Articles | Volume 16, issue 8
https://doi.org/10.5194/essd-16-3517-2024
© Author(s) 2024. 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-16-3517-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
02 Aug 2024
Data description paper |
| 02 Aug 2024
| 02 Aug 2024
IAPv4 ocean temperature and ocean heat content gridded dataset
Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China
University of Chinese Academy of Sciences, Beijing, 101408, China
Yuying Pan
Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China
University of Chinese Academy of Sciences, Beijing, 101408, China
Zhetao Tan
Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China
University of Chinese Academy of Sciences, Beijing, 101408, China
Huayi Zheng
Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China
University of Chinese Academy of Sciences, Beijing, 101408, China
Yujing Zhu
Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China
University of Chinese Academy of Sciences, Beijing, 101408, China
Wangxu Wei
Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China
University of Chinese Academy of Sciences, Beijing, 101408, China
Juan Du
Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China
Huifeng Yuan
Computer Network Information Center, Chinese Academy of Sciences, Beijing, 100083, China
University of Chinese Academy of Sciences, Beijing, 101408, China
Guancheng Li
Eco-Environmental Monitoring and Research Center, Pearl River Valley and South China Sea Ecology and Environment Administration, Ministry of Ecology and Environment, PRC, Guangzhou, 510611, China
Hanlin Ye
Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China
Viktor Gouretski
Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China
Yuanlong Li
Institute of Oceanography, Chinese Academy of Sciences, Qingdao, 266000, China
University of Chinese Academy of Sciences, Beijing, 101408, China
Kevin E. Trenberth
National Center for Atmospheric Research, P.O. Box 3000, Boulder, CO 80307, USA
Department of Physics, University of Auckland, Tāmaki Makaurau / Auckland, Aotearoa / New Zealand
John Abraham
University of St. Thomas, School of Engineering, 2115 Summit Ave, St Paul, MN 55105, USA
Yuchun Jin
Institute of Oceanography, Chinese Academy of Sciences, Qingdao, 266000, China
University of Chinese Academy of Sciences, Beijing, 101408, China
Franco Reseghetti
Istituto Nazionale di Geofisica e Vulcanologia, 40127, Bologna, Italy
Xiaopei Lin
Frontier Science Center for Deep Ocean Multispheres and Earth System and Physical Oceanography Laboratory, Ocean University of China, Qingdao, 266100, China
Bin Zhang
Institute of Oceanography, Chinese Academy of Sciences, Qingdao, 266000, China
Gengxin Chen
State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou, 510301, China
University of Chinese Academy of Sciences, Beijing, 101408, China
Michael E. Mann
Dept. of Earth and Environmental Science, University of Pennsylvania, Philadelphia, PA, USA
Jiang Zhu
Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China
University of Chinese Academy of Sciences, Beijing, 101408, China
Related authors
Piers M. Forster, Chris Smith, Tristram Walsh, William F. Lamb, Robin Lamboll, Christophe Cassou, Mathias Hauser, Zeke Hausfather, June-Yi Lee, Matthew D. Palmer, Karina von Schuckmann, Aimée B. A. Slangen, Sophie Szopa, Blair Trewin, Jeongeun Yun, Nathan P. Gillett, Stuart Jenkins, H. Damon Matthews, Krishnan Raghavan, Aurélien Ribes, Joeri Rogelj, Debbie Rosen, Xuebin Zhang, Myles Allen, Lara Aleluia Reis, Robbie M. Andrew, Richard A. Betts, Alex Borger, Jiddu A. Broersma, Samantha N. Burgess, Lijing Cheng, Pierre Friedlingstein, Catia M. Domingues, Marco Gambarini, Thomas Gasser, Johannes Gütschow, Masayoshi Ishii, Christopher Kadow, John Kennedy, Rachel E. Killick, Paul B. Krummel, Aurélien Liné, Didier P. Monselesan, Colin Morice, Jens Mühle, Vaishali Naik, Glen P. Peters, Anna Pirani, Julia Pongratz, Jan C. Minx, Matthew Rigby, Robert Rohde, Abhishek Savita, Sonia I. Seneviratne, Peter Thorne, Christopher Wells, Luke M. Western, Guido R. van der Werf, Susan E. Wijffels, Valérie Masson-Delmotte, and Panmao Zhai
Earth Syst. Sci. Data, 17, 2641–2680, https://doi.org/10.5194/essd-17-2641-2025, https://doi.org/10.5194/essd-17-2641-2025, 2025
Short summary
Short summary
In a rapidly changing climate, evidence-based decision-making benefits from up-to-date and timely information. Here we compile monitoring datasets to track real-world changes over time. To make our work relevant to policymakers, we follow methods from the Intergovernmental Panel on Climate Change (IPCC). Human activities are increasing the Earth's energy imbalance and driving faster sea-level rise compared to the IPCC assessment.
Guorong Zhong, Xuegang Li, Jinming Song, Baoxiao Qu, Fan Wang, Yanjun Wang, Bin Zhang, Lijing Cheng, Jun Ma, Huamao Yuan, Liqin Duan, Ning Li, Qidong Wang, Jianwei Xing, and Jiajia Dai
Earth Syst. Sci. Data, 17, 719–740, https://doi.org/10.5194/essd-17-719-2025, https://doi.org/10.5194/essd-17-719-2025, 2025
Short summary
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.
Simona Simoncelli, Franco Reseghetti, Claudia Fratianni, Lijing Cheng, and Giancarlo Raiteri
Earth Syst. Sci. Data, 16, 5531–5561, https://doi.org/10.5194/essd-16-5531-2024, https://doi.org/10.5194/essd-16-5531-2024, 2024
Short summary
Short summary
This data review is about the reprocessing of historical eXpendable BathyThermograp (XBT) profiles from the Ligurian and Tyrrhenian seas over the time period 1999–2019. A new automated quality control analysis has been performed starting from the original raw data and operational log sheets. The data have been formatted and standardized according to the latest community best practices, and all available metadata have been inserted, including calibration information and uncertainty specification.
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
Short summary
Short summary
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.
Karina von Schuckmann, Lorena Moreira, Mathilde Cancet, Flora Gues, Emmanuelle Autret, Jonathan Baker, Clément Bricaud, Romain Bourdalle-Badie, Lluis Castrillo, Lijing Cheng, Frederic Chevallier, Daniele Ciani, Alvaro de Pascual-Collar, Vincenzo De Toma, Marie Drevillon, Claudia Fanelli, Gilles Garric, Marion Gehlen, Rianne Giesen, Kevin Hodges, Doroteaciro Iovino, Simon Jandt-Scheelke, Eric Jansen, Melanie Juza, Ioanna Karagali, Thomas Lavergne, Simona Masina, Ronan McAdam, Audrey Minière, Helen Morrison, Tabea Rebekka Panteleit, Andrea Pisano, Marie-Isabelle Pujol, Ad Stoffelen, Sulian Thual, Simon Van Gennip, Pierre Veillard, Chunxue Yang, and Hao Zuo
State Planet, 4-osr8, 1, https://doi.org/10.5194/sp-4-osr8-1-2024, https://doi.org/10.5194/sp-4-osr8-1-2024, 2024
Piers M. Forster, Chris Smith, Tristram Walsh, William F. Lamb, Robin Lamboll, Bradley Hall, Mathias Hauser, Aurélien Ribes, Debbie Rosen, Nathan P. Gillett, Matthew D. Palmer, Joeri Rogelj, Karina von Schuckmann, Blair Trewin, Myles Allen, Robbie Andrew, Richard A. Betts, Alex Borger, Tim Boyer, Jiddu A. Broersma, Carlo Buontempo, Samantha Burgess, Chiara Cagnazzo, Lijing Cheng, Pierre Friedlingstein, Andrew Gettelman, Johannes Gütschow, Masayoshi Ishii, Stuart Jenkins, Xin Lan, Colin Morice, Jens Mühle, Christopher Kadow, John Kennedy, Rachel E. Killick, Paul B. Krummel, Jan C. Minx, Gunnar Myhre, Vaishali Naik, Glen P. Peters, Anna Pirani, Julia Pongratz, Carl-Friedrich Schleussner, Sonia I. Seneviratne, Sophie Szopa, Peter Thorne, Mahesh V. M. Kovilakam, Elisa Majamäki, Jukka-Pekka Jalkanen, Margreet van Marle, Rachel M. Hoesly, Robert Rohde, Dominik Schumacher, Guido van der Werf, Russell Vose, Kirsten Zickfeld, Xuebin Zhang, Valérie Masson-Delmotte, and Panmao Zhai
Earth Syst. Sci. Data, 16, 2625–2658, https://doi.org/10.5194/essd-16-2625-2024, https://doi.org/10.5194/essd-16-2625-2024, 2024
Short summary
Short summary
This paper tracks some key indicators of global warming through time, from 1850 through to the end of 2023. It is designed to give an authoritative estimate of global warming to date and its causes. We find that in 2023, global warming reached 1.3 °C and is increasing at over 0.2 °C per decade. This is caused by all-time-high greenhouse gas emissions.
Piers M. Forster, Christopher J. Smith, Tristram Walsh, William F. Lamb, Robin Lamboll, Mathias Hauser, Aurélien Ribes, Debbie Rosen, Nathan Gillett, Matthew D. Palmer, Joeri Rogelj, Karina von Schuckmann, Sonia I. Seneviratne, Blair Trewin, Xuebin Zhang, Myles Allen, Robbie Andrew, Arlene Birt, Alex Borger, Tim Boyer, Jiddu A. Broersma, Lijing Cheng, Frank Dentener, Pierre Friedlingstein, José M. Gutiérrez, Johannes Gütschow, Bradley Hall, Masayoshi Ishii, Stuart Jenkins, Xin Lan, June-Yi Lee, Colin Morice, Christopher Kadow, John Kennedy, Rachel Killick, Jan C. Minx, Vaishali Naik, Glen P. Peters, Anna Pirani, Julia Pongratz, Carl-Friedrich Schleussner, Sophie Szopa, Peter Thorne, Robert Rohde, Maisa Rojas Corradi, Dominik Schumacher, Russell Vose, Kirsten Zickfeld, Valérie Masson-Delmotte, and Panmao Zhai
Earth Syst. Sci. Data, 15, 2295–2327, https://doi.org/10.5194/essd-15-2295-2023, https://doi.org/10.5194/essd-15-2295-2023, 2023
Short summary
Short summary
This is a critical decade for climate action, but there is no annual tracking of the level of human-induced warming. We build on the Intergovernmental Panel on Climate Change assessment reports that are authoritative but published infrequently to create a set of key global climate indicators that can be tracked through time. Our hope is that this becomes an important annual publication that policymakers, media, scientists and the public can refer to.
Karina von Schuckmann, Audrey Minière, Flora Gues, Francisco José Cuesta-Valero, Gottfried Kirchengast, Susheel Adusumilli, Fiammetta Straneo, Michaël Ablain, Richard P. Allan, Paul M. Barker, Hugo Beltrami, Alejandro Blazquez, Tim Boyer, Lijing Cheng, John Church, Damien Desbruyeres, Han Dolman, Catia M. Domingues, Almudena García-García, Donata Giglio, John E. Gilson, Maximilian Gorfer, Leopold Haimberger, Maria Z. Hakuba, Stefan Hendricks, Shigeki Hosoda, Gregory C. Johnson, Rachel Killick, Brian King, Nicolas Kolodziejczyk, Anton Korosov, Gerhard Krinner, Mikael Kuusela, Felix W. Landerer, Moritz Langer, Thomas Lavergne, Isobel Lawrence, Yuehua Li, John Lyman, Florence Marti, Ben Marzeion, Michael Mayer, Andrew H. MacDougall, Trevor McDougall, Didier Paolo Monselesan, Jan Nitzbon, Inès Otosaka, Jian Peng, Sarah Purkey, Dean Roemmich, Kanako Sato, Katsunari Sato, Abhishek Savita, Axel Schweiger, Andrew Shepherd, Sonia I. Seneviratne, Leon Simons, Donald A. Slater, Thomas Slater, Andrea K. Steiner, Toshio Suga, Tanguy Szekely, Wim Thiery, Mary-Louise Timmermans, Inne Vanderkelen, Susan E. Wjiffels, Tonghua Wu, and Michael Zemp
Earth Syst. Sci. Data, 15, 1675–1709, https://doi.org/10.5194/essd-15-1675-2023, https://doi.org/10.5194/essd-15-1675-2023, 2023
Short summary
Short summary
Earth's climate is out of energy balance, and this study quantifies how much heat has consequently accumulated over the past decades (ocean: 89 %, land: 6 %, cryosphere: 4 %, atmosphere: 1 %). Since 1971, this accumulated heat reached record values at an increasing pace. The Earth heat inventory provides a comprehensive view on the status and expectation of global warming, and we call for an implementation of this global climate indicator into the Paris Agreement’s Global Stocktake.
Tian Tian, Lijing Cheng, Gongjie Wang, John Abraham, Wangxu Wei, Shihe Ren, Jiang Zhu, Junqiang Song, and Hongze Leng
Earth Syst. Sci. Data, 14, 5037–5060, https://doi.org/10.5194/essd-14-5037-2022, https://doi.org/10.5194/essd-14-5037-2022, 2022
Short summary
Short summary
A high-resolution gridded dataset is crucial for understanding ocean processes at various spatiotemporal scales. Here we used a machine learning approach and successfully reconstructed a high-resolution (0.25° × 0.25°) ocean subsurface (1–2000 m) salinity dataset for the period 1993–2018 (monthly) by merging in situ salinity profile observations with high-resolution satellite remote-sensing data. This new product could be useful in various applications in ocean and climate fields.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Piers M. Forster, Chris Smith, Tristram Walsh, William F. Lamb, Robin Lamboll, Christophe Cassou, Mathias Hauser, Zeke Hausfather, June-Yi Lee, Matthew D. Palmer, Karina von Schuckmann, Aimée B. A. Slangen, Sophie Szopa, Blair Trewin, Jeongeun Yun, Nathan P. Gillett, Stuart Jenkins, H. Damon Matthews, Krishnan Raghavan, Aurélien Ribes, Joeri Rogelj, Debbie Rosen, Xuebin Zhang, Myles Allen, Lara Aleluia Reis, Robbie M. Andrew, Richard A. Betts, Alex Borger, Jiddu A. Broersma, Samantha N. Burgess, Lijing Cheng, Pierre Friedlingstein, Catia M. Domingues, Marco Gambarini, Thomas Gasser, Johannes Gütschow, Masayoshi Ishii, Christopher Kadow, John Kennedy, Rachel E. Killick, Paul B. Krummel, Aurélien Liné, Didier P. Monselesan, Colin Morice, Jens Mühle, Vaishali Naik, Glen P. Peters, Anna Pirani, Julia Pongratz, Jan C. Minx, Matthew Rigby, Robert Rohde, Abhishek Savita, Sonia I. Seneviratne, Peter Thorne, Christopher Wells, Luke M. Western, Guido R. van der Werf, Susan E. Wijffels, Valérie Masson-Delmotte, and Panmao Zhai
Earth Syst. Sci. Data, 17, 2641–2680, https://doi.org/10.5194/essd-17-2641-2025, https://doi.org/10.5194/essd-17-2641-2025, 2025
Short summary
Short summary
In a rapidly changing climate, evidence-based decision-making benefits from up-to-date and timely information. Here we compile monitoring datasets to track real-world changes over time. To make our work relevant to policymakers, we follow methods from the Intergovernmental Panel on Climate Change (IPCC). Human activities are increasing the Earth's energy imbalance and driving faster sea-level rise compared to the IPCC assessment.
Guorong Zhong, Xuegang Li, Jinming Song, Baoxiao Qu, Fan Wang, Yanjun Wang, Bin Zhang, Lijing Cheng, Jun Ma, Huamao Yuan, Liqin Duan, Ning Li, Qidong Wang, Jianwei Xing, and Jiajia Dai
Earth Syst. Sci. Data, 17, 719–740, https://doi.org/10.5194/essd-17-719-2025, https://doi.org/10.5194/essd-17-719-2025, 2025
Short summary
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.
