, Guebuem Kim, Katja Klun, Piotr Kowalczuk, Atsushi Kubo, Choon-Weng Lee, Cláudia B. Lopes, Federica Maggioni, Paolo Magni, Celia Marrase, Patrick Martin, S. Leigh McCallister, Roisin McCallum, Patricia M. Medeiros, Xosé Anxelu G. Morán, Frank E. Muller-Karger, Allison Myers-Pigg, Marit Norli, Joanne M. Oakes, Helena Osterholz, Hyekyung Park, Maria Lund Paulsen, Judith A. Rosentreter, Jeff D. Ross, Digna Rueda-Roa, Chiara Santinelli, Yuan Shen, Eva Teira, Tinkara Tinta, Guenther Uher, Masahide Wakita, Nicholas Ward, Kenta Watanabe, Yu Xin, Youhei Yamashita, Liyang Yang, Jacob Yeo, Huamao Yuan, Qiang Zheng, and Xosé Antón Álvarez-Salgado
Earth Syst. Sci. Data, 16, 1107–1119, https://doi.org/10.5194/essd-16-1107-2024, https://doi.org/10.5194/essd-16-1107-2024, 2024
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In this paper, we present the first edition of a global database compiling previously published and unpublished measurements of dissolved organic matter (DOM) collected in coastal waters (CoastDOM v1). Overall, the CoastDOM v1 dataset will be useful to identify global spatial and temporal patterns and to facilitate reuse in studies aimed at better characterizing local biogeochemical processes and identifying a baseline for modelling future changes in coastal waters.
Simone R. Alin, Jan A. Newton, Richard A. Feely, Dana Greeley, Beth Curry, Julian Herndon, and Mark Warner
Earth Syst. Sci. Data, 16, 837–865, https://doi.org/10.5194/essd-16-837-2024, https://doi.org/10.5194/essd-16-837-2024, 2024
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The Salish cruise data product provides 2008–2018 oceanographic data from the southern Salish Sea and nearby coastal sampling stations. Temperature, salinity, oxygen, nutrient, and dissolved inorganic carbon measurements from 715 oceanographic profiles will facilitate further study of ocean acidification, hypoxia, and marine heatwave impacts in this region. Three subsets of the compiled datasets from 35 cruises are available with consistent formatting and multiple commonly used units.
Henry C. Bittig, Erik Jacobs, Thomas Neumann, and Gregor Rehder
Earth Syst. Sci. Data, 16, 753–773, https://doi.org/10.5194/essd-16-753-2024, https://doi.org/10.5194/essd-16-753-2024, 2024
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We present a pCO2 climatology of the Baltic Sea using a new approach to extrapolate from individual observations to the entire Baltic Sea. The extrapolation approach uses (a) a model to inform on how data at one location are connected to data at other locations, together with (b) very accurate pCO2 observations from 2003 to 2021 as the base data. The climatology can be used e.g. to assess uptake and release of CO2 or to identify extreme events.
Francesco Placenti, Marco Torri, Katrin Schroeder, Mireno Borghini, Gabriella Cerrati, Angela Cuttitta, Vincenzo Tancredi, Carmelo Buscaino, and Bernardo Patti
Earth Syst. Sci. Data, 16, 743–752, https://doi.org/10.5194/essd-16-743-2024, https://doi.org/10.5194/essd-16-743-2024, 2024
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Oceanographic surveys were conducted in the Strait of Sicily between 2010 and 2021. This paper provides a description of the time series of nutrients and hydrological data collected in this zone. The dataset fills an important gap in field observations of a crucial area where exchanges with the Mediterranean sub-basin take place, providing support for studies aimed at describing ongoing processes and at realizing reliable projections of the effects of these processes in the near future.
