Articles | Volume 18, issue 18
https://doi.org/10.5194/gmd-18-6255-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-18-6255-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
ROMSOC: a regional atmosphere–ocean coupled model for CPU–GPU hybrid system architectures
Gesa K. Eirund
CORRESPONDING AUTHOR
Environmental Physics, Institute of Biogeochemistry and Pollutant Dynamics, Zurich, ETH Zurich, Switzerland
Matthieu Leclair
Center for Climate Systems Modeling (C2SM), Zurich, ETH Zurich, Switzerland
Matthias Muennich
Environmental Physics, Institute of Biogeochemistry and Pollutant Dynamics, Zurich, ETH Zurich, Switzerland
Nicolas Gruber
Environmental Physics, Institute of Biogeochemistry and Pollutant Dynamics, Zurich, ETH Zurich, Switzerland
Center for Climate Systems Modeling (C2SM), Zurich, ETH Zurich, Switzerland
Related authors
Victoria M. Bauer, Sebastian Schemm, Raphael Portmann, Jingzhi Zhang, Gesa K. Eirund, Steven J. De Hertog, and Jan Zibell
Earth Syst. Dynam., 16, 379–409, https://doi.org/10.5194/esd-16-379-2025, https://doi.org/10.5194/esd-16-379-2025, 2025
Short summary
Short summary
Past research has shown that the North Atlantic Ocean circulation reacts strongly to global forest cover changes. Using Earth system model simulations featuring idealised forestation and deforestation of North America, this study shows that the North Atlantic Ocean is highly sensitive to upstream land cover changes. Anomalies in air temperature over land propagate downstream and modify ocean-to-atmosphere heat fluxes over the North Atlantic through altering the cold-air outbreak frequency.
Li-Qing Jiang, Amanda Fay, Jens Daniel Müller, Lydia Keppler, Dustin Carroll, Siv K. Lauvset, Tim DeVries, Judith Hauck, Christian Rödenbeck, Luke Gregor, Nicolas Metzl, Andrea J. Fassbender, Jean-Pierre Gattuso, Peter Landschützer, Rik Wanninkhof, Christopher Sabine, Simone R. Alin, Mario Hoppema, Are Olsen, Matthew P. Humphreys, Kumiko Azetsu-Scott, Dorothee C. E. Bakker, Leticia Barbero, Nicholas R. Bates, Nicole Besemer, Henry C. Bittig, Albert E. Boyd, Daniel Broullón, Wei-Jun Cai, Brendan R. Carter, Thi-Tuyet-Trang Chau, Chen-Tung Arthur Chen, Frédéric Cyr, John E. Dore, Ian Enochs, Richard A. Feely, Hernan E. Garcia, Marion Gehlen, Lucas Gloege, Melchor González-Dávila, Nicolas Gruber, Yosuke Iida, Masao Ishii, Esther Kennedy, Alex Kozyr, Nico Lange, Claire Lo Monaco, Derek P. Manzello, Galen A. McKinley, Natalie M. Monacci, Xose A. Padin, Ana M. Palacio-Castro, Fiz F. Pérez, Alizée Roobaert, J. Magdalena Santana-Casiano, Jonathan Sharp, Adrienne Sutton, Jim Swift, Toste Tanhua, Maciej Telszewski, Jens Terhaar, Ruben van Hooidonk, Anton Velo, Andrew J. Watson, Angelicque E. White, Zelun Wu, Hyelim Yoo, and Jiye Zeng
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-255, https://doi.org/10.5194/essd-2025-255, 2025
Preprint under review for ESSD
Short summary
Short summary
This review article provides an overview of 60 existing ocean carbonate chemistry data products, encompassing a broad range of types, including compilations of cruise datasets, gap-filled observational products, model simulations, and more. It is designed to help researchers identify and access the data products that best support their scientific objectives, thereby facilitating progress in understanding the ocean's changing carbonate chemistry.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Hongmei Li, Ingrid T. Luijkx, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Almut Arneth, Vivek Arora, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Carla F. Berghoff, Henry C. Bittig, Laurent Bopp, Patricia Cadule, Katie Campbell, Matthew A. Chamberlain, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Thomas Colligan, Jeanne Decayeux, Laique M. Djeutchouang, Xinyu Dou, Carolina Duran Rojas, Kazutaka Enyo, Wiley Evans, Amanda R. Fay, Richard A. Feely, Daniel J. Ford, Adrianna Foster, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Jens Heinke, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Andrew R. Jacobson, Atul K. Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Zhe Jin, Etsushi Kato, Ralph F. Keeling, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Xin Lan, Siv K. Lauvset, Nathalie Lefèvre, Zhu Liu, Junjie Liu, Lei Ma, Shamil Maksyutov, Gregg Marland, Nicolas Mayot, Patrick C. McGuire, Nicolas Metzl, Natalie M. Monacci, Eric J. Morgan, Shin-Ichiro Nakaoka, Craig Neill, Yosuke Niwa, Tobias Nützel, Lea Olivier, Tsuneo Ono, Paul I. Palmer, Denis Pierrot, Zhangcai Qin, Laure Resplandy, Alizée Roobaert, Thais M. Rosan, Christian Rödenbeck, Jörg Schwinger, T. Luke Smallman, Stephen M. Smith, Reinel Sospedra-Alfonso, Tobias Steinhoff, Qing Sun, Adrienne J. Sutton, Roland Séférian, Shintaro Takao, Hiroaki Tatebe, Hanqin Tian, Bronte Tilbrook, Olivier Torres, Etienne Tourigny, Hiroyuki Tsujino, Francesco Tubiello, Guido van der Werf, Rik Wanninkhof, Xuhui Wang, Dongxu Yang, Xiaojuan Yang, Zhen Yu, Wenping Yuan, Xu Yue, Sönke Zaehle, Ning Zeng, and Jiye Zeng
Earth Syst. Sci. Data, 17, 965–1039, https://doi.org/10.5194/essd-17-965-2025, https://doi.org/10.5194/essd-17-965-2025, 2025
Short summary
Short summary
The Global Carbon Budget 2024 describes the methodology, main results, and datasets used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land ecosystems, and the ocean over the historical period (1750–2024). These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Victoria M. Bauer, Sebastian Schemm, Raphael Portmann, Jingzhi Zhang, Gesa K. Eirund, Steven J. De Hertog, and Jan Zibell
Earth Syst. Dynam., 16, 379–409, https://doi.org/10.5194/esd-16-379-2025, https://doi.org/10.5194/esd-16-379-2025, 2025
Short summary
Short summary
Past research has shown that the North Atlantic Ocean circulation reacts strongly to global forest cover changes. Using Earth system model simulations featuring idealised forestation and deforestation of North America, this study shows that the North Atlantic Ocean is highly sensitive to upstream land cover changes. Anomalies in air temperature over land propagate downstream and modify ocean-to-atmosphere heat fluxes over the North Atlantic through altering the cold-air outbreak frequency.