Simona Simoncelli, Franco Reseghetti, Claudia Fratianni, Lijing Cheng, and Giancarlo Raiteri
Earth Syst. Sci. Data, 16, 5531–5561, https://doi.org/10.5194/essd-16-5531-2024, https://doi.org/10.5194/essd-16-5531-2024, 2024
Short summary
Short summary
This data review is about the reprocessing of historical eXpendable BathyThermograp (XBT) profiles from the Ligurian and Tyrrhenian seas over the time period 1999–2019. A new automated quality control analysis has been performed starting from the original raw data and operational log sheets. The data have been formatted and standardized according to the latest community best practices, and all available metadata have been inserted, including calibration information and uncertainty specification.
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
Short summary
Short summary
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.
Karina von Schuckmann, Lorena Moreira, Mathilde Cancet, Flora Gues, Emmanuelle Autret, Jonathan Baker, Clément Bricaud, Romain Bourdalle-Badie, Lluis Castrillo, Lijing Cheng, Frederic Chevallier, Daniele Ciani, Alvaro de Pascual-Collar, Vincenzo De Toma, Marie Drevillon, Claudia Fanelli, Gilles Garric, Marion Gehlen, Rianne Giesen, Kevin Hodges, Doroteaciro Iovino, Simon Jandt-Scheelke, Eric Jansen, Melanie Juza, Ioanna Karagali, Thomas Lavergne, Simona Masina, Ronan McAdam, Audrey Minière, Helen Morrison, Tabea Rebekka Panteleit, Andrea Pisano, Marie-Isabelle Pujol, Ad Stoffelen, Sulian Thual, Simon Van Gennip, Pierre Veillard, Chunxue Yang, and Hao Zuo
State Planet, 4-osr8, 1, https://doi.org/10.5194/sp-4-osr8-1-2024, https://doi.org/10.5194/sp-4-osr8-1-2024, 2024
Lei Kong, Xiao Tang, Zifa Wang, Jiang Zhu, Jianjun Li, Huangjian Wu, Qizhong Wu, Huansheng Chen, Lili Zhu, Wei Wang, Bing Liu, Qian Wang, Duohong Chen, Yuepeng Pan, Jie Li, Lin Wu, and Gregory R. Carmichael
Earth Syst. Sci. Data, 16, 4351–4387, https://doi.org/10.5194/essd-16-4351-2024, https://doi.org/10.5194/essd-16-4351-2024, 2024
Short summary
Short summary
A new long-term inversed emission inventory for Chinese air quality (CAQIEI) is developed in this study, which contains constrained monthly emissions of NOx, SO2, CO, PM2.5, PM10, and NMVOCs in China from 2013 to 2020 with a horizontal resolution of 15 km. Emissions of different air pollutants and their changes during 2013–2020 were investigated and compared with previous emission inventories, which sheds new light on the complex variations of air pollutant emissions in China.
Mikhail Y. Verbitsky, Michael E. Mann, and Dmitry Volobuev
Earth Syst. Dynam., 15, 1015–1017, https://doi.org/10.5194/esd-15-1015-2024, https://doi.org/10.5194/esd-15-1015-2024, 2024
Short summary
Short summary
It was recently suggested that global warming can be explained by the non-anthropogenic factor of seismic activity. If that is the case, it would have profound implications. We have assessed the validity of the claim by using a statistical technique that evaluates the existence of causal connections between variables, finding no evidence for any causal relationship between seismic activity and global warming.
Piers M. Forster, Chris Smith, Tristram Walsh, William F. Lamb, Robin Lamboll, Bradley Hall, Mathias Hauser, Aurélien Ribes, Debbie Rosen, Nathan P. Gillett, Matthew D. Palmer, Joeri Rogelj, Karina von Schuckmann, Blair Trewin, Myles Allen, Robbie Andrew, Richard A. Betts, Alex Borger, Tim Boyer, Jiddu A. Broersma, Carlo Buontempo, Samantha Burgess, Chiara Cagnazzo, Lijing Cheng, Pierre Friedlingstein, Andrew Gettelman, Johannes Gütschow, Masayoshi Ishii, Stuart Jenkins, Xin Lan, Colin Morice, Jens Mühle, Christopher Kadow, John Kennedy, Rachel E. Killick, Paul B. Krummel, Jan C. Minx, Gunnar Myhre, Vaishali Naik, Glen P. Peters, Anna Pirani, Julia Pongratz, Carl-Friedrich Schleussner, Sonia I. Seneviratne, Sophie Szopa, Peter Thorne, Mahesh V. M. Kovilakam, Elisa Majamäki, Jukka-Pekka Jalkanen, Margreet van Marle, Rachel M. Hoesly, Robert Rohde, Dominik Schumacher, Guido van der Werf, Russell Vose, Kirsten Zickfeld, Xuebin Zhang, Valérie Masson-Delmotte, and Panmao Zhai
Earth Syst. Sci. Data, 16, 2625–2658, https://doi.org/10.5194/essd-16-2625-2024, https://doi.org/10.5194/essd-16-2625-2024, 2024
Short summary
Short summary
This paper tracks some key indicators of global warming through time, from 1850 through to the end of 2023. It is designed to give an authoritative estimate of global warming to date and its causes. We find that in 2023, global warming reached 1.3 °C and is increasing at over 0.2 °C per decade. This is caused by all-time-high greenhouse gas emissions.
Yangyang Yu, Shaoqing Zhang, Haohuan Fu, Dexun Chen, Yang Gao, Xiaopei Lin, Zhao Liu, and Xiaojing Lv
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-10, https://doi.org/10.5194/gmd-2024-10, 2024
Preprint withdrawn
Short summary
Short summary
The hardware-related perturbations caused by the heterogeneous many-core architectures can blend with software or human errors, which can affect the accuracy of the model consistency verification. We develop a deep learning-based consistency test tool for ESMs on the heterogeneous systems (ESM-DCT) and evaluate it in CESM on new Sunway system. The ESM-DCT can detect the existence of software or human errors when taking hardware-related perturbations into account.
Piers M. Forster, Christopher J. Smith, Tristram Walsh, William F. Lamb, Robin Lamboll, Mathias Hauser, Aurélien Ribes, Debbie Rosen, Nathan Gillett, Matthew D. Palmer, Joeri Rogelj, Karina von Schuckmann, Sonia I. Seneviratne, Blair Trewin, Xuebin Zhang, Myles Allen, Robbie Andrew, Arlene Birt, Alex Borger, Tim Boyer, Jiddu A. Broersma, Lijing Cheng, Frank Dentener, Pierre Friedlingstein, José M. Gutiérrez, Johannes Gütschow, Bradley Hall, Masayoshi Ishii, Stuart Jenkins, Xin Lan, June-Yi Lee, Colin Morice, Christopher Kadow, John Kennedy, Rachel Killick, Jan C. Minx, Vaishali Naik, Glen P. Peters, Anna Pirani, Julia Pongratz, Carl-Friedrich Schleussner, Sophie Szopa, Peter Thorne, Robert Rohde, Maisa Rojas Corradi, Dominik Schumacher, Russell Vose, Kirsten Zickfeld, Valérie Masson-Delmotte, and Panmao Zhai
Earth Syst. Sci. Data, 15, 2295–2327, https://doi.org/10.5194/essd-15-2295-2023, https://doi.org/10.5194/essd-15-2295-2023, 2023
Short summary
Short summary
This is a critical decade for climate action, but there is no annual tracking of the level of human-induced warming. We build on the Intergovernmental Panel on Climate Change assessment reports that are authoritative but published infrequently to create a set of key global climate indicators that can be tracked through time. Our hope is that this becomes an important annual publication that policymakers, media, scientists and the public can refer to.
Karina von Schuckmann, Audrey Minière, Flora Gues, Francisco José Cuesta-Valero, Gottfried Kirchengast, Susheel Adusumilli, Fiammetta Straneo, Michaël Ablain, Richard P. Allan, Paul M. Barker, Hugo Beltrami, Alejandro Blazquez, Tim Boyer, Lijing Cheng, John Church, Damien Desbruyeres, Han Dolman, Catia M. Domingues, Almudena García-García, Donata Giglio, John E. Gilson, Maximilian Gorfer, Leopold Haimberger, Maria Z. Hakuba, Stefan Hendricks, Shigeki Hosoda, Gregory C. Johnson, Rachel Killick, Brian King, Nicolas Kolodziejczyk, Anton Korosov, Gerhard Krinner, Mikael Kuusela, Felix W. Landerer, Moritz Langer, Thomas Lavergne, Isobel Lawrence, Yuehua Li, John Lyman, Florence Marti, Ben Marzeion, Michael Mayer, Andrew H. MacDougall, Trevor McDougall, Didier Paolo Monselesan, Jan Nitzbon, Inès Otosaka, Jian Peng, Sarah Purkey, Dean Roemmich, Kanako Sato, Katsunari Sato, Abhishek Savita, Axel Schweiger, Andrew Shepherd, Sonia I. Seneviratne, Leon Simons, Donald A. Slater, Thomas Slater, Andrea K. Steiner, Toshio Suga, Tanguy Szekely, Wim Thiery, Mary-Louise Timmermans, Inne Vanderkelen, Susan E. Wjiffels, Tonghua Wu, and Michael Zemp
Earth Syst. Sci. Data, 15, 1675–1709, https://doi.org/10.5194/essd-15-1675-2023, https://doi.org/10.5194/essd-15-1675-2023, 2023
Short summary
Short summary
Earth's climate is out of energy balance, and this study quantifies how much heat has consequently accumulated over the past decades (ocean: 89 %, land: 6 %, cryosphere: 4 %, atmosphere: 1 %). Since 1971, this accumulated heat reached record values at an increasing pace. The Earth heat inventory provides a comprehensive view on the status and expectation of global warming, and we call for an implementation of this global climate indicator into the Paris Agreement’s Global Stocktake.
Zhenming Wang, Shaoqing Zhang, Yishuai Jin, Yinglai Jia, Yangyang Yu, Yang Gao, Xiaolin Yu, Mingkui Li, Xiaopei Lin, and Lixin Wu
Geosci. Model Dev., 16, 705–717, https://doi.org/10.5194/gmd-16-705-2023, https://doi.org/10.5194/gmd-16-705-2023, 2023
Short summary
Short summary
To improve the numerical model predictability of monthly extended-range scales, we use the simplified slab ocean model (SOM) to restrict the complicated sea surface temperature (SST) bias from a 3-D dynamical ocean model. As for SST prediction, whether in space or time, the WRF-SOM is verified to have better performance than the WRF-ROMS, which has a significant impact on the atmosphere. For extreme weather events such as typhoons, the predictions of WRF-SOM are in good agreement with WRF-ROMS.
Tian Tian, Lijing Cheng, Gongjie Wang, John Abraham, Wangxu Wei, Shihe Ren, Jiang Zhu, Junqiang Song, and Hongze Leng
Earth Syst. Sci. Data, 14, 5037–5060, https://doi.org/10.5194/essd-14-5037-2022, https://doi.org/10.5194/essd-14-5037-2022, 2022
Short summary
Short summary
A high-resolution gridded dataset is crucial for understanding ocean processes at various spatiotemporal scales. Here we used a machine learning approach and successfully reconstructed a high-resolution (0.25° × 0.25°) ocean subsurface (1–2000 m) salinity dataset for the period 1993–2018 (monthly) by merging in situ salinity profile observations with high-resolution satellite remote-sensing data. This new product could be useful in various applications in ocean and climate fields.
Yangyang Yu, Shaoqing Zhang, Haohuan Fu, Lixin Wu, Dexun Chen, Yang Gao, Zhiqiang Wei, Dongning Jia, and Xiaopei Lin
Geosci. Model Dev., 15, 6695–6708, https://doi.org/10.5194/gmd-15-6695-2022, https://doi.org/10.5194/gmd-15-6695-2022, 2022
Short summary
Short summary
To understand the scientific consequence of perturbations caused by slave cores in heterogeneous computing environments, we examine the influence of perturbation amplitudes on the determination of the cloud bottom and cloud top and compute the probability density function (PDF) of generated clouds. A series of comparisons of the PDFs between homogeneous and heterogeneous systems show consistently acceptable error tolerances when using slave cores in heterogeneous computing environments.
Jingzhe Sun, Yingjing Jiang, Shaoqing Zhang, Weimin Zhang, Lv Lu, Guangliang Liu, Yuhu Chen, Xiang Xing, Xiaopei Lin, and Lixin Wu
Geosci. Model Dev., 15, 4805–4830, https://doi.org/10.5194/gmd-15-4805-2022, https://doi.org/10.5194/gmd-15-4805-2022, 2022
Short summary
Short summary
An online ensemble coupled data assimilation system with the Community Earth System Model is designed and evaluated. This system uses the memory-based information transfer approach which avoids frequent I/O operations. The observations of surface pressure, sea surface temperature, and in situ temperature and salinity profiles can be effectively assimilated into the coupled model. That will facilitate a long-term high-resolution climate reanalysis once the algorithm efficiency is much improved.
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
Biogeosciences, 19, 845–859, https://doi.org/10.5194/bg-19-845-2022, https://doi.org/10.5194/bg-19-845-2022, 2022
Short summary
Short summary
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.
Zhaohui Chen, Parvadha Suntharalingam, Andrew J. Watson, Ute Schuster, Jiang Zhu, and Ning Zeng
Biogeosciences, 18, 4549–4570, https://doi.org/10.5194/bg-18-4549-2021, https://doi.org/10.5194/bg-18-4549-2021, 2021
Short summary
Short summary
As the global temperature continues to increase, carbon dioxide (CO2) is a major driver of this global warming. The increased CO2 is mainly caused by emissions from fossil fuel use and land use. At the same time, the ocean is a significant sink in the carbon cycle. The North Atlantic is a critical ocean region in reducing CO2 concentration. We estimate the CO2 uptake in this region based on a carbon inverse system and atmospheric CO2 observations.
Weiqi Xu, Chun Chen, Yanmei Qiu, Ying Li, Zhiqiang Zhang, Eleni Karnezi, Spyros N. Pandis, Conghui Xie, Zhijie Li, Jiaxing Sun, Nan Ma, Wanyun Xu, Pingqing Fu, Zifa Wang, Jiang Zhu, Douglas R. Worsnop, Nga Lee Ng, and Yele Sun
Atmos. Chem. Phys., 21, 5463–5476, https://doi.org/10.5194/acp-21-5463-2021, https://doi.org/10.5194/acp-21-5463-2021, 2021
Short summary
Short summary
Here aerosol volatility and viscosity at a rural site (Gucheng) and an urban site (Beijing) in the North China Plain (NCP) were investigated in summer and winter. Our results showed that organic aerosol (OA) in winter in the NCP is more volatile than that in summer due to enhanced primary emissions from coal combustion and biomass burning. We also found that OA existed mainly as a solid in winter in Beijing but as semisolids in Beijing in summer and Gucheng in winter.
Lei Kong, Xiao Tang, Jiang Zhu, Zifa Wang, Jianjun Li, Huangjian Wu, Qizhong Wu, Huansheng Chen, Lili Zhu, Wei Wang, Bing Liu, Qian Wang, Duohong Chen, Yuepeng Pan, Tao Song, Fei Li, Haitao Zheng, Guanglin Jia, Miaomiao Lu, Lin Wu, and Gregory R. Carmichael
Earth Syst. Sci. Data, 13, 529–570, https://doi.org/10.5194/essd-13-529-2021, https://doi.org/10.5194/essd-13-529-2021, 2021
Short summary
Short summary
China's air pollution has changed substantially since 2013. Here we have developed a 6-year-long high-resolution air quality reanalysis dataset over China from 2013 to 2018 to illustrate such changes and to provide a basic dataset for relevant studies. Surface fields of PM2.5, PM10, SO2, NO2, CO, and O3 concentrations are provided, and the evaluation results indicate that the reanalysis dataset has excellent performance in reproducing the magnitude and variation of air pollution in China.
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
Short summary
Short summary
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.