Natalie M. Monacci, Jessica N. Cross, Wiley Evans, Jeremy T. Mathis, and Hongjie Wang
Earth Syst. Sci. Data, 16, 647–665, https://doi.org/10.5194/essd-16-647-2024, https://doi.org/10.5194/essd-16-647-2024, 2024
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As carbon dioxide is released into the air through human-generated activity, about one third dissolves into the surface water of oceans, lowering pH and increasing acidity. This is known as ocean acidification. We merged 10 years of ocean carbon data and made them publicly available for adaptation planning during a time of change. The data confirmed that Alaska is already experiencing the effects of ocean acidification due to naturally cold water, high productivity, and circulation patterns.
Alizée Roobaert, Pierre Regnier, Peter Landschützer, and Goulven G. Laruelle
Earth Syst. Sci. Data, 16, 421–441, https://doi.org/10.5194/essd-16-421-2024, https://doi.org/10.5194/essd-16-421-2024, 2024
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The quantification of the coastal air–sea CO2 exchange (FCO2) has improved in recent years, but its multiannual variability remains unclear. This study, based on interpolated observations, reconstructs the longest global time series of coastal FCO2 (1982–2020). Results show the coastal ocean acts as a CO2 sink, with increasing intensity over time. This new coastal FCO2-product allows establishing regional carbon budgets and provides new constraints for closing the global carbon cycle.
Esther G. Kennedy, Meghan Zulian, Sara L. Hamilton, Tessa M. Hill, Manuel Delgado, Carina R. Fish, Brian Gaylord, Kristy J. Kroeker, Hannah M. Palmer, Aurora M. Ricart, Eric Sanford, Ana K. Spalding, Melissa Ward, Guadalupe Carrasco, Meredith Elliott, Genece V. Grisby, Evan Harris, Jaime Jahncke, Catherine N. Rocheleau, Sebastian Westerink, and Maddie I. Wilmot
Earth Syst. Sci. Data, 16, 219–243, https://doi.org/10.5194/essd-16-219-2024, https://doi.org/10.5194/essd-16-219-2024, 2024
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We present a new synthesis of oceanographic observations along the US West Coast that has been optimized for multiparameter investigations of coastal warming, deoxygenation, and acidification risk. This synthesis includes both previously published and new observations, all of which have been consistently formatted and quality-controlled to facilitate high-resolution investigations of climate risks and consequences across a wide range of spatial and temporal scales.
Thi-Tuyet-Trang Chau, Marion Gehlen, Nicolas Metzl, and Frédéric Chevallier
Earth Syst. Sci. Data, 16, 121–160, https://doi.org/10.5194/essd-16-121-2024, https://doi.org/10.5194/essd-16-121-2024, 2024
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CMEMS-LSCE leads as the first global observation-based reconstructions of six carbonate system variables for the years 1985–2021 at monthly and 0.25° resolutions. The high-resolution reconstructions outperform their 1° counterpart in reproducing horizontal and temporal gradients of observations over various oceanic regions to nearshore time series stations. New datasets can be exploited in numerous studies, including monitoring changes in ocean carbon uptake and ocean acidification.
Nicolas Metzl, Jonathan Fin, Claire Lo Monaco, Claude Mignon, Samir Alliouane, David Antoine, Guillaume Bourdin, Jacqueline Boutin, Yann Bozec, Pascal Conan, Laurent Coppola, Frédéric Diaz, Eric Douville, Xavier Durrieu de Madron, Jean-Pierre Gattuso, Frédéric Gazeau, Melek Golbol, Bruno Lansard, Dominique Lefèvre, Nathalie Lefèvre, Fabien Lombard, Férial Louanchi, Liliane Merlivat, Léa Olivier, Anne Petrenko, Sébastien Petton, Mireille Pujo-Pay, Christophe Rabouille, Gilles Reverdin, Céline Ridame, Aline Tribollet, Vincenzo Vellucci, Thibaut Wagener, and Cathy Wimart-Rousseau
Earth Syst. Sci. Data, 16, 89–120, https://doi.org/10.5194/essd-16-89-2024, https://doi.org/10.5194/essd-16-89-2024, 2024
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This work presents a synthesis of 44 000 total alkalinity and dissolved inorganic carbon observations obtained between 1993 and 2022 in the Global Ocean and the Mediterranean Sea at the surface and in the water column. Seawater samples were measured using the same method and calibrated with international Certified Reference Material. We describe the data assemblage, quality control and some potential uses of this dataset.