Bjorn Stevens, Stefan Adami, Tariq Ali, Hartwig Anzt, Zafer Aslan, Sabine Attinger, Jaana Bäck, Johanna Baehr, Peter Bauer, Natacha Bernier, Bob Bishop, Hendryk Bockelmann, Sandrine Bony, Guy Brasseur, David N. Bresch, Sean Breyer, Gilbert Brunet, Pier Luigi Buttigieg, Junji Cao, Christelle Castet, Yafang Cheng, Ayantika Dey Choudhury, Deborah Coen, Susanne Crewell, Atish Dabholkar, Qing Dai, Francisco Doblas-Reyes, Dale Durran, Ayoub El Gaidi, Charlie Ewen, Eleftheria Exarchou, Veronika Eyring, Florencia Falkinhoff, David Farrell, Piers M. Forster, Ariane Frassoni, Claudia Frauen, Oliver Fuhrer, Shahzad Gani, Edwin Gerber, Debra Goldfarb, Jens Grieger, Nicolas Gruber, Wilco Hazeleger, Rolf Herken, Chris Hewitt, Torsten Hoefler, Huang-Hsiung Hsu, Daniela Jacob, Alexandra Jahn, Christian Jakob, Thomas Jung, Christopher Kadow, In-Sik Kang, Sarah Kang, Karthik Kashinath, Katharina Kleinen-von Königslöw, Daniel Klocke, Uta Kloenne, Milan Klöwer, Chihiro Kodama, Stefan Kollet, Tobias Kölling, Jenni Kontkanen, Steve Kopp, Michal Koran, Markku Kulmala, Hanna Lappalainen, Fakhria Latifi, Bryan Lawrence, June Yi Lee, Quentin Lejeun, Christian Lessig, Chao Li, Thomas Lippert, Jürg Luterbacher, Pekka Manninen, Jochem Marotzke, Satoshi Matsouoka, Charlotte Merchant, Peter Messmer, Gero Michel, Kristel Michielsen, Tomoki Miyakawa, Jens Müller, Ramsha Munir, Sandeep Narayanasetti, Ousmane Ndiaye, Carlos Nobre, Achim Oberg, Riko Oki, Tuba Özkan-Haller, Tim Palmer, Stan Posey, Andreas Prein, Odessa Primus, Mike Pritchard, Julie Pullen, Dian Putrasahan, Johannes Quaas, Krishnan Raghavan, Venkatachalam Ramaswamy, Markus Rapp, Florian Rauser, Markus Reichstein, Aromar Revi, Sonakshi Saluja, Masaki Satoh, Vera Schemann, Sebastian Schemm, Christina Schnadt Poberaj, Thomas Schulthess, Cath Senior, Jagadish Shukla, Manmeet Singh, Julia Slingo, Adam Sobel, Silvina Solman, Jenna Spitzer, Philip Stier, Thomas Stocker, Sarah Strock, Hang Su, Petteri Taalas, John Taylor, Susann Tegtmeier, Georg Teutsch, Adrian Tompkins, Uwe Ulbrich, Pier-Luigi Vidale, Chien-Ming Wu, Hao Xu, Najibullah Zaki, Laure Zanna, Tianjun Zhou, and Florian Ziemen
Earth Syst. Sci. Data, 16, 2113–2122, https://doi.org/10.5194/essd-16-2113-2024, https://doi.org/10.5194/essd-16-2113-2024, 2024
Short summary
Short summary
To manage Earth in the Anthropocene, new tools, new institutions, and new forms of international cooperation will be required. Earth Virtualization Engines is proposed as an international federation of centers of excellence to empower all people to respond to the immense and urgent challenges posed by climate change.