Lei Kong, Xiao Tang, Jiang Zhu, Zifa Wang, Joshua S. Fu, Xuemei Wang, Syuichi Itahashi, Kazuyo Yamaji, Tatsuya Nagashima, Hyo-Jung Lee, Cheol-Hee Kim, Chuan-Yao Lin, Lei Chen, Meigen Zhang, Zhining Tao, Jie Li, Mizuo Kajino, Hong Liao, Zhe Wang, Kengo Sudo, Yuesi Wang, Yuepeng Pan, Guiqian Tang, Meng Li, Qizhong Wu, Baozhu Ge, and Gregory R. Carmichael
Atmos. Chem. Phys., 20, 181–202, https://doi.org/10.5194/acp-20-181-2020, https://doi.org/10.5194/acp-20-181-2020, 2020
Short summary
Short summary
Evaluation and uncertainty investigation of NO2, CO and NH3 modeling over China were conducted in this study using 14 chemical transport model results from MICS-Asia III. All models largely underestimated CO concentrations and showed very poor performance in reproducing the observed monthly variations of NH3 concentrations. Potential factors related to such deficiencies are investigated and discussed in this paper.
Wei Zhang, Chunyan Liu, Xunhua Zheng, Kai Wang, Feng Cui, Rui Wang, Siqi Li, Zhisheng Yao, and Jiang Zhu
Biogeosciences, 16, 2905–2922, https://doi.org/10.5194/bg-16-2905-2019, https://doi.org/10.5194/bg-16-2905-2019, 2019
Short summary
Short summary
A biogeochemical process model-based approach for screening the best management practices (BMPs) of a three-crop system was proposed. The BMPs are the management alternatives with the lowest negative impact potentials that still satisfy all given constraints. Three BMP alternatives with overlapping uncertainties of simulated NIPs were screened from 6000 scenarios using the modified DNDC95 model, which could sustain crop yields, enlarge SOC stock, mitigate GHG, and reduce other nitrogen losses.
Ullala Pathiranage Gayan Pathirana, Gengxin Chen, Tilak Priyadarshana, and Dongxiao Wang
Ocean Sci. Discuss., https://doi.org/10.5194/os-2017-67, https://doi.org/10.5194/os-2017-67, 2017
Revised manuscript not accepted
Short summary
Short summary
Seasonal changes of the mixed layer heat storage in the BoB significantly contribute to the regional weather and climate by inducing air-sea interactions. Seasonality associated with vertical mixing and barrier layer indicates the seasonal response from the ocean in the BoB. This study will provide a significant contribution to further studies on air-sea interactions in the BoB, especially the role of vertical mixing and barrier layer variation during cyclone formation and intensification.
Xiaolin Yu, Shaoqing Zhang, Xiaopei Lin, and Mingkui Li
Nonlin. Processes Geophys., 24, 125–139, https://doi.org/10.5194/npg-24-125-2017, https://doi.org/10.5194/npg-24-125-2017, 2017
Short summary
Short summary
Parameter estimation (PE) with a global coupled data assimilation (CDA) system can improve the runs, but the improvement remains in a limited range. We have to come back to simple models to sort out the sources of noises. Incomplete observations and the chaotic nature of the atmosphere have much stronger influences on the PE through the state estimation (SE) process. Here, we propose the guidelines of how to enhance the signal-to-noise ratio under partial SE status.
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
Short summary
Short summary
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.
Jingen Xiao, Qiang Xie, Dongxiao Wang, Lei Yang, Yeqiang Shu, Changjian Liu, Ju Chen, Jinglong Yao, and Gengxin Chen
Ocean Sci., 12, 335–344, https://doi.org/10.5194/os-12-335-2016, https://doi.org/10.5194/os-12-335-2016, 2016
Short summary
Short summary
We examine near-inertial variability of the meridional overturning circulation in the South China Sea (SCSMOC) using a global 1 / 12° ocean reanalysis. Based on wavelet analysis and power spectrum, we suggest that deep SCSMOC has a significant near-inertial band. The maximum amplitude of the near-inertial signal in the SCSMOC is nearly 4 Sv. The spatial structure of the signal features regularly alternating counterclockwise and clockwise overturning cells.
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
Short summary
Short summary
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
Short summary
Short summary
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.
Related subject area
Domain: ESSD – Ocean | Subject: Physical oceanography
ASM-SS: the first quasi-global high-spatial-resolution coastal storm surge dataset reconstructed from tide gauge records
Expendable bathythermograph (XBT) data collected along the Southern Ocean chokepoint between Aotearoa / New Zealand and Antarctica, 1994–2024
HHU24SWDSCS: a shallow-water depth model over island areas in the South China Sea retrieved from satellite-derived bathymetry
Gap-filled sub-surface mooring dataset off Western Australia during 2010–2023
The International Altimetry Service 2024 (IAS2024) coastal sea level dataset and first evaluations
Global ocean surface heat fluxes derived from the maximum entropy production framework accounting for ocean heat storage and Bowen ratio adjustments
A European database of resources on coastal storm impacts
Multi-year observations of near-bed hydrodynamics and suspended sediment at the core of the estuarine turbidity maximum of the Changjiang Estuary
Surface current variability in the East Australian Current from long-term high-frequency radar observations
SDUST2023VGGA: a global ocean vertical gradient of gravity anomaly model determined from multidirectional data from mean sea surface
The Italian contribution to the Synoptic Arctic Survey programme: the 2021 CASSANDRA cruise (LB21) through the Greenland Sea Gyre along the 75°N transect
A revisiting of early 18th century environmental data to identify Gulf of Lion properties before the industrial era
A global daily mesoscale front dataset from satellite observations: In situ validation and cross-dataset comparison
Satellite-based Analysis of Ocean-Surface Stress across the Ice-free and Ice-covered Polar Oceans
A new multi-grid bathymetric dataset of the Gulf of Naples (Italy) from complementary multi-beam echo sounders
A New-Generation Internal Tide Model Based on 30 Years of Satellite Sea Surface Height Measurements
A submesoscale eddy identification dataset in the northwest Pacific Ocean derived from GOCI I chlorophyll a data based on deep learning
MASCS 1.0: synchronous atmospheric and oceanic data from a cross-shaped moored array in the northern South China Sea during 2014–2015
Reprocessing of eXpendable BathyThermograph (XBT) profiles from the Ligurian and Tyrrhenian seas over the time period 1999–2019 with a full metadata upgrade
Coastal Atmosphere and Sea Time Series (CoASTS) and Bio-Optical mapping of Marine Properties (BiOMaP): the CoASTS-BiOMaP dataset
Spatio-temporal changes in China's mainland shorelines over 30 years using Landsat time series data (1990–2019)
ISASO2: recent trends and regional patterns of ocean dissolved oxygen change
Constructing a 22-year internal wave dataset for the northern South China Sea: spatiotemporal analysis using MODIS imagery and deep learning
Near-real-time atmospheric and oceanic science products of Himawari-8 and Himawari-9 geostationary satellites over the South China Sea
ReefTEMPS: The Pacific Islands Coastal Temperature Network
High-resolution observations of the ocean upper layer south of Cape St. Vincent, the western northern margin of the Gulf of Cádiz
Catalogue of coastal-based instances with bathymetric and topographic data
Oceanographic monitoring in Hornsund fjord, Svalbard
Salinity and Stratification at the Sea Ice Edge (SASSIE): an oceanographic field campaign in the Beaufort Sea
Weekly green tide mapping in the Yellow Sea with deep learning: integrating optical and synthetic aperture radar ocean imagery
A High Dense Temperature-Salinity Dataset Observed by Automatic Underwater Vehicles toward Mesoscale eddies’ Evolutions and Associated Submesoscale Processes in South China Sea
Probabilistic reconstruction of sea-level changes and their causes since 1900
Global Coastal Characteristics (GCC): a global dataset of geophysical, hydrodynamic, and socioeconomic coastal indicators
Insights from a topo-bathymetric and oceanographic dataset for coastal flooding studies: the French Flooding Prevention Action Program of Saint-Malo
Gap-filling techniques applied to the GOCI-derived daily sea surface salinity product for the Changjiang diluted water front in the East China Sea
A daily reconstructed chlorophyll-a dataset in the South China Sea from MODIS using OI-SwinUnet
Underwater light environment in Arctic fjords
Multiyear surface wave dataset from the subsurface “DeepLev” eastern Levantine moored station
SDUST2020MGCR: a global marine gravity change rate model determined from multi-satellite altimeter data
Lagrangian surface drifter observations in the North Sea: an overview of high-resolution tidal dynamics and surface currents
The physical and biogeochemical parameters along the coastal waters of Saudi Arabia during field surveys in summer, 2021
A Lagrangian coherent eddy atlas for biogeochemical applications in the North Pacific Subtropical Gyre
Global marine gravity gradient tensor inverted from altimetry-derived deflections of the vertical: CUGB2023GRAD
Reconstruction of hourly coastal water levels and counterfactuals without sea level rise for impact attribution
3D reconstruction of horizontal and vertical quasi-geostrophic currents in the North Atlantic Ocean
Laboratory data linking the reconfiguration of and drag on individual plants to the velocity structure and wave dissipation over a meadow of salt marsh plants under waves with and without current
Exploring multi-decadal time series of temperature extremes in Australian coastal waters
Measurements of morphodynamics of a sheltered beach along the Dutch Wadden Sea
Lagoon hydrodynamics of pearl farming islands: the case of Gambier (French Polynesia)
Oceanographic dataset collected during the 2021 scientific expedition of the Canadian Coast Guard Ship Amundsen
Lianjun Yang, Taoyong Jin, and Weiping Jiang
Earth Syst. Sci. Data, 17, 2793–2807, https://doi.org/10.5194/essd-17-2793-2025, https://doi.org/10.5194/essd-17-2793-2025, 2025
Short summary
Short summary
Storm surges (SSs) cause massive loss of life and property in coastal areas each year. High-spatial-resolution and long-term SS records are important for assessing such events. However, tide gauges can provide limited SS information due to sparse and uneven distributions. Based on artificial intelligence technology and tide gauges, a high-spatial-coverage SS dataset was generated for the period from 1940 to 2020, which can provide possible alternative support for deepening our understanding of SSs.
Giuseppe Aulicino, Antonino Ian Ferola, Laura Fortunato, Giorgio Budillon, Pasquale Castagno, Pierpaolo Falco, Giannetta Fusco, Naomi Krauzig, Giancarlo Spezie, Enrico Zambianchi, and Yuri Cotroneo
Earth Syst. Sci. Data, 17, 2625–2640, https://doi.org/10.5194/essd-17-2625-2025, https://doi.org/10.5194/essd-17-2625-2025, 2025
Short summary
Short summary
This study presents 30 years of water temperature data from expendable bathythermograph (XBT) probes collected between Aotearoa / New Zealand and the Ross Sea (Antarctica). Gathered during research cruises by the Italian National Antarctic Research Program, the data were rigorously verified and corrected for depth and temperature bias. This dataset provides a valuable insight into the Southern Ocean's climate and enhances satellite observations and ocean models.
Yihao Wu, Hongkai Shi, Dongzhen Jia, Ole Baltazar Andersen, Xiufeng He, Zhicai Luo, Yu Li, Shiyuan Chen, Xiaohuan Si, Sisu Diao, Yihuang Shi, and Yanglin Chen
Earth Syst. Sci. Data, 17, 2463–2488, https://doi.org/10.5194/essd-17-2463-2025, https://doi.org/10.5194/essd-17-2463-2025, 2025
Short summary
Short summary
We developed a high-quality and cost-effective shallow-water depth model for >120 islands in the South China Sea, using ICESat-2 and Sentinel-2 satellite data. This model maps water depths with an accuracy of ~1 m. Our findings highlight the limitations of existing global bathymetry models in shallow regions. Our model exhibited superior performance in capturing fine-scale bathymetric features with unprecedented spatial resolution, providing essential data for marine applications.
Toan Bui, Ming Feng, and Christopher C. Chapman
Earth Syst. Sci. Data, 17, 1693–1705, https://doi.org/10.5194/essd-17-1693-2025, https://doi.org/10.5194/essd-17-1693-2025, 2025
Short summary
Short summary
Moored time series data are crucial for detecting changes in the ocean. However, mooring losses or instrument failures often result in data gaps. A gap-filled time series dataset of a shelf mooring array off the Western Australian coast is created using a machine learning tool to fill the data gaps. The gap-filled data show consistency with observations and can be used to characterize marine heat waves and cold spells influenced by ocean boundary currents.
Fukai Peng, Xiaoli Deng, Yunzhong Shen, and Xiao Cheng
Earth Syst. Sci. Data, 17, 1441–1460, https://doi.org/10.5194/essd-17-1441-2025, https://doi.org/10.5194/essd-17-1441-2025, 2025
Short summary
Short summary
A new reprocessed altimeter coastal sea level dataset, International Altimetry Service 2024 (IAS2024), for monitoring sea level changes along the world’s coastlines is presented. The evaluation and validation results confirm the reliability of this dataset. The altimeter-based virtual stations along the world’s coastlines can be built using this dataset to monitor the coastal sea level changes where tide gauges are unavailable. Therefore, it is beneficial for both oceanographic communities and policymakers.
Yong Yang, Huaiwei Sun, Jingfeng Wang, Wenxin Zhang, Gang Zhao, Weiguang Wang, Lei Cheng, Lu Chen, Hui Qin, and Zhanzhang Cai
Earth Syst. Sci. Data, 17, 1191–1216, https://doi.org/10.5194/essd-17-1191-2025, https://doi.org/10.5194/essd-17-1191-2025, 2025
Short summary
Short summary
Traditional methods for estimating ocean heat flux often introduce large uncertainties due to complex parameterizations. To tackle this issue, we developed a novel framework based on maximum entropy production (MEP) theory. By incorporating heat storage effects and refining the Bowen ratio, we enhanced the MEP method's accuracy. This research derives a new long-term global ocean latent heat flux dataset that offers high accuracy, enhancing our understanding of ocean energy dynamics.
Paola Emilia Souto-Ceccon, Juan Montes, Enrico Duo, Paolo Ciavola, Tomás Fernández-Montblanc, and Clara Armaroli
Earth Syst. Sci. Data, 17, 1041–1054, https://doi.org/10.5194/essd-17-1041-2025, https://doi.org/10.5194/essd-17-1041-2025, 2025
Short summary
Short summary
This dataset supports the growing need for information on coastal storm impacts. It covers different European countries and is an open-access tool that can be exploited, updated, or complemented by different users and for different purposes. Via labelling with unique identifiers, the database allows for a quick and consistent retrieval of all of the resources associated with a storm event. The adopted approach can be easily exported to all European countries and beyond.
Zaiyang Zhou, Jianzhong Ge, Dirk Sebastiaan van Maren, Hualong Luan, Wenyun Guo, Jianfei Ma, Yingjia Tao, Peng Xu, Fuhai Dao, Wanlun Yang, Keteng Ke, Shenyang Shi, Jingting Zhang, Yu Kuai, Cheng Li, Jinghua Gu, and Pingxing Ding
Earth Syst. Sci. Data, 17, 917–935, https://doi.org/10.5194/essd-17-917-2025, https://doi.org/10.5194/essd-17-917-2025, 2025
Short summary
Short summary
The North Passage (NP) is the primary navigation channel of the Changjiang Estuary, supporting the shipping needs of Shanghai and its surrounding regions. To enhance our understanding of hydrodynamics and sediment dynamics of the NP, a multi-year field observation campaign was designed and conducted from 2015 to 2018. This campaign improves the temporal and spatial coverage compared to previous observations, enabling more detailed investigations of this important channel system.
Manh Cuong Tran, Moninya Roughan, and Amandine Schaeffer
Earth Syst. Sci. Data, 17, 937–963, https://doi.org/10.5194/essd-17-937-2025, https://doi.org/10.5194/essd-17-937-2025, 2025
Short summary
Short summary
The East Australian Current (EAC) plays an important role in the marine ecosystem and climate of the region. To understand the EAC regime and the inner shelf dynamics, we implement a variational approach to produce the first multiyear coastal radar dataset (2012–2023) in this region. The validated data allow for a comprehensive investigation of the EAC dynamics. This dataset will be useful for understanding the complex EAC regime and its far-reaching impacts on the shelf environment.