Céline Heuzé, Oliver Huhn, Maren Walter, Natalia Sukhikh, Salar Karam, Wiebke Körtke, Myriel Vredenborg, Klaus Bulsiewicz, Jürgen Sültenfuß, Ying-Chih Fang, Christian Mertens, Benjamin Rabe, Sandra Tippenhauer, Jacob Allerholt, Hailun He, David Kuhlmey, Ivan Kuznetsov, and Maria Mallet
Earth Syst. Sci. Data, 15, 5517–5534, https://doi.org/10.5194/essd-15-5517-2023, https://doi.org/10.5194/essd-15-5517-2023, 2023
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Gases dissolved in the ocean water not used by the ecosystem (or "passive tracers") are invaluable to track water over long distances and investigate the processes that modify its properties. Unfortunately, especially so in the ice-covered Arctic Ocean, such gas measurements are sparse. We here present a data set of several passive tracers (anthropogenic gases, noble gases and their isotopes) collected over the full ocean depth, weekly, during the 1-year drift in the Arctic during MOSAiC.
Weiyi Tang, Bess B. Ward, Michael Beman, Laura Bristow, Darren Clark, Sarah Fawcett, Claudia Frey, François Fripiat, Gerhard J. Herndl, Mhlangabezi Mdutyana, Fabien Paulot, Xuefeng Peng, Alyson E. Santoro, Takuhei Shiozaki, Eva Sintes, Charles Stock, Xin Sun, Xianhui S. Wan, Min N. Xu, and Yao Zhang
Earth Syst. Sci. Data, 15, 5039–5077, https://doi.org/10.5194/essd-15-5039-2023, https://doi.org/10.5194/essd-15-5039-2023, 2023
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Nitrification and nitrifiers play an important role in marine nitrogen and carbon cycles by converting ammonium to nitrite and nitrate. Nitrification could affect microbial community structure, marine productivity, and the production of nitrous oxide – a powerful greenhouse gas. We introduce the newly constructed database of nitrification and nitrifiers in the marine water column and guide future research efforts in field observations and model development of nitrification.
Jonathan D. Sharp, Andrea J. Fassbender, Brendan R. Carter, Gregory C. Johnson, Cristina Schultz, and John P. Dunne
Earth Syst. Sci. Data, 15, 4481–4518, https://doi.org/10.5194/essd-15-4481-2023, https://doi.org/10.5194/essd-15-4481-2023, 2023
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Dissolved oxygen content is a critical metric of ocean health. Recently, expanding fleets of autonomous platforms that measure oxygen in the ocean have produced a wealth of new data. We leverage machine learning to take advantage of this growing global dataset, producing a gridded data product of ocean interior dissolved oxygen at monthly resolution over nearly 2 decades. This work provides novel information for investigations of spatial, seasonal, and interannual variability in ocean oxygen.
Olivia Gibb, Frédéric Cyr, Kumiko Azetsu-Scott, Joël Chassé, Darlene Childs, Carrie-Ellen Gabriel, Peter S. Galbraith, Gary Maillet, Pierre Pepin, Stephen Punshon, and Michel Starr
Earth Syst. Sci. Data, 15, 4127–4162, https://doi.org/10.5194/essd-15-4127-2023, https://doi.org/10.5194/essd-15-4127-2023, 2023
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The ocean absorbs large quantities of carbon dioxide (CO2) released into the atmosphere as a result of the burning of fossil fuels. This, in turn, causes ocean acidification, which poses a major threat to global ocean ecosystems. In this study, we compiled 9 years (2014–2022) of ocean carbonate data (i.e., ocean acidification parameters) collected in Atlantic Canada as part of the Atlantic Zone Monitoring Program.