Flora Desmet, Matthias Münnich, and Nicolas Gruber
Biogeosciences, 20, 5151–5175, https://doi.org/10.5194/bg-20-5151-2023, https://doi.org/10.5194/bg-20-5151-2023, 2023
Short summary
Short summary
Ocean acidity extremes in the upper 250 m depth of the northeastern Pacific rapidly increase with atmospheric CO2 rise, which is worrisome for marine organisms that rapidly experience pH levels outside their local environmental conditions. Presented research shows the spatiotemporal heterogeneity in this increase between regions and depths. In particular, the subsurface increase is substantially slowed down by the presence of mesoscale eddies, often not resolved in Earth system models.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Ingrid T. Luijkx, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Peter Anthoni, Leticia Barbero, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Bertrand Decharme, Laurent Bopp, Ida Bagus Mandhara Brasika, Patricia Cadule, Matthew A. Chamberlain, Naveen Chandra, Thi-Tuyet-Trang Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Xinyu Dou, Kazutaka Enyo, Wiley Evans, Stefanie Falk, Richard A. Feely, Liang Feng, Daniel J. Ford, Thomas Gasser, Josefine Ghattas, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Jens Heinke, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Andrew R. Jacobson, Atul Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Zhe Jin, Fortunat Joos, Etsushi Kato, Ralph F. Keeling, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Xin Lan, Nathalie Lefèvre, Hongmei Li, Junjie Liu, Zhiqiang Liu, Lei Ma, Greg Marland, Nicolas Mayot, Patrick C. McGuire, Galen A. McKinley, Gesa Meyer, Eric J. Morgan, David R. Munro, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin M. O'Brien, Are Olsen, Abdirahman M. Omar, Tsuneo Ono, Melf Paulsen, Denis Pierrot, Katie Pocock, Benjamin Poulter, Carter M. Powis, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Roland Séférian, T. Luke Smallman, Stephen M. Smith, Reinel Sospedra-Alfonso, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Shintaro Takao, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Guido R. van der Werf, Erik van Ooijen, Rik Wanninkhof, Michio Watanabe, Cathy Wimart-Rousseau, Dongxu Yang, Xiaojuan Yang, Wenping Yuan, Xu Yue, Sönke Zaehle, Jiye Zeng, and Bo Zheng
Earth Syst. Sci. Data, 15, 5301–5369, https://doi.org/10.5194/essd-15-5301-2023, https://doi.org/10.5194/essd-15-5301-2023, 2023
Short summary
Short summary
The Global Carbon Budget 2023 describes the methodology, main results, and data sets used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land ecosystems, and the ocean over the historical period (1750–2023). These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Christoph Heinze, Thorsten Blenckner, Peter Brown, Friederike Fröb, Anne Morée, Adrian L. New, Cara Nissen, Stefanie Rynders, Isabel Seguro, Yevgeny Aksenov, Yuri Artioli, Timothée Bourgeois, Friedrich Burger, Jonathan Buzan, B. B. Cael, Veli Çağlar Yumruktepe, Melissa Chierici, Christopher Danek, Ulf Dieckmann, Agneta Fransson, Thomas Frölicher, Giovanni Galli, Marion Gehlen, Aridane G. González, Melchor Gonzalez-Davila, Nicolas Gruber, Örjan Gustafsson, Judith Hauck, Mikko Heino, Stephanie Henson, Jenny Hieronymus, I. Emma Huertas, Fatma Jebri, Aurich Jeltsch-Thömmes, Fortunat Joos, Jaideep Joshi, Stephen Kelly, Nandini Menon, Precious Mongwe, Laurent Oziel, Sólveig Ólafsdottir, Julien Palmieri, Fiz F. Pérez, Rajamohanan Pillai Ranith, Juliano Ramanantsoa, Tilla Roy, Dagmara Rusiecka, J. Magdalena Santana Casiano, Yeray Santana-Falcón, Jörg Schwinger, Roland Séférian, Miriam Seifert, Anna Shchiptsova, Bablu Sinha, Christopher Somes, Reiner Steinfeldt, Dandan Tao, Jerry Tjiputra, Adam Ulfsbo, Christoph Völker, Tsuyoshi Wakamatsu, and Ying Ye
Biogeosciences Discuss., https://doi.org/10.5194/bg-2023-182, https://doi.org/10.5194/bg-2023-182, 2023
Revised manuscript not accepted
Short summary
Short summary
For assessing the consequences of human-induced climate change for the marine realm, it is necessary to not only look at gradual changes but also at abrupt changes of environmental conditions. We summarise abrupt changes in ocean warming, acidification, and oxygen concentration as the key environmental factors for ecosystems. Taking these abrupt changes into account requires greenhouse gas emissions to be reduced to a larger extent than previously thought to limit respective damage.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Luke Gregor, Judith Hauck, Corinne Le Quéré, Ingrid T. Luijkx, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Ramdane Alkama, Almut Arneth, Vivek K. Arora, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Henry C. Bittig, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Wiley Evans, Stefanie Falk, Richard A. Feely, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Lucas Gloege, Giacomo Grassi, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Atul K. Jain, Annika Jersild, Koji Kadono, Etsushi Kato, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Peter Landschützer, Nathalie Lefèvre, Keith Lindsay, Junjie Liu, Zhu Liu, Gregg Marland, Nicolas Mayot, Matthew J. McGrath, Nicolas Metzl, Natalie M. Monacci, David R. Munro, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin O'Brien, Tsuneo Ono, Paul I. Palmer, Naiqing Pan, Denis Pierrot, Katie Pocock, Benjamin Poulter, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Carmen Rodriguez, Thais M. Rosan, Jörg Schwinger, Roland Séférian, Jamie D. Shutler, Ingunn Skjelvan, Tobias Steinhoff, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Shintaro Takao, Toste Tanhua, Pieter P. Tans, Xiangjun Tian, Hanqin Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Guido R. van der Werf, Anthony P. Walker, Rik Wanninkhof, Chris Whitehead, Anna Willstrand Wranne, Rebecca Wright, Wenping Yuan, Chao Yue, Xu Yue, Sönke Zaehle, Jiye Zeng, and Bo Zheng
Earth Syst. Sci. Data, 14, 4811–4900, https://doi.org/10.5194/essd-14-4811-2022, https://doi.org/10.5194/essd-14-4811-2022, 2022
Short summary
Short summary
The Global Carbon Budget 2022 describes the datasets and methodology used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, the land ecosystems, and the ocean. These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Pierre Friedlingstein, Matthew W. Jones, Michael O'Sullivan, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Corinne Le Quéré, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Rob B. Jackson, Simone R. Alin, Peter Anthoni, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Laurent Bopp, Thi Tuyet Trang Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Kim I. Currie, Bertrand Decharme, Laique M. Djeutchouang, Xinyu Dou, Wiley Evans, Richard A. Feely, Liang Feng, Thomas Gasser, Dennis Gilfillan, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Ingrid T. Luijkx, Atul Jain, Steve D. Jones, Etsushi Kato, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Peter Landschützer, Siv K. Lauvset, Nathalie Lefèvre, Sebastian Lienert, Junjie Liu, Gregg Marland, Patrick C. McGuire, Joe R. Melton, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Yosuke Niwa, Tsuneo Ono, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Clemens Schwingshackl, Roland Séférian, Adrienne J. Sutton, Colm Sweeney, Toste Tanhua, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco Tubiello, Guido R. van der Werf, Nicolas Vuichard, Chisato Wada, Rik Wanninkhof, Andrew J. Watson, David Willis, Andrew J. Wiltshire, Wenping Yuan, Chao Yue, Xu Yue, Sönke Zaehle, and Jiye Zeng
Earth Syst. Sci. Data, 14, 1917–2005, https://doi.org/10.5194/essd-14-1917-2022, https://doi.org/10.5194/essd-14-1917-2022, 2022
Short summary
Short summary
The Global Carbon Budget 2021 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Amanda R. Fay, Luke Gregor, Peter Landschützer, Galen A. McKinley, Nicolas Gruber, Marion Gehlen, Yosuke Iida, Goulven G. Laruelle, Christian Rödenbeck, Alizée Roobaert, and Jiye Zeng
Earth Syst. Sci. Data, 13, 4693–4710, https://doi.org/10.5194/essd-13-4693-2021, https://doi.org/10.5194/essd-13-4693-2021, 2021
Short summary
Short summary
The movement of carbon dioxide from the atmosphere to the ocean is estimated using surface ocean carbon (pCO2) measurements and an equation including variables such as temperature and wind speed; the choices of these variables lead to uncertainties. We introduce the SeaFlux ensemble which provides carbon flux maps calculated in a consistent manner, thus reducing uncertainty by using common choices for wind speed and a set definition of "global" coverage.