Ruichen Zhou, Jinyun Guo, Shaoshuai Ya, Heping Sun, and Xin Liu
Earth Syst. Sci. Data, 17, 817–836, https://doi.org/10.5194/essd-17-817-2025, https://doi.org/10.5194/essd-17-817-2025, 2025
Short summary
Short summary
SDUST2023VGGA is a high-resolution (1' × 1') model developed to map the ocean's vertical gradient of gravity anomaly. By using multidirectional mean sea surface data, it reduces the impact of ocean dynamics and provides detailed global gravity anomaly change rates. This model provides critical insights into seafloor structures and ocean mass distribution, contributing to research in marine geophysics and oceanography. The dataset is freely available on Zenodo.
Manuel Bensi, Giuseppe Civitarese, Diego Borme, Carmela Caroppo, Gabriella Caruso, Federica Cerino, Franco Decembrini, Alessandra de Olazabal, Tommaso Diociaiuti, Michele Giani, Vedrana Kovacevic, Martina Kralj, Angelina Lo Giudice, Giovanna Maimone, Marina Monti, Maria Papale, Luisa Patrolecco, Elisa Putelli, Alessandro Ciro Rappazzo, Federica Relitti, Carmen Rizzo, Francesca Spataro, Valentina Tirelli, Clara Turetta, and Maurizio Azzaro
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-37, https://doi.org/10.5194/essd-2025-37, 2025
Revised manuscript accepted for ESSD
Short summary
Short summary
In September 2021, the Italian Arctic Research Programme funded a multidisciplinary study along the 75° N in the Greenland Sea as part of the CASSANDRA project and the Synoptic Arctic Survey programme. The study emphasises the spatial variability of water properties, nutrient distribution and biological communities determined by oceanographic dynamics, in a region influenced by sea ice melting, Atlantic water inflow and climatic teleconnections during a record low summer sea ice extent.
Marina Locritani, Sara Garvani, Giuseppe Manzella, Giancarlo Tamburello, and Antonio Guarnieri
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-53, https://doi.org/10.5194/essd-2025-53, 2025
Revised manuscript accepted for ESSD
Short summary
Short summary
The Histoire Physique de la Mer, written by L.F. Marsili in 1725, was one of the first treatises to analyse the science of the sea. However, it is difficult to understand Marsili's original data. This paper has undertaken a major effort to re-evaluate Marsili's observations, converting historical measurements into modern units: water weight in water density, bathymetric profiles mapping the locations where these measurements were made, and sea level variations, considering the associated error.
Qinwang Xing, Haiqing Yu, Wei Yu, Xinjun Chen, and Hui Wang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-592, https://doi.org/10.5194/essd-2024-592, 2025
Revised manuscript accepted for ESSD
Short summary
Short summary
Ocean fronts play a key role in marine ecosystems and often implicitly exist in satellite observations. This work presents the first publicly available daily global front dataset spanning from 1982 to 2023, with comprehensive validations using in-situ global observations. Our validations enhance confidence in the application of satellite-based front detection and provide independent support for global front occurrence patterns. The dataset is expected to be widely used in front-related studies.
Chao Liu and Lisan Yu
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-14, https://doi.org/10.5194/essd-2025-14, 2025
Revised manuscript accepted for ESSD
Short summary
Short summary
A daily dataset on ocean-surface stress is synthesized for both ice-covered and ice-free Arctic and Antarctic areas. It is based on satellite data on ocean winds, ice movement, and sea surface height. Sensitivity analyses address uncertainties, including variations in sea level products and ice-water drag. The dataset's accuracy is validated against in situ measurements, showing moderate to good agreement on monthly and longer timescales.
Federica Foglini, Marzia Rovere, Renato Tonielli, Giorgio Castellan, Mariacristina Prampolini, Francesca Budillon, Marco Cuffaro, Gabriella Di Martino, Valentina Grande, Sara Innangi, Maria Filomena Loreto, Leonardo Langone, Fantina Madricardo, Alessandra Mercorella, Paolo Montagna, Camilla Palmiotto, Claudio Pellegrini, Antonio Petrizzo, Lorenzo Petracchini, Alessandro Remia, Marco Sacchi, Daphnie Sanchez Galvez, Anna Nora Tassetti, and Fabio Trincardi
Earth Syst. Sci. Data, 17, 181–203, https://doi.org/10.5194/essd-17-181-2025, https://doi.org/10.5194/essd-17-181-2025, 2025
Short summary
Short summary
In 2022, the new CNR research vessel Gaia Blu explored the seabed of the Naples and Pozzuoli gulfs and the Amalfi coastal area (Tyrrhenian Sea, Italy) from 50–2000 m water depth, covering 5000 m2 of seafloor. This paper describes data acquisition and processing and provides maps in unprecedented detail of this area affected by geological changes and human impacts. The findings support future geological and geomorphological investigations and mapping and monitoring of the seafloor and habitats.
Zhongxiang Zhao
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-611, https://doi.org/10.5194/essd-2024-611, 2025
Revised manuscript accepted for ESSD
Short summary
Short summary
Internal tides are generated by barotropic tidal currents flowing over variable topography. They play an important role in a variety of ocean processes such as diapycnal mixing and tracer transport. A global internal tide model is developed using 30 years of satellite altimetry data and a new mapping technique. It decomposes the internal tide field into 60 plane waves at each point, giving numerous long-range beams that contain key information on their generation, propagation, and dissipation.
Yan Wang, Ge Chen, Jie Yang, Zhipeng Gui, and Dehua Peng
Earth Syst. Sci. Data, 16, 5737–5752, https://doi.org/10.5194/essd-16-5737-2024, https://doi.org/10.5194/essd-16-5737-2024, 2024
Short summary
Short summary
Mesoscale eddies are ubiquitous in the ocean and account for 90 % of its kinetic energy, but their generation and dissipation are difficult to observe using current remote sensing technology. Our submesoscale eddy dataset, formed by suppressing large-scale circulation signals and enhancing small-scale chlorophyll structures, has important implications for understanding marine environments and ecosystems, as well as improving climate model predictions.
Han Zhang, Dake Chen, Tongya Liu, Di Tian, Min He, Qi Li, Guofei Wei, and Jian Liu
Earth Syst. Sci. Data, 16, 5665–5679, https://doi.org/10.5194/essd-16-5665-2024, https://doi.org/10.5194/essd-16-5665-2024, 2024
Short summary
Short summary
This paper provides a cross-shaped moored array dataset (MASCS 1.0) of observations that consist of five buoys and four moorings in the northern South China Sea from 2014 to 2015. The moored array is influenced by atmospheric forcings such as tropical cyclones and monsoon as well as oceanic tides and flows. The data reveal variations of the air–sea interface and the ocean itself, which are valuable for studies of air–sea interactions and ocean dynamics in the northern South China Sea.
Simona Simoncelli, Franco Reseghetti, Claudia Fratianni, Lijing Cheng, and Giancarlo Raiteri
Earth Syst. Sci. Data, 16, 5531–5561, https://doi.org/10.5194/essd-16-5531-2024, https://doi.org/10.5194/essd-16-5531-2024, 2024
Short summary
Short summary
This data review is about the reprocessing of historical eXpendable BathyThermograp (XBT) profiles from the Ligurian and Tyrrhenian seas over the time period 1999–2019. A new automated quality control analysis has been performed starting from the original raw data and operational log sheets. The data have been formatted and standardized according to the latest community best practices, and all available metadata have been inserted, including calibration information and uncertainty specification.
Giuseppe Zibordi and Jean-François Berthon
Earth Syst. Sci. Data, 16, 5477–5502, https://doi.org/10.5194/essd-16-5477-2024, https://doi.org/10.5194/essd-16-5477-2024, 2024
Short summary
Short summary
The Coastal Atmosphere and Sea Time Series (CoASTS) and Bio-Optical mapping of Marine Properties (BiOMaP) programs produced bio-optical data supporting satellite ocean color applications across European seas for almost 2 decades. CoASTS and BiOMaP applied equal standardized instruments, measurement methods, quality control schemes and processing codes to ensure temporal and spatial consistency with data products.
Gang Yang, Ke Huang, Lin Zhu, Weiwei Sun, Chao Chen, Xiangchao Meng, Lihua Wang, and Yong Ge
Earth Syst. Sci. Data, 16, 5311–5331, https://doi.org/10.5194/essd-16-5311-2024, https://doi.org/10.5194/essd-16-5311-2024, 2024
Short summary
Short summary
Continuous monitoring of shoreline dynamics is critical to understanding the drivers of shoreline change and evolution. This study uses long-term sequences of Landsat Landsat Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM+), and Operational Land Imager (OLI) images to analyze the spatio-temporal evolution characteristics of the coastlines of Hainan, mainland China, Taiwan, and other countries from 1990 to 2019.
Nicolas Kolodziejczyk, Esther Portela, Virginie Thierry, and Annaig Prigent
Earth Syst. Sci. Data, 16, 5191–5206, https://doi.org/10.5194/essd-16-5191-2024, https://doi.org/10.5194/essd-16-5191-2024, 2024
Short summary
Short summary
Oceanic dissolved oxygen (DO) is fundamental for ocean biogeochemical cycles and marine life. To ease the computation of the ocean oxygen budget from in situ DO data, mapping of data on a regular 3D grid is useful. Here, we present a new DO gridded product from the Argo database. We compare it with existing DO mapping from a historical dataset. We suggest that the ocean has generally been losing oxygen since the 1980s, but large interannual and regional variabilities should be considered.
Xudong Zhang and Xiaofeng Li
Earth Syst. Sci. Data, 16, 5131–5144, https://doi.org/10.5194/essd-16-5131-2024, https://doi.org/10.5194/essd-16-5131-2024, 2024
Short summary
Short summary
Internal wave (IW) is an important ocean process and is frequently observed in the South China Sea (SCS). This study presents a detailed IW dataset for the northern SCS spanning from 2000 to 2022, with a spatial resolution of 250 m, comprising 3085 IW MODIS images. This dataset can enhance understanding of IW dynamics and serve as a valuable resource for studying ocean dynamics, validating numerical models, and advancing AI-driven model building, fostering further exploration into IW phenomena.
Jian Liu, Jingjing Yu, Chuyong Lin, Min He, Haiyan Liu, Wei Wang, and Min Min
Earth Syst. Sci. Data, 16, 4949–4969, https://doi.org/10.5194/essd-16-4949-2024, https://doi.org/10.5194/essd-16-4949-2024, 2024
Short summary
Short summary
The Japanese Himawari-8 and Himawari-9 (H8/9) geostationary (GEO) satellites are strategically positioned over the South China Sea (SCS), spanning from 3 November 2022 to the present. They mainly provide cloud mask, fraction, height, phase, optical, and microphysical property; layered precipitable water; and sea surface temperature products within a temporal resolution of 10 min and a gridded resolution of 0.05° × 0.05°.
Romain Le Gendre, David Varillon, Sylvie Fiat, Régis Hocdé, Antoine De Ramon N'Yeurt, Jérôme Aucan, Sophie Cravatte, Maxime Duphil, Alexandre Ganachaud, Baptiste Gaudron, Elodie Kestenare, Vetea Liao, Bernard Pelletier, Alexandre Peltier, Anne-Lou Schaefer, Thomas Trophime, Simon Van Wynsberge, Yves Dandonneau, Michel Allenbach, and Christophe Menkes
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-394, https://doi.org/10.5194/essd-2024-394, 2024
Revised manuscript accepted for ESSD
Short summary
Short summary
Due to ocean warming, coral reef ecosystems are strongly impacted with dystrophic events and corals experiencing increasing frequencies of bleaching events. In-situ observation remains the best alternative for accurate characterization of trends and extremes in these shallow environments. This paper presents the coastal temperature dataset of the ReefTEMPS monitoring network which spreads over multiple Pacific Island Countries and Territories (PICTS) in the Western and Central South Pacific.
Sarah A. Rautenbach, Carlos Mendes de Sousa, Mafalda Carapuço, and Paulo Relvas
Earth Syst. Sci. Data, 16, 4641–4654, https://doi.org/10.5194/essd-16-4641-2024, https://doi.org/10.5194/essd-16-4641-2024, 2024
Short summary
Short summary
This article presents the data of a 4-month observation of the Iberian Margin Cape St. Vincent ocean observatory, in Portugal (2022), a European Multidisciplinary Seafloor and water column Observatory node. Three instruments at depths between 150 and 200 m collected physical/biogeochemical parameters at different spatial and temporal scales. EMSO-ERIC aims at developing strategies to enable sustainable ocean observation with regards to costs, time, and resolution.
Owein Thuillier, Nicolas Le Josse, Alexandru-Liviu Olteanu, Marc Sevaux, and Hervé Tanguy
Earth Syst. Sci. Data, 16, 4529–4556, https://doi.org/10.5194/essd-16-4529-2024, https://doi.org/10.5194/essd-16-4529-2024, 2024
Short summary
Short summary
Our study unveils a comprehensive catalogue of 17 700 unique coastal digital elevation models (DEMs) derived from the General Bathymetric Chart of the Oceans (GEBCO) as of 2022. These DEMs are designed to support a variety of scientific and educational purposes. Organised into three libraries, they cover a wide range of coastal geometries and different sizes. Data and custom colour palettes for visualisation are made freely available online, promoting open science and collaboration.
Meri Korhonen, Mateusz Moskalik, Oskar Głowacki, and Vineet Jain
Earth Syst. Sci. Data, 16, 4511–4527, https://doi.org/10.5194/essd-16-4511-2024, https://doi.org/10.5194/essd-16-4511-2024, 2024
Short summary
Short summary
Since 2015, temperature and salinity have been monitored in Hornsund fjord (Svalbard), where retreating glaciers add meltwater and terrestrial matter to coastal waters. Therefore, turbidity and water sampling for suspended sediment concentration and sediment deposition are measured. The monitoring spans from May to October, enabling studies on seasonality and its variability over the years, and the dataset covers the whole fjord, including the inner basins in close proximity to the glaciers.
Kyla Drushka, Elizabeth Westbrook, Frederick M. Bingham, Peter Gaube, Suzanne Dickinson, Severine Fournier, Viviane Menezes, Sidharth Misra, Jaynice Pérez Valentín, Edwin J. Rainville, Julian J. Schanze, Carlyn Schmidgall, Andrey Shcherbina, Michael Steele, Jim Thomson, and Seth Zippel
Earth Syst. Sci. Data, 16, 4209–4242, https://doi.org/10.5194/essd-16-4209-2024, https://doi.org/10.5194/essd-16-4209-2024, 2024
Short summary
Short summary
The NASA SASSIE mission aims to understand the role of salinity in modifying sea ice formation in early autumn. The 2022 SASSIE campaign collected measurements of upper-ocean properties, including stratification (layering of the ocean) and air–sea fluxes in the Beaufort Sea. These data are presented here and made publicly available on the NASA Physical Oceanography Distributed Active Archive Center (PO.DAAC), along with code to manipulate the data and generate the figures presented herein.
Le Gao, Yuan Guo, and Xiaofeng Li
Earth Syst. Sci. Data, 16, 4189–4207, https://doi.org/10.5194/essd-16-4189-2024, https://doi.org/10.5194/essd-16-4189-2024, 2024
Short summary
Short summary
Since 2008, the Yellow Sea has faced a significant ecological issue, the green tide, which has become one of the world's largest marine disasters. Satellite remote sensing plays a pivotal role in detecting this phenomenon. This study uses AI-based models to extract the daily green tide from MODIS and SAR images and integrates these daily data to introduce a continuous weekly dataset, which aids research in disaster simulation, forecasting, and prevention.
Chunhua Qiu, Zhenyang Du, Jiancheng Yu, Huabin Mao, Haibo Tang, Zhenhui Yi, Jiawei Qiao, Dongxiao Wang, Xiaoming Zhai, and Yeqiang Shu
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-338, https://doi.org/10.5194/essd-2024-338, 2024
Revised manuscript accepted for ESSD
Short summary
Short summary
The high dense AUVs’ dataset in SCS provides 24498 temperature and salinity profiles and covers 463 days’ experiments, including 83 AUGs’ and 2 AUVs’ experiments. To our knowledge, the resolution and length of this dataset is enough in detecting the asymmetry, vertical tilt, temporal evolution of MEs, and the submesoscale processes. The dataset is expected to improve the accuracy of current and biogeochemistry numerical model. More projects gathering AUVs network will be promoted in future.