Öykü Z. Mete, Adam V. Subhas, Heather H. Kim, Ann G. Dunlea, Laura M. Whitmore, Alan M. Shiller, Melissa Gilbert, William D. Leavitt, and Tristan J. Horner
Earth Syst. Sci. Data, 15, 4023–4045, https://doi.org/10.5194/essd-15-4023-2023, https://doi.org/10.5194/essd-15-4023-2023, 2023
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We present results from a machine learning model that accurately predicts dissolved barium concentrations for the global ocean. Our results reveal that the whole-ocean barium inventory is significantly lower than previously thought and that the deep ocean below 1000 m is at equilibrium with respect to barite. The model output can be used for a number of applications, including intercomparison, interpolation, and identification of regions warranting additional investigation.
Zhibo Shao, Yangchun Xu, Hua Wang, Weicheng Luo, Lice Wang, Yuhong Huang, Nona Sheila R. Agawin, Ayaz Ahmed, Mar Benavides, Mikkel Bentzon-Tilia, Ilana Berman-Frank, Hugo Berthelot, Isabelle C. Biegala, Mariana B. Bif, Antonio Bode, Sophie Bonnet, Deborah A. Bronk, Mark V. Brown, Lisa Campbell, Douglas G. Capone, Edward J. Carpenter, Nicolas Cassar, Bonnie X. Chang, Dreux Chappell, Yuh-ling Lee Chen, Matthew J. Church, Francisco M. Cornejo-Castillo, Amália Maria Sacilotto Detoni, Scott C. Doney, Cecile Dupouy, Marta Estrada, Camila Fernandez, Bieito Fernández-Castro, Debany Fonseca-Batista, Rachel A. Foster, Ken Furuya, Nicole Garcia, Kanji Goto, Jesús Gago, Mary R. Gradoville, M. Robert Hamersley, Britt A. Henke, Cora Hörstmann, Amal Jayakumar, Zhibing Jiang, Shuh-Ji Kao, David M. Karl, Leila R. Kittu, Angela N. Knapp, Sanjeev Kumar, Julie LaRoche, Hongbin Liu, Jiaxing Liu, Caroline Lory, Carolin R. Löscher, Emilio Marañón, Lauren F. Messer, Matthew M. Mills, Wiebke Mohr, Pia H. Moisander, Claire Mahaffey, Robert Moore, Beatriz Mouriño-Carballido, Margaret R. Mulholland, Shin-ichiro Nakaoka, Joseph A. Needoba, Eric J. Raes, Eyal Rahav, Teodoro Ramírez-Cárdenas, Christian Furbo Reeder, Lasse Riemann, Virginie Riou, Julie C. Robidart, Vedula V. S. S. Sarma, Takuya Sato, Himanshu Saxena, Corday Selden, Justin R. Seymour, Dalin Shi, Takuhei Shiozaki, Arvind Singh, Rachel E. Sipler, Jun Sun, Koji Suzuki, Kazutaka Takahashi, Yehui Tan, Weiyi Tang, Jean-Éric Tremblay, Kendra Turk-Kubo, Zuozhu Wen, Angelicque E. White, Samuel T. Wilson, Takashi Yoshida, Jonathan P. Zehr, Run Zhang, Yao Zhang, and Ya-Wei Luo
Earth Syst. Sci. Data, 15, 3673–3709, https://doi.org/10.5194/essd-15-3673-2023, https://doi.org/10.5194/essd-15-3673-2023, 2023
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N2 fixation by marine diazotrophs is an important bioavailable N source to the global ocean. This updated global oceanic diazotroph database increases the number of in situ measurements of N2 fixation rates, diazotrophic cell abundances, and nifH gene copy abundances by 184 %, 86 %, and 809 %, respectively. Using the updated database, the global marine N2 fixation rate is estimated at 223 ± 30 Tg N yr−1, which triplicates that using the original database.