Tessa Sophia van der Voort, Thomas Michael Blattmann, Muhammed Usman, Daniel Montluçon, Thomas Loeffler, Maria Luisa Tavagna, Nicolas Gruber, and Timothy Ian Eglinton
Earth Syst. Sci. Data, 13, 2135–2146, https://doi.org/10.5194/essd-13-2135-2021, https://doi.org/10.5194/essd-13-2135-2021, 2021
Short summary
Short summary
Ocean sediments form the largest and longest-term storage of organic carbon. Despite their global importance, information on these sediments is often scattered, incomplete or inaccessible. Here we present MOSAIC (Modern Ocean Sediment Archive and Inventory of Carbon, mosaic.ethz.ch), a (radio)carbon-centric database that addresses this information gap. This database provides a platform for assessing the transport, deposition and storage of carbon in ocean surface sediments.
Giulia Bonino, Elisa Lovecchio, Nicolas Gruber, Matthias Münnich, Simona Masina, and Doroteaciro Iovino
Biogeosciences, 18, 2429–2448, https://doi.org/10.5194/bg-18-2429-2021, https://doi.org/10.5194/bg-18-2429-2021, 2021
Short summary
Short summary
Seasonal variations of processes such as upwelling and biological production that happen along the northwestern African coast can modulate the temporal variability of the biological activity of the adjacent open North Atlantic hundreds of kilometers away from the coast thanks to the lateral transport of coastal organic carbon. This happens with a temporal delay, which is smaller than a season up to roughly 500 km from the coast due to the intense transport by small-scale filaments.
Luke Gregor and Nicolas Gruber
Earth Syst. Sci. Data, 13, 777–808, https://doi.org/10.5194/essd-13-777-2021, https://doi.org/10.5194/essd-13-777-2021, 2021
Short summary
Short summary
Ocean acidification (OA) has altered the ocean's carbonate chemistry, with consequences for marine life. Yet, no observation-based data set exists that permits us to study changes in OA. We fill this gap with a global data set of relevant surface ocean parameters over the period 1985–2018. This data set, OceanSODA-ETHZ, was created by using satellite and other data to extrapolate ship-based measurements of carbon dioxide and total alkalinity from which parameters for OA were computed.
Anne-Marie Wefing, Núria Casacuberta, Marcus Christl, Nicolas Gruber, and John N. Smith
Ocean Sci., 17, 111–129, https://doi.org/10.5194/os-17-111-2021, https://doi.org/10.5194/os-17-111-2021, 2021
Short summary
Short summary
Atlantic Water that carries heat and anthropogenic carbon into the Arctic Ocean plays an important role in the Arctic sea-ice cover decline, but its pathways and travel times remain unclear. Here we used two radionuclides of anthropogenic origin (129I and 236U) to track Atlantic-derived waters along their way through the Arctic Ocean, estimating their travel times and mixing properties. Results help to understand how future changes in Atlantic Water properties will spread through the Arctic.
Derara Hailegeorgis, Zouhair Lachkar, Christoph Rieper, and Nicolas Gruber
Biogeosciences, 18, 303–325, https://doi.org/10.5194/bg-18-303-2021, https://doi.org/10.5194/bg-18-303-2021, 2021
Short summary
Short summary
Using a Lagrangian modeling approach, this study provides a quantitative analysis of water and nitrogen offshore transport in the Canary Current System. We investigate the timescales, reach and structure of offshore transport and demonstrate that the Canary upwelling is a key source of nutrients to the open North Atlantic Ocean. Our findings stress the need for improving the representation of the Canary system and other eastern boundary upwelling systems in global coarse-resolution models.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Judith Hauck, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Corinne Le Quéré, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone Alin, Luiz E. O. C. Aragão, Almut Arneth, Vivek Arora, Nicholas R. Bates, Meike Becker, Alice Benoit-Cattin, Henry C. Bittig, Laurent Bopp, Selma Bultan, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Wiley Evans, Liesbeth Florentie, Piers M. Forster, Thomas Gasser, Marion Gehlen, Dennis Gilfillan, Thanos Gkritzalis, Luke Gregor, Nicolas Gruber, Ian Harris, Kerstin Hartung, Vanessa Haverd, Richard A. Houghton, Tatiana Ilyina, Atul K. Jain, Emilie Joetzjer, Koji Kadono, Etsushi Kato, Vassilis Kitidis, Jan Ivar Korsbakken, Peter Landschützer, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Zhu Liu, Danica Lombardozzi, Gregg Marland, Nicolas Metzl, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin O'Brien, Tsuneo Ono, Paul I. Palmer, Denis Pierrot, Benjamin Poulter, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Adam J. P. Smith, Adrienne J. Sutton, Toste Tanhua, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Guido van der Werf, Nicolas Vuichard, Anthony P. Walker, Rik Wanninkhof, Andrew J. Watson, David Willis, Andrew J. Wiltshire, Wenping Yuan, Xu Yue, and Sönke Zaehle