Sönke Dangendorf, Qiang Sun, Thomas Wahl, Philip Thompson, Jerry X. Mitrovica, and Ben Hamlington
Earth Syst. Sci. Data, 16, 3471–3494, https://doi.org/10.5194/essd-16-3471-2024, https://doi.org/10.5194/essd-16-3471-2024, 2024
Short summary
Short summary
Sea-level information from the global ocean is sparse in time and space, with comprehensive data being limited to the period since 2005. Here we provide a novel reconstruction of sea level and its contributing causes, as determined by a Kalman smoother approach applied to tide gauge records over the period 1900–2021. The new reconstruction shows a continuing acceleration in global mean sea-level rise since 1970 that is dominated by melting land ice. Contributors vary significantly by region.
Panagiotis Athanasiou, Ap van Dongeren, Maarten Pronk, Alessio Giardino, Michalis Vousdoukas, and Roshanka Ranasinghe
Earth Syst. Sci. Data, 16, 3433–3452, https://doi.org/10.5194/essd-16-3433-2024, https://doi.org/10.5194/essd-16-3433-2024, 2024
Short summary
Short summary
The shape of the coast, the intensity of waves, the height of the water levels, the presence of people or critical infrastructure, and the land use are important information to assess the vulnerability of the coast to coastal hazards. Here, we provide 80 indicators of this kind at consistent locations along the global ice-free coastline using open-access global datasets. These can be valuable for quick assessments of the vulnerability of the coast and at data-poor locations.
Léo Seyfried, Laurie Biscara, Héloïse Michaud, Fabien Leckler, Audrey Pasquet, Marc Pezerat, and Clément Gicquel
Earth Syst. Sci. Data, 16, 3345–3367, https://doi.org/10.5194/essd-16-3345-2024, https://doi.org/10.5194/essd-16-3345-2024, 2024
Short summary
Short summary
In Saint-Malo, France, an initiative to enhance marine submersion prevention began in 2018. Shom conducted an extensive sea campaign, mapping the bay's topography and exploring coastal processes. High-resolution data improve knowledge of the interactions between waves, tide and surge and determine processes responsible for submersion. Beyond science, these findings contribute crucially to a local warning system, providing a tangible solution to protect the community from coastal threats.
Jisun Shin, Dae-Won Kim, So-Hyun Kim, Gi Seop Lee, Boo-Keun Khim, and Young-Heon Jo
Earth Syst. Sci. Data, 16, 3193–3211, https://doi.org/10.5194/essd-16-3193-2024, https://doi.org/10.5194/essd-16-3193-2024, 2024
Short summary
Short summary
We overcame the limitations of satellite and reanalysis sea surface salinity (SSS) datasets and produced a gap-free gridded SSS product with reasonable accuracy and a spatial resolution of 1 km using a machine learning model. Our data enabled the recognition of SSS distribution and movement patterns of the Changjiang diluted water (CDW) front in the East China Sea (ECS) during summer. These results will further advance our understanding and monitoring of long-term SSS variations in the ECS.
Haibin Ye, Chaoyu Yang, Yuan Dong, Shilin Tang, and Chuqun Chen
Earth Syst. Sci. Data, 16, 3125–3147, https://doi.org/10.5194/essd-16-3125-2024, https://doi.org/10.5194/essd-16-3125-2024, 2024
Short summary
Short summary
A deep-learning model for gap-filling based on expected variance was developed. OI-SwinUnet achieves good performance reconstructing chlorophyll-a concentration data on the South China Sea. The reconstructed dataset depicts both the spatiotemporal patterns at the seasonal scale and a fast-change process at the weather scale. Reconstructed data show chlorophyll perturbations of individual eddies at different life stages, giving academics a unique and complete perspective on eddy studies.
Robert W. Schlegel, Rakesh Kumar Singh, Bernard Gentili, Simon Bélanger, Laura Castro de la Guardia, Dorte Krause-Jensen, Cale A. Miller, Mikael Sejr, and Jean-Pierre Gattuso
Earth Syst. Sci. Data, 16, 2773–2788, https://doi.org/10.5194/essd-16-2773-2024, https://doi.org/10.5194/essd-16-2773-2024, 2024
Short summary
Short summary
Fjords play a vital role in the Arctic ecosystems and human communities. It is therefore important to have as clear of an understanding of the processes within these systems as possible. While temperature and salinity tend to be well measured, light is usually not. The dataset described in this paper uses remotely sensed data from 2003 to 2022 to address this problem by providing high-spatial-resolution surface, water column, and seafloor light data for several well-studied Arctic fjords.
Nir Haim, Vika Grigorieva, Rotem Soffer, Boaz Mayzel, Timor Katz, Ronen Alkalay, Eli Biton, Ayah Lazar, Hezi Gildor, Ilana Berman-Frank, Yishai Weinstein, Barak Herut, and Yaron Toledo
Earth Syst. Sci. Data, 16, 2659–2668, https://doi.org/10.5194/essd-16-2659-2024, https://doi.org/10.5194/essd-16-2659-2024, 2024
Short summary
Short summary
This paper outlines the process of creating an open-access surface wave dataset, drawing from deep-sea research station observations located 50 km off the coast of Israel. The discussion covers the wave monitoring procedure, from instrument configuration to wave field retrieval, and aspects of quality assurance. The dataset presented spans over 5 years, offering uncommon in situ wave measurements in the deep sea, and addresses the existing gap in wave information within the region.
Fengshun Zhu, Jinyun Guo, Huiying Zhang, Lingyong Huang, Heping Sun, and Xin Liu
Earth Syst. Sci. Data, 16, 2281–2296, https://doi.org/10.5194/essd-16-2281-2024, https://doi.org/10.5194/essd-16-2281-2024, 2024
Short summary
Short summary
We used multi-satellite altimeter data to construct a high-resolution marine gravity change rate (MGCR) model on 5′×5′ grids, named SDUST2020MGCR. The spatial distribution of SDUST2020MGCR and GRACE MGCR are similar, such as in the eastern seas of Japan (dipole), western seas of the Nicobar Islands (rising), and southern seas of Greenland (falling). The SDUST2020MGCR can provide a detailed view of long-term marine gravity change, which will help to study the seawater mass migration.
Lisa Deyle, Thomas H. Badewien, Oliver Wurl, and Jens Meyerjürgens
Earth Syst. Sci. Data, 16, 2099–2112, https://doi.org/10.5194/essd-16-2099-2024, https://doi.org/10.5194/essd-16-2099-2024, 2024
Short summary
Short summary
A dataset from the North Sea of 85 surface drifters from 2017–2021 is presented. Surface drifters enable the analysis of ocean currents by determining the velocities of surface currents and tidal effects. The entire North Sea has not been studied using drifters before, but the analysis of ocean currents is essential, e.g., to understand the pathways of plastic. The results show that there are strong tidal effects in the shallow North Sea area and strong surface currents in the deep areas.
Yasser O. Abualnaja, Alexandra Pavlidou, James H. Churchill, Ioannis Hatzianestis, Dimitris Velaoras, Harilaos Kontoyiannis, Vassilis P. Papadopoulos, Aristomenis P. Karageorgis, Georgia Assimakopoulou, Helen Kaberi, Theodoros Kannelopoulos, Constantine Parinos, Christina Zeri, Dionysios Ballas, Elli Pitta, Vassiliki Paraskevopoulou, Afroditi Androni, Styliani Chourdaki, Vassileia Fioraki, Stylianos Iliakis, Georgia Kabouri, Angeliki Konstantinopoulou, Georgios Krokos, Dimitra Papageorgiou, Alkiviadis Papageorgiou, Georgios Pappas, Elvira Plakidi, Eleni Rousselaki, Ioanna Stavrakaki, Eleni Tzempelikou, Panagiota Zachioti, Anthi Yfanti, Theodore Zoulias, Abdulah Al Amoudi, Yasser Alshehri, Ahmad Alharbi, Hammad Al Sulami, Taha Boksmati, Rayan Mutwalli, and Ibrahim Hoteit
Earth Syst. Sci. Data, 16, 1703–1731, https://doi.org/10.5194/essd-16-1703-2024, https://doi.org/10.5194/essd-16-1703-2024, 2024
Short summary
Short summary
We present oceanographic measurements obtained during two surveillance cruises conducted in June and September 2021 in the Red Sea and the Arabian Gulf. It is the first multidisciplinary survey within the Saudi Arabian coastal zone, extending from near the Saudi–Jordanian border in the north of the Red Sea to the south close to the Saudi--Yemen border and in the Arabian Gulf. The objective was to record the pollution status along the coastal zone of the kingdom related to specific pressures.
Alexandra E. Jones-Kellett and Michael J. Follows
Earth Syst. Sci. Data, 16, 1475–1501, https://doi.org/10.5194/essd-16-1475-2024, https://doi.org/10.5194/essd-16-1475-2024, 2024
Short summary
Short summary
Ocean eddies can limit horizontal mixing, potentially isolating phytoplankton populations and affecting their concentration. We used two decades of satellite data and computer simulations to identify and track eddy-trapping boundaries in the Pacific Ocean for application in phytoplankton research. Although some eddies trap water masses for months, many continuously mix with surrounding waters. A case study shows how eddy trapping can enhance the signature of a phytoplankton bloom.
Richard Fiifi Annan, Xiaoyun Wan, Ruijie Hao, and Fei Wang
Earth Syst. Sci. Data, 16, 1167–1176, https://doi.org/10.5194/essd-16-1167-2024, https://doi.org/10.5194/essd-16-1167-2024, 2024
Short summary
Short summary
Gravity gradient tensor, a set of six unique gravity signals, is suitable for detecting undersea features. However, due to poor spatial resolution in past years, it has received less research interest and investment. However, current datasets have better accuracy and resolutions, thereby necessitating a revisit. Our analysis shows comparable results with reference models. We conclude that current-generation altimetry datasets can precisely resolve all six gravity gradients.
Simon Treu, Sanne Muis, Sönke Dangendorf, Thomas Wahl, Julius Oelsmann, Stefanie Heinicke, Katja Frieler, and Matthias Mengel
Earth Syst. Sci. Data, 16, 1121–1136, https://doi.org/10.5194/essd-16-1121-2024, https://doi.org/10.5194/essd-16-1121-2024, 2024
Short summary
Short summary
This article describes a reconstruction of monthly coastal water levels from 1900–2015 and hourly data from 1979–2015, both with and without long-term sea level rise. The dataset is based on a combination of three datasets that are focused on different aspects of coastal water levels. Comparison with tide gauge records shows that this combination brings reconstructions closer to the observations compared to the individual datasets.
Sarah Asdar, Daniele Ciani, and Bruno Buongiorno Nardelli
Earth Syst. Sci. Data, 16, 1029–1046, https://doi.org/10.5194/essd-16-1029-2024, https://doi.org/10.5194/essd-16-1029-2024, 2024
Short summary
Short summary
Estimating 3D currents is crucial for the understanding of ocean dynamics, and a precise knowledge of ocean circulation is essential to ensure a sustainable ocean. In this context, a new high-resolution (1 / 10°) data-driven dataset of 3D ocean currents has been developed within the European Space Agency World Ocean Circulation project, providing 10 years (2010–2019) of horizontal and vertical quasi-geostrophic currents at daily resolution over the North Atlantic Ocean, down to 1500 m depth.
Xiaoxia Zhang and Heidi Nepf
Earth Syst. Sci. Data, 16, 1047–1062, https://doi.org/10.5194/essd-16-1047-2024, https://doi.org/10.5194/essd-16-1047-2024, 2024
Short summary
Short summary
This study measured the wave-induced plant drag, flow structure, turbulent intensity, and wave energy attenuation in the presence of a salt marsh. We showed that leaves contribute to most of the total plant drag and wave dissipation. Plant resistance significantly reshapes the velocity profile and enhances turbulence intensity. Adding current obviously impact the plants' wave decay capacity. The dataset can be reused to develop and calibrate marsh-flow theoretical and numerical models.
Michael Hemming, Moninya Roughan, and Amandine Schaeffer
Earth Syst. Sci. Data, 16, 887–901, https://doi.org/10.5194/essd-16-887-2024, https://doi.org/10.5194/essd-16-887-2024, 2024
Short summary
Short summary
We present new datasets that are useful for exploring extreme ocean temperature events in Australian coastal waters. These datasets span multiple decades, starting from the 1940s and 1950s, and include observations from the surface to the bottom at four coastal sites. The datasets provide valuable insights into the intensity, frequency and timing of extreme warm and cold temperature events and include event characteristics such as duration, onset and decline rates and their categorisation.
Marlies A. van der Lugt, Jorn W. Bosma, Matthieu A. de Schipper, Timothy D. Price, Marcel C. G. van Maarseveen, Pieter van der Gaag, Gerben Ruessink, Ad J. H. M. Reniers, and Stefan G. J. Aarninkhof
Earth Syst. Sci. Data, 16, 903–918, https://doi.org/10.5194/essd-16-903-2024, https://doi.org/10.5194/essd-16-903-2024, 2024
Short summary
Short summary
A 6-week field campaign was carried out at a sheltered sandy beach on Texel along the Dutch Wadden Sea with the aim of gaining new insights into the driving processes behind sheltered beach morphodynamics. Detailed measurements of the local hydrodynamics, bed-level changes and sediment composition were collected. The morphological evolution on this sheltered site is the result of the subtle interplay between waves, currents and bed composition.
Oriane Bruyère, Romain Le Gendre, Vetea Liao, and Serge Andréfouët
Earth Syst. Sci. Data, 16, 667–679, https://doi.org/10.5194/essd-16-667-2024, https://doi.org/10.5194/essd-16-667-2024, 2024
Short summary
Short summary
During 2019–2020, the lagoon and forereefs of Gambier Island (French Polynesia) were monitored with oceanographic instruments to measure lagoon hydrodynamics and ocean–lagoon water exchanges. Gambier Island is a key black pearl producer and the study goal was to understand the processes influencing spat collection of pearl oyster Pinctada margaritifera, the species used to produce black pearls. The data set is provided to address local pearl farming questions and other investigations as well.
Tahiana Ratsimbazafy, Thibaud Dezutter, Amélie Desmarais, Daniel Amirault, Pascal Guillot, and Simon Morisset
Earth Syst. Sci. Data, 16, 471–499, https://doi.org/10.5194/essd-16-471-2024, https://doi.org/10.5194/essd-16-471-2024, 2024
Short summary
Short summary
The Canadian Coast Guard Ship has collected oceanographic data across the Canadian Arctic annually since 2003. Such activity aims to support Canadian and international researchers. The ship has several instruments with cutting-edge technology available for research each year during the summer. The data presented here include measurements of physical, chemical and biological variables during the year 2021. Datasets collected from each expedition are available free of charge for the public.
Cited articles
Abraham, J. P. and Cheng, L.: Intersection of Climate Change, Energy, and Adaptation, Energies, 15, 5886, https://doi.org/10.3390/en15165886, 2022.
Abraham, J. P., Baringer, M., Bindoff, N. L., Boyer, T., Cheng, L. J., Church, J. A., Conroy, J. L., Domingues, C. M., Fasullo, J. T., Gilson, J., Goni, G., Good, S. A., Gorman, J. M., Gouretski, V., Ishii, M., Johnson, G. C., Kizu, S., Lyman, J. M., Macdonald, A. M., Minkowycz, W. J., Moffitt, S. E., Palmer, M. D., Piola, A. R., Reseghetti, F., Schuckmann, K., Trenberth, K. E., Velicogna, I., and Willis, J. K.: A review of global ocean temperature observations: Implications for ocean heat content estimates and climate change, Rev. Geophys., 51, 450–483, https://doi.org/10.1002/rog.20022, 2013.
Abraham, J. P., Cheng, L., Mann, M. E., Trenberth, K., and von Schuckmann, K.: The ocean response to climate change guides both adaptation and mitigation efforts, Atmos. Ocean. Sci. Lett., 15, 100221, https://doi.org/10.1016/j.aosl.2022.100221, 2022.