Jean-Pierre Gattuso, Samir Alliouane, and Philipp Fischer
Earth Syst. Sci. Data, 15, 2809–2825, https://doi.org/10.5194/essd-15-2809-2023, https://doi.org/10.5194/essd-15-2809-2023, 2023
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The Arctic Ocean is subject to high rates of ocean warming and acidification, with critical implications for marine organisms, ecosystems and the services they provide. We report here on the first high-frequency (1 h), multi-year (5 years) dataset of the carbonate system at a coastal site in a high-Arctic fjord (Kongsfjorden, Svalbard). This site is a significant sink for CO2 every month of the year (9 to 17 mol m-2 yr-1). The saturation state of aragonite can be as low as 1.3.
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
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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.
Yayoi Inomata and Michio Aoyama
Earth Syst. Sci. Data, 15, 1969–2007, https://doi.org/10.5194/essd-15-1969-2023, https://doi.org/10.5194/essd-15-1969-2023, 2023
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The behavior of 137Cs in surface seawater in the global ocean was analyzed by using the HAMGlobal2021 database. Approximately 32 % of 137Cs existed in the surface seawater in 1970. The 137Cs released into the North Pacific Ocean by large-scale nuclear weapons tests was transported to the Indian Ocean and then the Atlantic Ocean on a 4–5 decadal timescale, whereas 137Cs released from nuclear reprocessing plants was transported northward to the Arctic Ocean on a decadal scale.
Zhixuan Wang, Guizhi Wang, Xianghui Guo, Yan Bai, Yi Xu, and Minhan Dai
Earth Syst. Sci. Data, 15, 1711–1731, https://doi.org/10.5194/essd-15-1711-2023, https://doi.org/10.5194/essd-15-1711-2023, 2023
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We reconstructed monthly sea surface pCO2 data with a high spatial resolution in the South China Sea (SCS) from 2003 to 2020. We validate our reconstruction with three independent testing datasets and present a new method to assess the uncertainty of the data. The results strongly suggest that our reconstruction effectively captures the main features of the spatiotemporal patterns of pCO2 in the SCS. Using this dataset, we found that the SCS is overall a weak source of atmospheric CO2.
Peter Edward Land, Helen S. Findlay, Jamie D. Shutler, Jean-Francois Piolle, Richard Sims, Hannah Green, Vassilis Kitidis, Alexander Polukhin, and Irina I. Pipko
Earth Syst. Sci. Data, 15, 921–947, https://doi.org/10.5194/essd-15-921-2023, https://doi.org/10.5194/essd-15-921-2023, 2023
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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.
Giulia Leone, Ana I. Catarino, Liesbeth De Keukelaere, Mattias Bossaer, Els Knaeps, and Gert Everaert
Earth Syst. Sci. Data, 15, 745–752, https://doi.org/10.5194/essd-15-745-2023, https://doi.org/10.5194/essd-15-745-2023, 2023
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This paper illustrates a dataset of hyperspectral reflectance measurements of macroplastics. Plastic samples consisted of pristine, artificially weathered, and biofouled plastic items and field plastic debris. Samples were measured in dry conditions and a subset of plastics in wet and submerged conditions. This dataset can be used to better understand plastic optical features when exposed to natural agents and to support the development of algorithms for monitoring environmental plastics.
Michael J. Whitehouse, Katharine R. Hendry, Geraint A. Tarling, Sally E. Thorpe, and Petra ten Hoopen
Earth Syst. Sci. Data, 15, 211–224, https://doi.org/10.5194/essd-15-211-2023, https://doi.org/10.5194/essd-15-211-2023, 2023
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We present a database of Southern Ocean macronutrient, temperature and salinity measurements collected on 20 oceanographic cruises between 1980 and 2009. Vertical profiles and underway surface measurements were collected year-round as part of an integrated ecosystem study. Our data provide a novel view of biogeochemical cycling in biologically productive regions across a critical period in recent climate history and will contribute to a better understanding of the drivers of primary production.