Earth Syst. Sci. Data, 12, 3269–3340, https://doi.org/10.5194/essd-12-3269-2020, https://doi.org/10.5194/essd-12-3269-2020, 2020
Short summary
Short summary
The Global Carbon Budget 2020 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Cited articles
Afanasyev, A., Bianco, M., Mosimann, L., Osuna, C., Thaler, F., Vogt, H., Fuhrer, O., VandeVondele, J., and Schulthess, T. C.: GridTools: A framework for portable weather and climate applications, SoftwareX, 15, 1, https://doi.org/10.1016/j.softx.2021.100707, 2021. a
Atlas, R., Hoffman, R. N., Ardizzone, J., Leidner, S. M., Jusem, J. C., Smith, D. K., and Gombos, D.: A cross-calibrated, multiplatform ocean surface wind velocity product for meteorological and oceanographic applications, B. Am. Meteorol. Soc., 92, 157–174, https://doi.org/10.1175/2010BAMS2946.1, 2011. a
Auclair, F., Benshila, R., Bordois, L., Boutet, M., Brémond, M., Caillaud, M., Cambon, G., Capet, X., Debreu, L., Ducousso, N., Dufois, F., Dumas, F., Ethé, C., Gula, J., Hourdin, C., Illig, S., Jullien, S., Le Corre, M., Le Gac, S., Le Gentil, S., Lemarié, F., Marchesiello, P., Mazoyer, C., Morvan, G., Nguyen, C., Penven, P., Person, R., Pianezze, J., Pous, S., Renault, L., Roblou, L., Sepulveda, A., and Theetten, S.: Coastal and Regional Ocean COmmunity model, Version 1.3, Zenodo [software], https://doi.org/10.5281/zenodo.7415343, 2022. a
Baldauf, M., Seifert, A., Förstner, J., Majewski, D., Raschendorfer, M., and Reinhardt, T.: Operational Convective-Scale Numerical Weather Prediction with the COSMO Model: Description and Sensitivities, Mon. Weather Rev., 139, 3887–3905, https://doi.org/10.1175/MWR-D-10-05013.1, 2011. a
Bender, F. A., Charlson, R. J., Ekman, A. M., and Leahy, L. V.: Quantification of monthly mean regional-scale albedo of marine stratiform clouds in satellite observations and GCMs, J. Appl. Meteorol. Clim., 50, 2139–2148, https://doi.org/10.1175/JAMC-D-11-049.1, 2011. a
Brient, F., Roehrig, R., and Voldoire, A.: Evaluating Marine Stratocumulus Clouds in the CNRM-CM6-1 Model Using Short-Term Hindcasts, J. Adv. Model. Earth Sy., 11, 127–148, https://doi.org/10.1029/2018MS001461, 2019. a, b
Brogli, R., Heim, C., Mensch, J., Sørland, S. L., and Schär, C.: The pseudo-global-warming (PGW) approach: methodology, software package PGW4ERA5 v1.1, validation, and sensitivity analyses, Geosci. Model Dev., 16, 907–926, https://doi.org/10.5194/gmd-16-907-2023, 2023. a
Byrne, D., Münnich, M., Frenger, I., and Gruber, N.: Mesoscale atmosphere ocean coupling enhances the transfer of wind energy into the ocean, Nat. Commun., 7, 1, https://doi.org/10.1038/ncomms11867, 2016. a, b
Caldwell, P. M., Terai, C. R., Hillman, B., Keen, N. D., Bogenschutz, P., Lin, W., Beydoun, H., Taylor, M., Bertagna, L., Bradley, A. M., Clevenger, T. C., Donahue, A. S., Eldred, C., Foucar, J., Golaz, J. C., Guba, O., Jacob, R., Johnson, J., Krishna, J., Liu, W., Pressel, K., Salinger, A. G., Singh, B., Steyer, A., Ullrich, P., Wu, D., Yuan, X., Shpund, J., Ma, H. Y., and Zender, C. S.: Convection-Permitting Simulations With the E3SM Global Atmosphere Model, J. Adv. Model. Earth Sy., 13, 11, https://doi.org/10.1029/2021MS002544, 2021. a
Carton, J. A. and Giese, B. S.: A reanalysis of ocean climate using Simple Ocean Data Assimilation (SODA), Mon. Weather Rev., 136, 2999–3017, https://doi.org/10.1175/2007MWR1978.1, 2008. a
Demeshko, I., Maruyama, N., Tomita, H., and Matsuoka, S.: Multi-GPU Implementation of the NICAM Atmospheric Model, Euro-Par 2012: Parallel Processing Workshops, 7640, 175–184, https://doi.org/10.1007/978-3-642-36949-0, 2013. a
Desmet, F., Gruber, N., Köhn, E. E., Münnich, M., and Vogt, M.: Tracking the space-time evolution of ocean acidification extremes in the California Current System and Northeast Pacific, J. Geophys. Res.-Oceans, 127, e2021JC018159, https://doi.org/10.1029/2021JC018159, 2022. a, b, c
Eirund, G. K.: Data and Code for “ROMSOC: A regional atmosphere-ocean coupled model for CPU-GPU hybrid system architectures”, Zenodo [data set], https://doi.org/10.5281/zenodo.14275348, 2024. a
Eirund, G. K.: Source code for COSMO and ROMS in coupled mode, Zenodo [code], https://doi.org/10.5281/zenodo.14624664, 2025. a
Foerstner, J. and Doms, G.: Runge-Kutta time integration and high-order spatial discretization of advection – a new dynamical core for the LMK, COSMO Newsletter No. 4, Deutscher Wetterdienst, 168–176, https://www.cosmo-model.org (last access: 2 September 2025), 2004. a
Frischknecht, M., Münnich, M., and Gruber, N.: Remote versus local influence of ENSO on the California Current System, J. Geophys. Res.-Oceans, 120, 1353–1374, https://doi.org/10.1002/2014JC010531, 2015. a, b, c, d
Frischknecht, M., Münnich, M., and Gruber, N.: Origin, Transformation, and Fate: The Three-Dimensional Biological Pump in the California Current System, J. Geophys. Res.-Oceans, 123, 7939–7962, https://doi.org/10.1029/2018JC013934, 2018. a, b, c, d