Argo: Argo float data and metadata from Global Data Assembly Centre (Argo GDAC), SEANOE [data set], https://doi.org/10.17882/42182, 2000.
Bagnell, A. and DeVries, T.: 20(th) century cooling of the deep ocean contributed to delayed acceleration of Eart”s energy imbalance, Nat. Commun., 12, 4604, https://doi.org/10.1038/s41467-021-24472-3, 2021.
Barker, P. M. and McDougall, T. J.: Two Interpolation Methods Using Multiply-Rotated Piecewise Cubic Hermite Interpolating Polynomials, J. Atmos. Ocean Technol., 37, 605–619, https://doi.org/10.1175/JTECH-D-19-0211.1, 2020.
Barnoud, A., Pfeffer, J., Guérou, A., Frery, M.-L., Siméon, M., Cazenave, A., Chen, J., Llovel, W., Thierry, V., Legeais, J.-F., and Ablain, M.: Contributions of Altimetry and Argo to Non-Closure of the Global Mean Sea Level Budget Since 2016, Geophys. Res. Lett., 48, e2021GL092824, https://doi.org/10.1029/2021GL092824, 2021.
Barnoud, A., Pfeffer, J., Cazenave, A., Fraudeau, R., Rousseau, V., and Ablain, M.: Revisiting the global mean ocean mass budget over 2005–2020, Ocean Sci., 19, 321–334, https://doi.org/10.5194/os-19-321-2023, 2023.
Bindoff, N. L., Cheung, W. W. L., Kairo, J. G., Arístegui, J., Guinder, V. A., Hallberg, R., Hilmi, N., Jiao, N., and Karim, M. S.: Changing Ocean, Marine Ecosystems, and Dependent Communities, in: IPCC Special Report on the Ocean and Cryosphere in a Changing Climate, edited by: Pörtner, H.-O., Roberts, D. C., Masson-Delmotte, V., Zhai, P., Tignor, M., Poloczanska, E., Mintenbeck, K., Alegría, A., Nicolai, M., Okem, A., Petzold, J., Rama, B., and Weyer, N. M., Cambridge University Press, Cambridge, UK and New York, NY, USA, 447–587, https://doi.org/10.1017/9781009157964.007, 2019.
Boyer, T., Domingues, C. M., Good, S. A., Johnson, G. C., Lyman, J. M., Ishii, M., Gouretski, V., Willis, J. K., Antonov, J., Wijffels, S., Church, J. A., Cowley, R., and Bindoff, N. L.: Sensitivity of Global Upper Ocean Heat Content Estimates to Mapping Methods, XBT Bias Corrections, and Baseline Climatologies, J. Clim., 29, 4817–4842, https://doi.org/10.1175/JCLI-D-15-0801.1, 2016.
Caesar, L., Rahmstorf, S., Robinson, A., Feulner, G., and Saba, V.: Observed fingerprint of a weakening Atlantic Ocean overturning circulation, Nature, 556, 191–196, https://doi.org/10.1038/s41586-018-0006-5, 2018.
Cane, M. A. and Zebiak, S. E.: A theory for El Niño and the southern oscillation, Science, 228, 1085–1087, https://doi.org/10.1126/science.228.4703.1085, 1985.
Cheng, L.: Sensitivity of Ocean Heat Content to Various Instrumental Platforms in Global Ocean Observing System, Ocean-Land-Atmos. Res., 3, 0037, https://doi.org/10.34133/olar.0037, 2024a.
Cheng, L. and Zhu, J.: Uncertainties of the Ocean Heat Content Estimation Induced by Insufficient Vertical Resolution of Historical Ocean Subsurface Observations, J. Atmos. Ocean Technol., 31, 1383–1396, https://doi.org/10.1175/JTECH-D-13-00220.1, 2014.
Cheng, L. and Zhu, J.: Influences of the Choice of Climatology on Ocean Heat Content Estimation, J. Atmos. Ocean Technol., 32, 388–394, https://doi.org/10.1175/JTECH-D-14-00169.1, 2015.
Cheng, L. and Zhu, J.: Benefits of CMIP5 Multimodel Ensemble in Reconstructing Historical Ocean Subsurface Temperature Variations, J. Clim., 29, 5393–5416, https://doi.org/10.1175/JCLI-D-15-0730.1, 2016.
Cheng, L., Zhu, J., Cowley, R., Boyer, T., and Wijffels, S.: Time, Probe Type, and Temperature Variable Bias Corrections to Historical Expendable Bathythermograph Observations, J. Atmos. Ocean. Technol., 31, 1793–1825, https://doi.org/10.1175/jtech-d-13-00197.1, 2014.
Cheng, L., Abraham, J., Goni, G., Boyer, T., Wijffels, S., Cowley, R., Gouretski, V., Reseghetti, F., Kizu, S., Dong, S., Bringas, F., Goes, M., Houpert, L., Sprintall, J., and Zhu, J.: XBT Science: Assessment of Instrumental Biases and Errors, B. Am. Meteorol. Soc., 97, 924–933, https://doi.org/10.1175/BAMS-D-15-00031.1, 2016.
Cheng, L., Trenberth, K. E., Fasullo, J., Boyer, T., Abraham, J., and Zhu, J.: Improved estimates of ocean heat content from 1960 to 2015, Sci. Adv., 3, e1601545, https://doi.org/10.1126/sciadv.1601545, 2017.
Cheng, L., Luo, H., Boyer, T., Cowley, R.. Abraham, J., Gouretski, V., Reseghetti, F., and Zhu, J.: How Well Can We Correct Systematic Errors in Historical XBT Data?, J. Atmos. Ocean. Technol., 35, 1103–1125, https://doi.org/10.1175/JTECH-D-17-0122.1, 2018.
Cheng, L., Trenberth, K. E., Fasullo, J. T., Mayer, M., Balmaseda, M., and Zhu, J.: Evolution of Ocean Heat Content Related to ENSO, J. Clim., 32, 3529–3556, https://doi.org/10.1175/jcli-d-18-0607.1, 2019.
Cheng, L., Trenberth, K. E., Gruber, N., Abraham, J. P., Fasullo, J. T., Li, G., Mann, M. E., Zhao, X., and Zhu, J.: Improved Estimates of Changes in Upper Ocean Salinity and the Hydrological Cycle, J. Clim., 33, 10357–10381, https://doi.org/10.1175/JCLI-D-20-0366.1, 2020.
Cheng, L., von Schuckmann, K., Abraham, J. P., Trenberth, K. E., Mann, M. E., Zanna, L., England, M. H., Zika, J. D., Fasullo, J. T., Yu, Y., Pan, Y., Zhu, J., Newsom, E. R., Bronselaer, B., and Lin, X.: Past and future ocean warming, Nat. Rev. Earth Environ., 3, 776–794, https://doi.org/10.1038/s43017-022-00345-1, 2022a.
Cheng, L., Foster, G., Hausfather, Z., Trenberth, K. E., and Abraham, J.: Improved quantification of the rate of ocean warming, J. Clim., 35, 4827–4840, https://doi.org/10.1175/jcli-d-20-0366.1, 2022b.
Cheng, L., Tan, Z., Pan, Y., Zheng, H., Zhu, Y., Wei, W., Du, J., Li, G., Ye, H., Gourteski, V.: IAP temperature 1° gridded analysis product (IAPv4), CODC [data set], https://doi.org/10.12157/IOCAS.20240117.002, 2024a.
Cheng, L., Tan, Z., Pan, Y., Zheng, H., Zhu, Y., Wei, W., Du, J., Li, G., Ye, H., and Gourteski, V.: IAP global ocean heat content 1° gridded analysis product (IAPv4), CODC [data set], https://doi.org/10.12157/IOCAS.20240117.001, 2024b.
Chu, P. C. and Fan, C.: Global climatological data of ocean thermohaline parameters derived from WOA18, Sci. Data, 10, 408, https://doi.org/10.1038/s41597-023-02308-7, 2023.
Comiso, J. C., Meier, W. N., and Gersten, R.: Variability and trends in the Arctic Sea ice cover: Results from different techniques, J. Geophys. Res.-Ocean., 122, 6883–6900, https://doi.org/10.1002/2017JC012768, 2017.
Cowley, R., Killick, R. E., Boyer, T., Gouretski, V., Reseghetti, F., Kizu, S., Palmer, M. D., Cheng, L., Storto, A., Le Menn, M., Simoncelli, S., Macdonald, A. M., and Domingues, C. M.: International Quality-Controlled Ocean Database (iQuOD) v0.1: The Temperature Uncertainty Specification, Front. Mar. Sci., 8, 689695, https://doi.org/10.3389/fmars.2021.689695, 2021.
Dangendorf, S., Frederikse, T., Chafik, L., Klinck, J. M., Ezer, T., and Hamlington, B. D.: Data-driven reconstruction reveals large-scale ocean circulation control on coastal sea level, Nat. Clim. Change, 11, 514–520, https://doi.org/10.1038/s41558-021-01046-1, 2021.
de Boyer Montégut, C., Madec, G., Fischer, A. S., Lazar, A., and Iudicone, D.: Mixed layer depth over the global ocean: An examination of profile data and a profile-based climatology, J. Geophys. Res.-Ocean., 109, C12003, https://doi.org/10.1029/2004JC002378, 2004.
Desbruyères, D., McDonagh, E. L., King, B. A., and Thierry, V.: Global and full-depth ocean temperature trends during the early twenty-first century from Argo and repeat hydrography, J. Clim., 30, 1985–1997, 2017.
England, M. H., McGregor, S., Spence, P., Meehl, G. A., Timmermann, A., Cai, W., Gupta, A. S., McPhaden, M. J., Purich, A., and Santoso, A.: Recent intensification of wind-driven circulation in the Pacific and the ongoing warming hiatus, Nat. Clim. Change, 4, 222–227, https://doi.org/10.1038/nclimate2106, 2014.
Fasullo, J. T. and Nerem, R. S.: Altimeter-era emergence of the patterns of forced sea-level rise in climate models and implications for the future, P. Natl. Acad. Sci. USA, 115, 12944–12949, https://doi.org/10.1073/pnas.1813233115, 2018.
Frederikse, T., Jevrejeva, S., Riva, R. E. M., and Dangendorf, S.: A Consistent Sea-Level Reconstruction and Its Budget on Basin and Global Scales over 1958–2014, J. Clim., 31, 1267–1280, https://doi.org/10.1175/JCLI-D-17-0502.1, 2018.
Frederikse, T., Landerer, F., Caron, L., Adhikari, S., Parkes, D., Humphrey, V. W., Dangendorf, S., Hogarth, P., Zanna, L., Cheng, L., and Wu, Y.-H.: The causes of sea level rise since 1900, Nature, 584, 393–397, https://doi.org/10.1038/s41586-020-2591-3, 2020 (data set available at https://zenodo.org/records/3862995).
Garcia, H. E., Boyer, T. P., Locarnini, R. A., Baranova, O. K., and Zweng, M. M.: World Ocean Database 2018: User's Manual, T. E. A. V. Mishonov, MD NOAA Atlas NESDIS 87, NOAA, Silver Spring, 2018
Goni, G. J., Sprintall, J., Bringas, F., Cheng, L., Cirano, M., Dong, S., Domingues, R., Goes, M., Lopez, H., Morrow, R., Rivero, U., Rossby, T., Todd, R. E., Trinanes, J., Zilberman, N., Baringer, M., Boyer, T., Cowley, R., Domingues, Hutchinson, K., Kramp, M., Mata, M. M., Reseghetti, F., Sun, C., Bhaskar, T. U., and Volkov, D.: More Than 50 Years of Successful Continuous Temperature Section Measurements by the Global Expendable Bathythermograph Network, Its Integrability, Societal Benefits, and Future, Fron. Mar. Sci., 6, 452, https://doi.org/10.3389/fmars.2019.00452, 2019.
Good, S. A., Martin, M. J., and Rayner, N. A.: EN4: Quality controlled ocean temperature and salinity profiles and monthly objective analyses with uncertainty estimates, J. Geophys. Res.-Ocean., 118, 6704–6716, https://doi.org/10.1002/2013jc009067, 2013 (data set available at https://www.metoffice.gov.uk/hadobs/en4/index.html).
Gouretski, V. and Cheng, L.: Correction for Systematic Errors in the Global Dataset of Temperature Profiles from Mechanical Bathythermographs, J. Atmos. Ocean. Technol., 37, 841–855, https://doi.org/10.1175/jtech-d-19-0205.1, 2020.
Gouretski, V. and Koltermann, K. P.: WOCE global hydrographic climatolog, Berichte BSH, 35, 1–52, 2004.
Gouretski, V. and Koltermann, K. P.: How much is the ocean really warming?, Geophys. Res. Lett., 34, L01610, https://doi.org/10.1029/2006GL027834, 2007.
Gouretski, V. and Reseghetti, F.: On depth and temperature biases in bathythermograph data: Development of a new correction scheme based on analysis of a global ocean database, Deep-Sea Res., 57, 812–833, https://doi.org/10.1016/j.dsr.2010.03.011, 2010.
Gouretski, V., Kennedy, J., Boyer, T., and Köhl, A.: Consistent near-surface ocean warming since 1900 in two largely independent observing networks, Geophys. Res. Lett., 39, L19606, https://doi.org/10.1029/2012GL052975, 2012.
Gouretski, V., Cheng, L., and Boyer, T.: On the Consistency of the Bottle and CTD Profile Data, J. Atmos. Ocean Technol., 39, 1869–1887, https://doi.org/10.1175/JTECH-D-22-0004.1, 2022.
Gouretski, V., Roquet, F., and Cheng, L.: Measurement biases in ocean temperature profiles from marine mammal data loggers, J. Atmos. Ocean Technol., 41, 629–645, https://doi.org/10.1175/JTECH-D-23-0081.1, 2024.
Gulev, S. K., Thorne, P. W., Ahn, J., Dentener, F. J., Domingues, C. M., Gerland, S., Gong, D., Kaufman, D. S., Nnamchi, H. C., Quaas, J., Rivera, J. A., Sathyendranath, S., Smith, S. L., Trewin, B., von Schuckmann, K., and Vose, R. S.: Changing State of the Climate System Supplementary Material, in: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S. L., Péan, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M. I., Huang, M., Leitzell, K., Lonnoy, E., Matthews, J. B. R., Maycock, T. K., Waterfield, T., Yelekçi, O., Yu, R., and Zhou, B., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 287– 422, https://doi.org/10.1017/9781009157896.004, 2021.
Hakuba, M. Z., Frederikse, T., and Landerer, F. W.: Earth's Energy Imbalance From the Ocean Perspective (2005–2019), Geophys. Res. Lett., 48, e2021GL093624, https://doi.org/10.1029/2021GL093624, 2021.
Hansen, J., Sato, M., Kharecha, P., and von Schuckmann, K.: Eart”s energy imbalance and implications, Atmos. Chem. Phys., 11, 13421–13449, https://doi.org/10.5194/acp-11-13421-2011, 2011.
Hirahara, S., Ishii, M., and Fukuda, Y.: Centennial-Scale Sea Surface Temperature Analysis and Its Uncertainty, J. Clim., 27, 57-75, https://doi.org/10.1175/JCLI-D-12-00837.1, 2014 (data set available at https://psl.noaa.gov/data/gridded/data.cobe2.html).
Holte, J., Talley, L. D., Gilson, J., and Roemmich, D.: An Argo mixed layer climatology and database, Geophys. Res. Lett., 44, 5618–5626, https://doi.org/10.1002/2017GL073426, 2017.
Hosoda, S., Ohira, T., and Nakamura, T.: Monthly mean dataset of global oceanic temperature and salinity derived from Argo float observations, JAMSTEC Rep. Res. Dev., 8, 47–59, https://doi.org/10.5918/jamstecr.8.47, 2008.