Siv K. Lauvset, Nico Lange, Toste Tanhua, Henry C. Bittig, Are Olsen, Alex Kozyr, Simone Alin, Marta Álvarez, Kumiko Azetsu-Scott, Leticia Barbero, Susan Becker, Peter J. Brown, Brendan R. Carter, Leticia Cotrim da Cunha, Richard A. Feely, Mario Hoppema, Matthew P. Humphreys, Masao Ishii, Emil Jeansson, Li-Qing Jiang, Steve D. Jones, Claire Lo Monaco, Akihiko Murata, Jens Daniel Müller, Fiz F. Pérez, Benjamin Pfeil, Carsten Schirnick, Reiner Steinfeldt, Toru Suzuki, Bronte Tilbrook, Adam Ulfsbo, Anton Velo, Ryan J. Woosley, and Robert M. Key
Earth Syst. Sci. Data, 14, 5543–5572, https://doi.org/10.5194/essd-14-5543-2022, https://doi.org/10.5194/essd-14-5543-2022, 2022
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GLODAP is a data product for ocean inorganic carbon and related biogeochemical variables measured by the chemical analysis of water bottle samples from scientific cruises. GLODAPv2.2022 is the fourth update of GLODAPv2 from 2016. The data that are included have been subjected to extensive quality controlling, including systematic evaluation of measurement biases. This version contains data from 1085 hydrographic cruises covering the world's oceans from 1972 to 2021.
Zhour Najoui, Nellya Amoussou, Serge Riazanoff, Guillaume Aurel, and Frédéric Frappart
Earth Syst. Sci. Data, 14, 4569–4588, https://doi.org/10.5194/essd-14-4569-2022, https://doi.org/10.5194/essd-14-4569-2022, 2022
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Oil spills could have serious repercussions for both the marine environment and ecosystem. The Gulf of Guinea is a very active area with respect to maritime traffic as well as oil and gas exploitation (platforms). As a result, the region is subject to a large number of oil pollution events. This study aims to detect oil slicks in the Gulf of Guinea and analyse their spatial and temporal distribution using satellite data.
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Ólafsdóttir, S. R., Benoit-Cattin, A., and Danielsen, M.: Dissolved inorganic carbon (DIC), total alkalinity, temperature, salinity, nutrients and dissolved oxygen collected from discrete samples and profile observations during the R/Vs Arni Fridriksson and Bjarni Saemundsson Irminger Sea (FX9) time series cruises in the North Atlantic Ocean in from 2014-02-11 to 2022-08-09 (NCEI Accession 0209072), NOAA National Centers for Environmental Information [data set], https://doi.org/10.25921/vjmy-8h90, 2020a.
Ólafsdóttir, S. R., Benoit-Cattin, A., and Danielsen, M.: Dissolved inorganic carbon (DIC), total alkalinity, temperature, salinity, nutrients and dissolved oxygen collected from discrete samples and profile observations during the R/Vs Arni Fridriksson and Bjarni Saemundsson time series IcelandSea (LN6) cruises in the North Atlantic Ocean from 2014-02-18 to 2022-08-16 (NCEI Accession 0209074), NOAA National Centers for Environmental Information [data set], https://doi.org/10.25921/qhed-3h84, 2020b.
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Short summary
The continuous uptake of atmospheric CO2 by the ocean leads to decreasing seawater pH, which is an ongoing threat to the marine ecosystem. This pH change has been globally documented in the surface ocean, but information is limited below the surface. Here, we present a monthly 1° gridded product of global seawater pH based on a machine learning method and real pH observations. The pH product covers the years from 1992 to 2020 and depths from 0 to 2000 m.
The continuous uptake of atmospheric CO2 by the ocean leads to decreasing seawater pH, which is...
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