Fuhrer, O., Osuna, C., Lapillonne, X., Gysi, T., Cumming, B., Bianco, M., Arteaga, A., and Schulthess, T. C.: Towards a performance portable, architecture agnostic implementation strategy for weather and climate models, Supercomputing Frontiers and Innovations, 1, 44–61, https://doi.org/10.14529/jsfi140103, 2014. a, b
Fuhrer, O., Chadha, T., Hoefler, T., Kwasniewski, G., Lapillonne, X., Leutwyler, D., Lüthi, D., Osuna, C., Schär, C., Schulthess, T. C., and Vogt, H.: Near-global climate simulation at 1 km resolution: establishing a performance baseline on 4888 GPUs with COSMO 5.0, Geosci. Model Dev., 11, 1665–1681, https://doi.org/10.5194/gmd-11-1665-2018, 2018. a, b, c
Giorgetta, M. A., Sawyer, W., Lapillonne, X., Adamidis, P., Alexeev, D., Clément, V., Dietlicher, R., Engels, J. F., Esch, M., Franke, H., Frauen, C., Hannah, W. M., Hillman, B. R., Kornblueh, L., Marti, P., Norman, M. R., Pincus, R., Rast, S., Reinert, D., Schnur, R., Schulzweida, U., and Stevens, B.: The ICON-A model for direct QBO simulations on GPUs (version icon-cscs:baf28a514), Geosci. Model Dev., 15, 6985–7016, https://doi.org/10.5194/gmd-15-6985-2022, 2022. a, b
Gruber, N., Frenzel, H., Doney, S. C., Marchesiello, P., McWilliams, J. C., Moisan, J. R., Oram, J. J., Plattner, G. K., and Stolzenbach, K. D.: Eddy-resolving simulation of plankton ecosystem dynamics in the California Current System, Deep-Sea Res. Pt. I, 53, 1483–1516, https://doi.org/10.1016/j.dsr.2006.06.005, 2006. a
Gruber, N., Lachkar, Z., Frenzel, H., Marchesiello, P., Münnich, M., McWilliams, J. C., Nagai, T., and Plattner, G. K.: Eddy-induced reduction of biological production in eastern boundary upwelling systems, Nat. Geosci., 4, 787–792, https://doi.org/10.1038/ngeo1273, 2011. a
Heim, C., Hentgen, L., Ban, N., and Schär, C.: Inter-model variability in convection-resolving simulations of subtropical marine low clouds, J. Meteorol. Soc. Jpn., 99, 1271–1295, https://doi.org/10.2151/jmsj.2021-062, 2021. a, b
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., Chiara, G. D., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J. N.: The ERA5 global reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020. a, b
Hohenegger, C., Korn, P., Linardakis, L., Redler, R., Schnur, R., Adamidis, P., Bao, J., Bastin, S., Behravesh, M., Bergemann, M., Biercamp, J., Bockelmann, H., Brokopf, R., Brüggemann, N., Casaroli, L., Chegini, F., Datseris, G., Esch, M., George, G., Giorgetta, M., Gutjahr, O., Haak, H., Hanke, M., Ilyina, T., Jahns, T., Jungclaus, J., Kern, M., Klocke, D., Kluft, L., Kölling, T., Kornblueh, L., Kosukhin, S., Kroll, C., Lee, J., Mauritsen, T., Mehlmann, C., Mieslinger, T., Naumann, A. K., Paccini, L., Peinado, A., Praturi, D. S., Putrasahan, D., Rast, S., Riddick, T., Roeber, N., Schmidt, H., Schulzweida, U., Schütte, F., Segura, H., Shevchenko, R., Singh, V., Specht, M., Stephan, C. C., von Storch, J.-S., Vogel, R., Wengel, C., Winkler, M., Ziemen, F., Marotzke, J., and Stevens, B.: ICON-Sapphire: simulating the components of the Earth system and their interactions at kilometer and subkilometer scales, Geosci. Model Dev., 16, 779–811, https://doi.org/10.5194/gmd-16-779-2023, 2023. a
Jeronimo, G. and Gomez-Valdes, J.: Mixed layer depth variability in the tropical boundary of the California Current, 1997–2007, J. Geophys. Res.-Oceans, 115, C05014, https://doi.org/10.1029/2009JC005457, 2010. a
Jones, N.: How to stop data centres from gobbling up the world's electricity, Nature, 561, 163–166, 2018. a
Kirtman, B. P., Bitz, C., Bryan, F., Collins, W., Dennis, J., Hearn, N., Kinter, J. L., Loft, R., Rousset, C., Siqueira, L., Stan, C., Tomas, R., and Vertenstein, M.: Impact of ocean model resolution on CCSM climate simulations, Clim. Dynam., 39, 1303–1328, https://doi.org/10.1007/s00382-012-1500-3, 2012. a
Klein, S. A. and Hartmann, D. L.: The seasonal cycle of low stratiform clouds, J. Climate, 6, 1587–1606, https://doi.org/10.1175/1520-0442(1993)006<1587:TSCOLS>2.0.CO;2, 1993. a
Koehn, E. E., Muennich, M., Vogt, M., Desmet, F., and Gruber, N.: Strong Habitat Compression by Extreme Shoaling Events of Hypoxic Waters in the Eastern Pacific, J. Geophys. Res.-Oceans, 127, e2022JC018429, https://doi.org/10.1029/2022JC018429, 2022. a
Kurian, J., Colas, F., Capet, X., McWilliams, J. C., and Chelton, D. B.: Eddy properties in the California Current System, J. Geophys. Res.-Oceans, 116, C08027, https://doi.org/10.1029/2010JC006895, 2011. a
Large, W. G., McWilliams, J. C., and Doney, S. C.: Oceanic vertical mixing: A review and a model with a nonlocal boundary layer parameterization, Rev. Geophys., 32, 363–403, https://doi.org/10.1029/94RG01872, 1994. a
Leutwyler, D., Fuhrer, O., Lapillonne, X., Lüthi, D., and Schär, C.: Towards European-scale convection-resolving climate simulations with GPUs: a study with COSMO 4.19, Geosci. Model Dev., 9, 3393–3412, https://doi.org/10.5194/gmd-9-3393-2016, 2016. a, b, c