Huang, B., Thorne, P. W., Banzon, V. F., Boyer, T., Chepurin, G., Lawrimore, J. H., Menne, M. J., Smith, T. M., Vose, R. S., and Zhang, H.-M.: Extended Reconstructed Sea Surface Temperature, Version 5 (ERSSTv5): Upgrades, Validations, and Intercomparisons, J. Clim., 30, 8179–8205, https://doi.org/10.1175/JCLI-D-16-0836.1, 2017 (data set available at https://www1.ncdc.noaa.gov/pub/data/cmb/ersst/v5/netcdf/).
Hugonnet, R., McNabb, R., Berthier, E., Menounos, B., Nuth, C., Girod, L., Farinotti, D., Huss, M., Dussaillant, I., Brun, F., and Kääb, A.: Accelerated global glacier mass loss in the early twenty-first century, Nature, 592, 726–731, https://doi.org/10.1038/s41586-021-03436-z, 2021.
IPCC,: Annex I: Observational Products, edited by: Trewin, B., in: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S. L., Péan, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M. I., Huang, M., Leitzell, K., Lonnoy, E., Matthews, J. B. R., Maycock, T. K., Waterfield, T., Yelekçi, O., Yu, R., and Zhou, B.: Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 2061–2086, https://doi.org/10.1017/9781009157896.015, 2021.
Ishii, M. and Kimoto, M.: Reevaluation of historical ocean heat content variations with time-varying XBT and MBT depth bias corrections, J. Oceanogr., 65, 287–299, https://doi.org/10.1007/s10872-009-0027-7, 2009.
Ishii, M., Shouji, A., Sugimoto, S., and Matsumoto, T.: Objective analyses of sea-surface temperature and marine meteorological variables for the 20th century using ICOADS and the Kobe Collection, Int. J. Climatol., 25, 865–879, https://doi.org/10.1002/joc.1169, 2005.
Ishii, M., Fukuda, Y., Hirahara, S., Yasui, S., Suzuki, T., and, Sato K.: Accuracy of Global Upper Ocean Heat Content Estimation Expected from Present Observational Data Sets, Sola, 13, 163–167, https://doi.org/10.2151/sola.2017-030, 2017 (data set available at https://www.data.jma.go.jp/gmd/kaiyou/english/ohc/ohc_global_en.html).
Jin, F.-F.: An Equatorial Ocean Recharge Paradigm for ENSO, Part I: Conceptual Model, J. Atmos. Sci., 54, 811–829, https://doi.org/10.1175/1520-0469(1997)054<0811:AEORPF>2.0.CO;2, 1997.
Jin, Y., Li, Y., Cheng, L., Duan, J., Li, R., and Wang, F.: Ocean heat content increase of the Maritime Continent since the 1990s, Geophys. Res. Lett., 51, e2023GL107526, https://doi.org/10. 1029/2023GL107526, 2024.
Johns, W. E., Elipot, S., Smeed, D. A., Moat, B., King, B, Volkov, D. L., and Smith, R. H.: Towards two decades of Atlantic Ocean mass and heat transports at 26.5° N, Philos. T. R. Soc. A, 381, 20220188, 2023.
Johnson, G. C., Purkey, S. G., Zilberman, N. V., and Roemmich, D.: Deep Argo Quantifies Bottom Water Warming Rates in the Southwest Pacific Basin, Geophys. Res. Lett., 46, 2662–2669, https://doi.org/10.1098/rsta.2022.0188, 2019.
Katsumata, K., Purkey, S. G., Cowley, R., Sloyan, B. M., Diggs, S. C., Moore, T. S., Talley, L. D., and Swift, J. H.: GO-SHIP Easy Ocean: Gridded ship-based hydrographic section of temperature, salinity, and dissolved oxygen, Sci. Data, 9, 103, https://doi.org/10.1038/s41597-022-01212-w, 2022.
Kennedy, J.: A review of uncertainty in in situ measurements and data sets of sea surface temperature, Rev. Geophys., 52, 1–32, https://doi.org/10.1002/2013RG000434, 2014.
Levitus, S., Antonov, J. I., Boyer, T. P., Locarnini, R. A., Garcia, H. E., and Mishonov, A. V.: Global ocean heat content 1955–2008 in light of recently revealed instrumentation problems. Geophys. Res. Lett., 36, L07608, https://doi.org/10.1029/2008GL037155, 2009.
Levitus, S., Antonov, J. I., Boyer, T. P., Baranova, O. K., Garcia, H. E., Locarnini, R. A., Mishonov, A. V, Reagan, J. R., Seidov, D., Yarosh, E. S., and Zweng, M. M.: World ocean heat content and thermosteric sea level change (0–2000 m), 1955–2010, Geophys. Res. Lett., 39, L10603, https://doi.org/10.1029/2012GL051106, 2012 (data set available at https://www.ncei.noaa.gov/products/).
Li, G., Cheng, L., Zhu, J., Trenberth, K. E., Mann, M. E., and Abraham, J. P.: Increasing ocean stratification over the past half-century, Nat. Clim. Change, 10, 1116–1123, https://doi.org/10.1038/s41558-020-00918-2, 2020.
Li, H., Xu, F., Zhou, W., Wang, D., Wright, J. S., Liu, Z., and Lin, Y.: Development of a global gridded Argo data set with Barnes successive corrections, J. Geophys. Res.-Ocean., 122, 866–889, https://doi.org/10.1002/2016JC012285, 2017 (data set available at https://argo.ucsd.edu/data/argo-data-products/).
Li, Y., Church, J. A., McDougall, T. J., and Barker, P. M.: Sensitivity of Observationally Based Estimates of Ocean Heat Content and Thermal Expansion to Vertical Interpolation Schemes, Geophys. Res. Lett., 49, e2022GL101079, https://doi.org/10.1029/2022GL101079, 2022.
Lian, T., Wang, J., Chen, D., Liu, T., and Wang, D.: A Strong 2023/24 El Niño is Staged by Tropical Pacific Ocean Heat Content Buildup, Ocean-Land-Atmos. Res., 2, 0011, https://doi.org/10.34133/olar.0011, 2023.
Liu, C. and Allan, R.: Reconstructions of the radiation fluxes at the top of atmosphere and net surface energy flux: DEEP-C version 5.0, University of Reading Dataset [data set], https://doi.org/10.17864/1947.000347, 2022.
Liu, C., Allan, R. P., Mayer, M., Hyder, P., Loeb, N. G., Roberts, C. D., Valdivieso, M., Edwards, J. M., and Vidale, P.-L.: Evaluation of satellite and reanalysis-based global net surface energy flux and uncertainty estimates, J. Geophys. Res.- Atmos., 122, 6250–6272, https://doi.org/10.1002/2017JD026616, 2017.
Liu, C., Allan, R. P., Mayer, M., Hyder, P., Desbruyères, D., Cheng, L., Xu, J., Xu, F., and Zhang, Y.: Variability in the global energy budget and transports 1985–2017, Clim. Dynam., 55, 3381–3396, https://doi.org/10.1007/s00382-020-05451-8, 2020.
Loeb, N. G., Wielicki, B. A., Doelling, D. R., Smith, G. L., Keyes, D. F., Kato, S., Manalo-Smith, N., and Wong, T.: Toward Optimal Closure of the Earth's Top-of-Atmosphere Radiation Budget, J. Clim., 22, 748–766, https://doi.org/10.1175/2008JCLI2637.1, 2009.
Loeb, N. G., Thorsen, T. J., Norris, J. R., Wang, H., and Su, W.: Changes in Earth's energy budget during and after the “Pause” in global warming: An observational perspective, Climate, 6, 62, https://doi.org/10.3390/cli6030062, 2018.
Loeb, N. G., Johnson, G. C., Thorsen, T. J., Lyman, J. M., Rose, F. G., and Kato, S.: Satellite and Ocean Data Reveal Marked Increase in Earth's Heating Rate, Geophys. Res. Lett., 48, e2021GL093047, https://doi.org/10.1029/2021gl093047, 2021 (data set available at https://asdc.larc.nasa.gov/project/CERES).
Lyman, J. M. and Johnson, G. C.: Estimating Global Ocean Heat Content Changes in the Upper 1800 m since 1950 and the Influence of Climatology Choice, J. Clim., 27, 1945–1957, https://doi.org/10.1175/JCLI-D-12-00752.1, 2014.
Lyman, J. M. and Johnson, G. C.: Global High-Resolution Random Forest Regression Maps of Ocean Heat Content Anomalies Using In Situ and Satellite Data, J. Atmos. Ocean. Technol., 40, 575–586, https://doi.org/10.1175/JTECH-D-22-0058.1, 2023.
Lyman, J. M., Good, S. A., Gouretski, V. V., Ishii, M., Johnson, G. C., Palmer, M. D., Smith, D. M., and Willis, J. K.: Robust warming of the global upper ocean, Nature, 465, 334–337, https://doi.org/10.1038/nature09043, 2010.
Mann, M. E.: Beyond the Hockey Stick: Climate Lessons from The Common Era, P. Natl. Acad. Sci. USA, 118, e2112797118, https://doi.org/10.1073/pnas.2112797118, 2021.
Mayer, J., Mayer, M., and Haimberger, L.: Consistency and Homogeneity of Atmospheric Energy, Moisture, and Mass Budgets in ERA5, J. Clim., 34, 3955–3974, https://doi.org/10.1175/JCLI-D-20-0676.1, 2021.
Mayer, M., Alonso Balmaseda, M., and Haimberger, L.: Unprecedented 2015/2016 Indo-Pacific Heat Transfer Speeds Up Tropical Pacific Heat Recharge, Geophys. Res. Lett., 45, 3274–3284, https://doi.org/10.1002/2018GL077106, 2018.
Mayer, M., Tietsche, S., Haimberger, L., Tsubouchi, T., Mayer, J., and Zuo, H.: An Improved Estimate of the Coupled Arctic Energy Budget, J. Clim., 32, 7915–7934, https://doi.org/10.1175/JCLI-D-19-0233.1, 2019.
McDougall, T. J. and Barker, P. M.: Getting started with TEOS-10 and the Gibbs Seawater (GSW) Oceanographic Toolbox, 28 pp., SCOR/IAPSO WG127, Intergovernmental Oceanographic Commission, ISBN 978-0-646-55621-5, 2011.
McPhaden, M. J.: A 21st century shift in the relationship between enso sst and warm water volume anomalies, Geophys. Res. Lett., 39, 9706, https://doi.org/10.1029/2012GL051826, 2012.
McMahon, C. R., Roquet, F., Baudel, S., Belbeoch, M., Bestley, S., Blight, C., Boehme, L., Carse, F., Costa, D. P., Fedak, M. A., Guinet, C., Harcourt, R., Heslop, E., Hindell, M. A., Hoenner, X., Holland, K., Holland, M., Jaine, F. R. A., Jeanniard du Dot, T., Jonsen, I., Keates, T. R., Kovacs, K. M., Labrousse, S., Lovell, P., Lydersen, C., March, D., Mazloff, M., McKinzie, M. K., Muelbert, M. M. C., O’Brien, K., Phillips, L., Portela, E., Pye, J., Rintoul, S., Sato, K., Sequeira, A. M. M., Simmons, S. E., Tsontos, V. M., Turpin, V., van Wijk, E., Vo, D., Wege, M., Whoriskey, F. G., Wilson K., and Woodward, B.: Animal Borne Ocean Sensors – AniBOS – An Essential Component of the Global Ocean Observing System, Front. Mar. Sci., 8, 751840, https://doi.org/10.3389/fmars.2021.751840, 2021.
Meyssignac, B., Boyer, T., Zhao, Z., Hakuba, M. Z., Landerer, F. W., Stammer, D., Köhl, A., Kato, S., L'Ecuyer, T., Ablain, M., Abraham, J. P., Blazquez, A., Cazenave, A., Church, J. A., Cowley, R., Cheng, L., Domingues, C. M., Giglio, D., Gouretski, V., Ishii, M., Johnson, G. C., Killick, R. E., Legler, D., Llovel, W., Lyman, J., Palmer, M. D., Piotrowicz, S., Purkey, S. G., Roemmich, D., Roca, R., Savita, A., Schuckmann, K. von, Speich, S., Stephens, G., Wang, G., Wijffels, S. E., and Zilberman, N.: Measuring Global Ocean Heat Content to Es- timate the Earth Energy Imbalance, Front. Mar. Sci., 6, 432, https://doi.org/10.3389/fmars.2019.00432, 2019.
Minière, A., von Schuckmann, K., Sallée, J.-B., and Vogt, L.: Robust acceleration of Earth system heating observed over the past six decades, Sci. Rep., 13, 22975, https://doi.org/10.1038/s41598-023-49353-1, 2024
Nerem, R. S., Beckley, B. D., Fasullo, J. T., Hamlington, B. D., Masters, D., and Mitchum, G. T.: Climate-change–driven accelerated sea-level rise detected in the altimeter era, P. Natl. Acad. Sci. USA, 115, 2022–2025, https://doi.org/10.1073/pnas.1717312115, 2018.
O'Carroll, A. G., Armstrong, E. M., Beggs, H. M., Bouali, M., Casey, K. S., Corlett, G. K., Dash, P., Donlon, C. J., Gentemann, C. L., Høyer, J. L., Ignatov, A., Kabobah, K., Kachi, M., Kurihara, Y., Karagali, I., Maturi, E., Merchant, C. J., Marullo, S., Minnett, P. J., Pennybacker, M., Ramakrishnan, B., Ramsankaran, R. Santoleri, R., Sunder, S., Saux Picart, S. Vázquez-Cuervo, J., and Wimmer, W.: Observational Needs of Sea Surface Temperature, Front. Mar. Sci., 6, 420, https://doi.org/10.3389/fmars.2019.00420, 2019.
Palmer, M. D. and Haines, K.: Estimating Oceanic Heat Content Change Using Isotherms, J. Clim., 22, 4953–4969, https://doi.org/10.1175/2009JCLI2823.1, 2009.
Purkey, S. G. and Johnson, G. C.: Warming of Global Abyssal and Deep Southern Ocean Waters between the 1990s and 2000s: Contributions to Global Heat and Sea Level Rise Budgets, J. Clim., 23, 6336–6351, https://doi.org/10.1175/2010jcli3682.1, 2010.
Rahmstorf, S., Box, J., Feulner, G., Mann, M. E., Robinson, A., Rutherford, S., and Schaffernicht, E.: Exceptional 20th-Century slowdown in Atlantic Ocean overturning, Nat. Clim. Change, 5, 475–480, 2015.
Rayner, N. A., Parker, D. E., Horton, E. B., Folland, C. K., Alexander, L. V., Rowell, D. P., Kent, E. C., and Kaplan, A.: Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century, J. Geophys. Res.-Atmos., 108, 4407, https://doi.org/10.1029/2002JD002670, 2003 (data set available at https://www.metoffice.gov.uk/hadobs/hadisst/).
Reiniger, R. F. and Ross, C. K.: A method of interpolation with application to oceanographic data, Deep-Sea Res., 15, 185–193, https://doi.org/10.1016/0011-7471(68)90040-5, 1968.
Rhein, M., Rintoul, S. R., Aoki, S., Campos, E., Chambers, D., Feely, R. A., Gulev, S., Johnson, G. C., Josey, S. A., Kostianoy, A., Mauritzen, C., Roemmich, D., Talley, L. D., and Wang, F.: Observations: Ocean, in: Climate Change 2013: The Physical Science Basis, Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, https://doi.org/10.1017/CBO9781107415324.010, 2013.
Roemmich, D. and Gilson, J.: The 2004–2008 mean and annual cycle of temperature, salinity, and steric height in the global ocean from the Argo Program, Prog. Oceanogr., 82, 81–100, https://doi.org/10.1016/j.pocean.2009.03.004, 2009 (data set available at http://sio-argo.ucsd.edu/RG_Climatology.html).
Roemmich, D. and Gilson, J.: The global ocean imprint of ENSO, Geophys. Res. Lett., 38, L13606, https://doi.org/10.1029/2011GL047992, 2011.