Levitus, S., Boyer, T. P., García, H. E., Locarnini, R. A., Zweng, M. M., Mishonov, A. V., Reagan, J. R., Antonov, J. I., Baranova, O. K., Biddle, M., Hamilton, M., Johnson, D. R., Paver, C. R., and Seidov, D.: World Ocean Atlas 2013 (NCEI Accession 0114815), NOAA National Centers for Environmental Information [data set], https://doi.org/10.7289/v5f769gt, 2014. a
Lin, J. L., Qian, T., and Shinoda, T.: Stratocumulus clouds in Southeastern pacific simulated by eight CMIP5-CFMIP global climate models, J. Climate, 27, 3000–3022, https://doi.org/10.1175/JCLI-D-13-00376.1, 2014. a
Madec, G. and the NEMO System Team: NEMO Ocean Engine Reference Manual, Zenodo, https://doi.org/10.5281/zenodo.1464816, 2024. a
Marchesiello, P., Mcwilliams, J. C., and Shchepetkin, A.: Equilibrium Structure and Dynamics of the California Current System, 33, 753–783, https://doi.org/10.1175/1520-0485(2003)33<753:ESADOT>2.0.CO;2, 2003. a, b
Mauritsen, T., Redler, R., Esch, M., Stevens, B., Hohenegger, C., Klocke, D., Brokopf, R., Haak, H., Linardakis, L., Röber, N., and Schnur, R.: Early Development and Tuning of a Global Coupled Cloud Resolving Model, and its Fast Response to Increasing CO2, Tellus A, 74, 346–363, https://doi.org/10.16993/tellusa.54, 2022. a
McClean, J. L., Bader, D. C., Bryan, F. O., Maltrud, M. E., Dennis, J. M., Mirin, A. A., Jones, P. W., Kim, Y. Y., Ivanova, D. P., Vertenstein, M., Boyle, J. S., Jacob, R. L., Norton, N., Craig, A., and Worley, P. H.: A prototype two-decade fully-coupled fine-resolution CCSM simulation, Ocean Model., 39, 10–30, https://doi.org/10.1016/j.ocemod.2011.02.011, 2011. a
Mears, C. A., Scott, J., Wentz, F. J., Ricciardulli, L., Leidner, S. M., Hoffman, R., and Atlas, R.: A Near-Real-Time Version of the Cross-Calibrated Multiplatform (CCMP) Ocean Surface Wind Velocity Data Set, J. Geophys. Res.-Oceans, 124, 6997–7010, https://doi.org/10.1029/2019JC015367, 2019. a
Meredith, E. P., Maraun, D., Semenov, V. A., and Park, W.: Evidence for added value of convection-permitting models for studying changes in extreme precipitation, J. Geophys. Res., 120, 12500–12513, https://doi.org/10.1002/2015JD024238, 2015. a
Palmer, T.: Climate forecasting: Build high-resolution global climate models, Nature, 515, 338–339, https://doi.org/10.1038/515338a, 2014. a
Palmer, T. and Stevens, B.: The scientific challenge of understanding and estimating climate change, P. Natl. Acad. Sci. USA, 116, 24390–24395, https://doi.org/10.1073/pnas.1906691116, 2019. a
Prein, A. F., Langhans, W., Fosser, G., Ferrone, A., Ban, N., Goergen, K., Keller, M., Tölle, M., Gutjahr, O., Feser, F., Brisson, E., Kollet, S., Schmidli, J., Lipzig, N. P. V., and Leung, R.: A review on regional convection-permitting climate modeling: Demonstrations, prospects, and challenges, Rev. Geophys., 53, 323–361, https://doi.org/10.1002/2014RG000475, 2015. a
Redler, R., Valcke, S., and Ritzdorf, H.: OASIS4 – a coupling software for next generation earth system modelling, Geosci. Model Dev., 3, 87–104, https://doi.org/10.5194/gmd-3-87-2010, 2010. a, b
Renault, L., Deutsch, C., McWilliams, J. C., Frenzel, H., Liang, J. H., and Colas, F.: Partial decoupling of primary productivity from upwelling in the California Current system, Nat. Geosci., 9, 505–508, https://doi.org/10.1038/ngeo2722, 2016a. a
Renault, L., Hall, A., and McWilliams, J. C.: Orographic shaping of US West Coast wind profiles during the upwelling season, Clim. Dynam., 46, 273–289, https://doi.org/10.1007/s00382-015-2583-4, 2016b. a, b
Renault, L., Molemaker, M. J., Mcwilliams, J. C., Shchepetkin, A. F., Lemarié, F., Chelton, D., Illig, S., and Hall, A.: Modulation of wind work by oceanic current interaction with the atmosphere, J. Phys. Oceanogr., 46, 1685–1704, https://doi.org/10.1175/JPO-D-15-0232.1, 2016c. a, b, c
Renault, L., Lemarié, F., and Arsouze, T.: On the implementation and consequences of the oceanic currents feedback in ocean–atmosphere coupled models, Ocean Model., 141, 101423, https://doi.org/10.1016/j.ocemod.2019.101423, 2019. a
Renault, L., McWilliams, J., Kessouri, F., Jousse, A., Frenzel, H., Chen, R., and Deutsch, C.: Evaluation of high-resolution atmospheric and oceanic simulations of the California Current System, Prog. Oceanogr., 195, 102564, https://doi.org/10.1016/j.pocean.2021.102564, 2020. a, b, c, d
Reynolds, R. W., Smith, T. M., Liu, C., Chelton, D. B., Casey, K. S., and Schlax, M. G.: Daily high-resolution-blended analyses for sea surface temperature, J. Climate, 20, 5473–5496, https://doi.org/10.1175/2007JCLI1824.1, 2007. a, b
Richter, I.: Climate model biases in the eastern tropical oceans: Causes, impacts and ways forward, WIRES Clim. Change, 6, 345–358, https://doi.org/10.1002/wcc.338, 2015. a, b
Ritter, B. and Geleyn, J.-F.: A Comprehensive Radiation Scheme for Numerical Weather Prediction Models with Potential Applications in Climate Simulations, Mon. Weather Rev., 120, 303–325, https://doi.org/10.1175/1520-0493(1992)120<0303:ACRSFN>2.0.CO;2, 1992. a