Roemmich, D., Alford, M. H., Claustre, H., Johnson, K., King, B., Moum, J., Oke, P., Owens, W. B., Pouliquen, S., Purkey, S., Scanderbeg, M., Suga, T., Wijffels, S., Zilberman, N., Bakker, D., Baringer, M., Belbeoch, M., Bittig, H. C., Boss, E., Calil, P., Carse, F., Carval, T., Chai, F., Conchubhair, D. Ó., d’Ortenzio, F., Dall’Olmo, G., Desbruyeres, D., Fennel, K., Fer, I., Ferrari, R., Forget, G., Freeland, H., Fujiki, T., Gehlen, M., Greenan, B., Hallberg, R., Hibiya, T., Hosoda, S., Jayne, S., Jochum, M., Johnson, G. C., Kang, K., Kolodziejczyk, N., Körtzinger, A., L. Traon, P.-Y., Lenn, Y.-D., Maze, G., Mork, K. A., Morris, T., Nagai, T., Nash, J., Garabato, A. N., Olsen, A., Pattabhi, R. R., Prakash, S., Riser, S., Schmechtig, C., Schmid, C., Shroyer, E., Sterl, A., Sutton, P., Talley, L., Tanhua, T., Thierry, V., Thomalla, S., Toole, J., Troisi, A., Trull, T. W., Turton, J., Velez-Belchi, P. J., Walczowski, W., Wang, H., Wanninkhof, R., Waterhouse, A. F., Waterman, S., Watson, A., Wilson, C., Wong, A. P. S., Xu, J., and Yasuda, I.: On the Future of Argo: A Global, Full-Depth, Multi-Disciplinary Array, Front. Mar. Sci., 6, 439, https://doi.org/10.3389/fmars.2019.00439, 2019.
Savita, A., Domingues, C. M., Boyer, T., Gouretski, V., Ishii, M., Johnson, G. C., Lyman, J. M., Willis, J. K., Marsland, S. J., Hobbs, W., Church, J. A., Monselesan, D. P., Dobrohotoff, P., Cowley, R., and Wijffels, S. E.: Quantifying Spread in Spatiotemporal Changes of Upper-Ocean Heat Content Estimates: An Internationally Coordinated Comparison, J. Clim., 35, 851–875, https://doi.org/10.1175/JCLI-D-20-0603.1, 2022.
Schweiger, A., Lindsay, R., Zhang, J., Steele, M., Stern, H., and Kwok, R.: Uncertainty in modeled Arctic sea ice volume, J. Geophys. Res., 116, C00D06, https://doi.org/10.1029/2011JC007084, 2011.
Sloyan, B. M., Wanninkhof, R., Kramp, M., Johnson, G. C., Talley, L. D., Tanhua, T., McDonagh, E., Cusack, C., O'Rourke, E., McGovern, E., Katsumata, K., Diggs, S., Hummon, J., Ishii, M., Azetsu-Scott, K., Boss, E., Ansorge, I., Perez, F. F., Mercier, H., Williams, M. J. M., Anderson, L., Lee, J. H., Murata, A., Kouketsu, S., Jeansson, E., Hoppema, M., and Campos, E.: The Global Ocean Ship-Based Hydrographic Investigations Program (GO-SHIP): A Platform for Integrated Multidisciplinary Ocean Science, Front. Mar. Sci., 6, p. 445, https://doi.org/10.3389/fmars.2019.00445, 2019.
Su, H., Zhang, H., Geng, X., Qin, T., Lu, W., and Yan, X.: OPEN: a new estimation of global ocean heat content for upper 2000 meters from remote sensing data, Remote Sens., 12, 2294, https://doi.org/10.3390/rs12142294, 2020.
Sun, D., Li, F., Jing, Z., Hu, S., and Zhang, B.: Frequent marine heatwaves hidden below the surface of the global ocean, Nat. Geosci., 16, 1099–1104, https://doi.org/10.1038/s41561-023-01325-w, 2023.
Tan, Z., Zhang, B., Wu, X., Dong, M., and Cheng, L.: Quality control for ocean observations: From present to future, Sci. China Earth Sci., 65, 215–233, https://doi.org/10.1007/s11430-021-9846-7, 2022.
Tan, Z., Cheng, L., Gouretski, V., Zhang, B., Wang, Y., Li, F., Liu, Z., and Zhu, J.: A new automatic quality control system for ocean profile observations and impact on ocean warming estimate, Deep-Sea Res. Pt. I, 194, 103961, https://doi.org/10.1016/j.dsr.2022.103961, 2023.
Trenberth, K. E.: The Changing Flow of Energy Through the Climate System, Cambridge University Press, https://doi.org/10.1017/9781108979030, 2022.
Trenberth, K. E. and Fasullo, J. T.: Atlantic meridional heat transports computed from balancing Earth's energy locally, Geophys. Res. Lett., 44, 1919–1927, https://doi.org/10.1002/2016gl072475, 2017.
Trenberth, K. E., Fasullo, J. T., and Kiehl, J.: Earth's Global Energy Budget, Bull. Am. Meteorol. Soc., 90, 311–324, https://doi.org/10.1175/2008bams2634.1, 2009.
Trenberth, K. E., Fasullo, J. T., Von Schuckmann, K., and Cheng, L.: Insights into Earth's Energy Imbalance from Multiple Sources, J. Clim., 29, 7495–7505, https://doi.org/10.1175/jcli-d-16-0339.1, 2016.
Trenberth, K. E., Zhang, Y., Fasullo, J. T., and Cheng, L.: Observation-Based Estimates of Global and Basin Ocean Meridional Heat Transport Time Series, J. Clim., 32, 4567–4583, https://doi.org/10.1175/jcli-d-18-0872.1, 2019.
Thresher, A., Cowley, R., and Wijffels, S.: QuOTA dataset (Quality-controlled Ocean Temperature Archive), Commonwealth Scientific and Industrial Research Organisation (CSIRO) [data set], https://doi.org/10.25919/5ec357563bd3e, 2008.
von Schuckmann, K. and Le Traon, P. Y.: How well can we derive Global Ocean Indicators from Argo data?, Ocean Sci., 7, 783–791, https://doi.org/10.5194/os-7-783-2011, 2011.
von Schuckmann, K., Cheng, L., Palmer, M. D., Hansen, J., Tassone, C., Aich, V., Adusumilli, S., Beltrami, H., Boyer, T., Cuesta-Valero, F. J., Desbruyères, D., Domingues, C., García-García, A., Gentine, P., Gilson, J., Gorfer, M., Haim- berger, L., Ishii, M., Johnson, G. C., Killick, R., King, B. A., Kirchengast, G., Kolodziejczyk, N., Lyman, J., Marzeion, B., Mayer, M., Monier, M., Monselesan, D. P., Purkey, S., Roemmich, D., Schweiger, A., Seneviratne, S. I., Shepherd, A., Slater, D. A., Steiner, A. K., Straneo, F., Timmermans, M.-L., and Wijffels, S. E.: Heat stored in the Earth system: where does the energy go?, Earth Syst. Sci. Data, 12, 2013–2041, https://doi.org/10.5194/essd-12-2013-2020, 2020.
von Schuckmann, K., Palmer, M. D., Trenberth, K. E., Cazenave, A., Chambers, D., Champollion, N., Hansen, J., Josey, S. A., Loeb, N., Mathieu, P.-P., Meyssignac, B., and Wild, M.: An imperative to monitor Earth's energy imbalance, Nat. Clim. Change, 6, 138–144, https://doi.org/10.1038/nclimate2876, 2016.
von Schuckmann, K., Minière, A., Gues, F., Cuesta-Valero, F. J., Kirchengast, G., Adusumilli, S., Straneo, F., Allan, R., Barker, P. M., Beltrami, H., Boyer, T., Cheng, L., Church, J., Desbruyeres, D., Dolman, H., Domingues, C., García-García, A., Giglio, D., Gilson, J., Gorfer, M., Haimberger, L., Hendricks, S., Hosoda, S., Johnson, G. C., Killick, R., King, B. A., Kolodziejczyk, N., Korosov, A., Krinner, G., Kuusela, M., Langer, M., Lavergne, T., Li, Y., Lyman, J., Marzeion, B., Mayer, M., MacDougall, A., Lawrence, I., McDougall, T., Monselesan, D. P., Nitzbon, J., Otosaka, I., Peng, J., Purkey, S., Roemmich, D., Sato, K., Sato, K., Savita, A., Schweiger, A., Shepherd, A., Seneviratne, S. I., Simons, L., Slater, D. A., Slater, T., Smith, N., Steiner, A. K., Suga, T., Szekely, T., Thiery, W., Timmermanns, M.-L., Vanderkelen, I., Wijffels, S. E., Wu, T., and Zemp, M.: Heat stored in the Earth system 1960–2020: Where does the energy go?, World Data Center for Climate (WDCC) at DKRZ [data set], https://hdl.handle.net/21.14106/279f535efb48324f4f604bb390f74deadf268812, 2022.
von Schuckmann, K., Minière, A., Gues, F., Cuesta-Valero, F. J., Kirchengast, G., Adusumilli, S., Straneo, F., Ablain, M., Allan, R. P., Barker, P. M., Beltrami, H., Blazquez, A., Boyer, T., Cheng, L., Church, J., Desbruyeres, D., Dolman, H., Domingues, C. M., García-García, A., Giglio, D., Gilson, J. E., Gorfer, M., Haimberger, L., Hakuba, M. Z., Hendricks, S., Hosoda, S., Johnson, G. C., Killick, R., King, B., Kolodziejczyk, N., Korosov, A., Krinner, G., Kuusela, M., Landerer, F. W., Langer, M., Lavergne, T., Lawrence, I., Li, Y., Lyman, J., Marti, F., Marzeion, B., Mayer, M., MacDougall, A. H., McDougall, T., Monselesan, D. P., Nitzbon, J., Otosaka, I., Peng, J., Purkey, S., Roemmich, D., Sato, K., Sato, K., Savita, A., Schweiger, A., Shepherd, A., Seneviratne, S. I., Simons, L., Slater, D. A., Slater, T., Steiner, A. K., Suga, T., Szekely, T., Thiery, W., Timmermans, M. L., Vanderkelen, I., Wjiffels, S. E., Wu, T., and Zemp, M.: Heat stored in the Earth system 1960–2020: where does the energy go?, Earth Syst. Sci. Data, 15, 1675–1709, https://doi.org/10.5194/essd-15-1675-2023, 2023.
Wang, F., Shen, Y., Chen, Q., and Sun, Y.: Reduced misclosure of global sea-level budget with updated Tongji-Grace2018 solution, Sci. Rep.-UK, 11, 17667, https://doi.org/10.1038/s41598-021-96880-w, 2021.
Watkins, M. M., Wiese, D. N., Yuan, D. N., Boening, C., and Landerer, F. W.: Improved methods for observing Earth's time variable mass distribution with GRACE using spherical cap mascons, J. Geophys. Res.-Sol. Ea., 120, 2648–2671, https://doi.org/10.1002/2014JB011547, 2015 (data set available at https://grace.jpl.nasa.gov/data/get-data/jpl_global_mascons/).
Wijffels, S. E., Willis, J., Domingues, C. M., Barker, P., White, N. J., Gronell, A., Ridgway, K., and Church, J. A.: Changing Expendable Bathythermograph Fall Rates and Their Impact on Estimates of Thermosteric Sea Level Rise, J. Clim., 21, 5657–5672, https://doi.org/10.1175/2008jcli2290.1, 2008.
WMO: State of the Global Climate 2021, WMO-No. 1290, ISBN: 978-92-63-11290-3, 2022.
Wong, A. P. S., Wijffels, S. E., Riser, S. C., Pouliquen, S., Hosoda, S., Roemmich, D., Gilson, J., Johnson, G. C., Martini, K., Murphy, D. J., Scanderbeg, M., Bhaskar, T. V. S. U., Buck, J. J. H., Merceur, F., Carval, T., Maze, G., Cabanes, C., André, X., Poffa, N., Yashayaev, I., Barker, P. M., Guinehut, S., Belbéoch, M., Ignaszewski, M., Baringer, M. O. N., Schmid, C., Lyman, J. M., McTaggart, K. E., Purkey, S. G., Zilberman, N., Alkire, M. B., Swift, D., Owens, W. B., Jayne, S. R., Hersh, C., Robbins, P., West-Mack, D., Bahr, F., Yoshida, S., Sutton, P. J. H., Cancouët, R., Coatanoan, C., Dobbler, D., Juan, A. G., Gourrion, J., Kolodziejczyk, N., Bernard, V., Bourlès, B., Claustre, H., D'Ortenzio, F., Le Reste, S., Le Traon, P.-Y., Rannou, J.-P., Saout-Grit, C., Speich, S., Thierry, V., Verbrugge, N., Angel-Benavides, I. M., Klein, B., Notarstefano, G., Poulain, P.-M., Vélez-Belchí, P., Suga, T., Ando, K., Iwasaska, N., Kobayashi, T., Masuda, S., Oka, E., Sato, K., Nakamura, T., Sato, K., Takatsuki, Y., Yoshida, T., Cowley, R., Lovell, J. L., Oke, P. R., van Wijk, E. M., Carse, F., Donnelly, M., Gould, W. J., Gowers, K., King, B. A., Loch, S. G., Mowat, M., Turton, J., Rama Rao, E. P., Ravichandran, M., Freeland, H. J., Gaboury, I., Gilbert, D., Greenan, B. J. W., Ouellet, M., Ross, T., Tran, A., Dong, M., Liu, Z., Xu, J., Kang, K., Jo, H., Kim, S.-D., and Park, H.-M.: Argo Data 1999–2019: Two Million Temperature-Salinity Profiles and Subsurface Velocity Observations From a Global Array of Profiling Floats, Front. Mar. Sci., 7, 700, https://doi.org/10.3389/fmars.2020.00700, 2020.
Yashayaev, I.: Hydrographic changes in the Labrador Sea 1960–2005, Prog. Oceanogr., 73, 242–276, https://doi.org/10.1016/j.pocean.2007.04.015, 2007.
Yashayaev, I. and Loder, J. W.: Further intensification of deep convection in the Labrador Sea in 2016, Geophys. Res. Lett., 44, 1429–1438, https://doi.org/10.1002/2016GL071668, 2017.
Zanna, L., Khatiwala, S., Gregory, J. M., Ison, J., and Heimbach, P.: Global reconstruction of historical ocean heat storage and transport, P. Natl. Acad. Sci. USA, 116, 1126–1131, https://doi.org/10.1073/pnas.1808838115, 2019.
Zhang, B., Cheng, L., Tan, Z., Gouretski, V., Li, F., Pan, Y., Yuan, H., Ren, H., Reseghetti, F., Zhu, J., and Wang, F.: CAS-Ocean Data Center, Global Ocean Science Database (CODCv1): temperature, Marine Science Data Center of the Chinese Academy of Science, https://doi.org/10.12157/IOCAS.20230525.001, 2024a.
Zhang, B., Cheng, L., Tan, Z. Gouretski, V., Li, F., Pan, Y., Yuan, H., Ren, H., Reseghetti, F., Zhu, J., and Wang, F.: CODC-v1: a quality-controlled and bias-corrected ocean temperature profile database from 1940–2023, Sci. Data, 11, 666, https://doi.org/10.1038/s41597-024-03494-8, 2024b.
Zhang, J. and Rothrock, D. A.: Modeling Global Sea Ice with a Thickness and Enthalpy Distribution Model in Generalized Curvilinear Coordinates, Mon. Weather Rev., 131, 845–861, https://doi.org/10.1175/1520-0493(2003)131<0845:MGSIWA>2.0.CO;2, 2003.
Zhang, X., Church, J. A., Platten, S. M., and Monselesan, D.: Projection of subtropical gyre circulation and associated sea level changes in the Pacific based on CMIP3 climate models, Clim. Dynam., 43, 131–144, https://doi.org/10.1007/s00382-013-1902-x, 2014.
Short summary
Observational gridded products are essential for understanding the ocean, the atmosphere, and climate change; they support policy decisions and socioeconomic developments. This study provides an update of an ocean subsurface temperature and ocean heat content gridded product, named the IAPv4 data product, which is available for the upper 6000 m (119 levels) since 1940 (more reliable after ~1955) for monthly and 1° × 1° temporal and spatial resolutions.
Observational gridded products are essential for understanding the ocean, the atmosphere, and...
Altmetrics
Final-revised paper
Preprint