Rudnick, D. L., Zaba, K. D., Todd, R. E., and Davis, R. E.: A climatology of the California Current System from a network of underwater gliders, Prog. Oceanogr., 154, 64–106, https://doi.org/10.1016/j.pocean.2017.03.002, 2017. a
Schneider, T., Teixeira, J., Bretherton, C. S., Brient, F., Pressel, K. G., Schär, C., and Siebesma, A. P.: Climate goals and computing the future of clouds, Nat. Clim. Change, 7, 3–5, https://doi.org/10.1038/nclimate3190, 2017. a
Schrodin, R. and Heise, E.: The Multi−Layer Version of the DWD Soil Model TERRA_LM, COSMO Technical Report No. 2, https://doi.org/10.5676/DWD_pub/nwv/cosmo-tr_2, 2001. a
Schär, C., Fuhrer, O., Arteaga, A., Ban, N., Charpilloz, C., Girolamo, S. D., Hentgen, L., Hoefler, T., Lapillonne, X., Leutwyler, D., Osterried, K., Panosetti, D., Rüdisühli, S., Schlemmer, L., Schulthess, T. C., Sprenger, M., Ubbiali, S., and Wernli, H.: Kilometer-scale climate models: Prospects and challenges, B. Am. Meteorol. Soc., 101, E567–E587, https://doi.org/10.1175/BAMS-D-18-0167.1, 2020. a
Schättler, U., Doms, G., and Steppele, J.: Requirements and problems in parallel model development at DWD, Sci. Programming, 8, 13–22, 2000. a
Seifert, A. and Beheng, K. D.: A two-moment cloud microphysics parameterization for mixed-phase clouds. Part 1: Model description, Meteorol. Atmos. Phys., 92, 45–66, https://doi.org/10.1007/s00703-005-0112-4, 2006. a
Shchepetkin, A. F. and McWilliams, J. C.: The regional oceanic modeling system (ROMS): A split-explicit, free-surface, topography-following-coordinate oceanic model, Ocean Model., 9, 347–404, https://doi.org/10.1016/j.ocemod.2004.08.002, 2005. a, b
Skamarock, W. C., Klemp, J. B., Dudhia, J., Gill, D. O., Liu, Z., Berner, J., Wang, W., Powers, J. G., Duda, M. G., Barker, D. M., and Huang, X.-Y.: A Description of the Advanced Research WRF Model Version 4, Technical report, No. NCAR/TN-556+STR, http://library.ucar.edu/research/publish-technote (last access: 2 September 2025), 2021. a
Small, R. J., Curchitser, E., Hedstrom, K., Kauffman, B., and Large, W. G.: The Benguela Upwelling System: Quantifying the Sensitivity to Resolution and Coastal Wind Representation in a Global Climate Model, J. Climate, 28, 9409–9432, https://doi.org/10.1175/JCLI-D-15-0192.1, 2015. a
Steppeler, J., Doms, G., Schättler, U., Bitzer, H., Gassmann, A., Damrath, U., and Gregoric, G.: Meso-gamma scale forecasts using the nonhydrostatic model LM, Meteorol. Atmos. Phys., 82, 75–96, https://doi.org/10.1007/s00703-001-0592-9, 2003. a
Stevens, B.: On the growth of layers of nonprecipitating cumulus convection, J. Atmos. Sci., 64, 2916–2931, https://doi.org/10.1175/JAS3983.1, 2007. a
Stevens, B., Acquistapace, C., Hansen, A., Heinze, R., Klinger, C., Klocke, D., Rybka, H., Schubotz, W., Windmiller, J., Adamidis, P., Arka, I., Barlakas, V., Biercamp, J., Brueck, M., Brune, S., Buehler, S. A., Burkhardt, U., Cioni, G., Costa-Surós, M., Crewell, S., Crüger, T., Deneke, H., Friederichs, P., Henken, C. C., Hohenegger, C., Jacob, M., Jakub, F., Kalthoff, N., Köhler, M., van LAAR, T. W., Li, P., Löhnert, U., Macke, A., Madenach, N., Mayer, B., Nam, C., Naumann, A. K., Peters, K., Poll, S., Quaas, J., Röber, N., Rochetin, N., Scheck, L., Schemann, V., Schnitt, S., Seifert, A., Senf, F., Shapkalijevski, M., Simmer, C., Singh, S., Sourdeval, O., Spickermann, D., Strandgren, J., Tessiot, O., Vercauteren, N., Vial, J., Voigt, A., and Zängl, G.: The added value of large-eddy and storm-resolving models for simulating clouds and precipitation, J. Meteorol. Soc. Jpn., 98, 395–435, https://doi.org/10.2151/jmsj.2020-021, 2020. a, b
Takasuka, D. and Satoh, M.: A protocol and analysis of year-long simulations of global storm-resolving models and beyond, Research Square Platform LLC [preprint], https://doi.org/10.21203/rs.3.rs-4458164/v1, 2024. a
Teixeira, J., Cardoso, S., Bonazzola, M., Cole, J., Delgenio, A., Demott, C., Franklin, C., Hannay, C., Jakob, C., Jiao, Y., Karlsson, J., Kitagawa, H., Köhler, M., Kuwano-Yoshida, A., Ledrian, C., Li, J., Lock, A., Miller, M. J., Marquet, P., Martins, J., Mechoso, C. R., Meijgaard, E. V., Meinke, I., Miranda, P. M., Mironov, D., Neggers, R., Pan, H. L., Randall, D. A., Rasch, P. J., Rockel, B., Rossow, W. B., Ritter, B., Siebesma, A. P., Soares, P. M., Turk, F. J., Vaillancourt, P. A., Engeln, A. V., and Zhao, M.: Tropical and subtropical cloud transitions in weather and climate prediction models: The GCSS/WGNE pacific cross-section intercomparison (GPCI), J. Climate, 24, 5223–5256, https://doi.org/10.1175/2011JCLI3672.1, 2011. a
Vergara-Temprado, J., Ban, N., Panosetti, D., Wetterdienst, D., and Offenbach, H.: Climate Models Permit Convection at Much Coarser Resolutions Than Previously Considered, J. Climate, 33, 1915–1933, https://doi.org/10.1175/JCLI-D-19-0286.s1, 2020. a
WWang, P., Jiang, J., Lin, P., Ding, M., Wei, J., Zhang, F., Zhao, L., Li, Y., Yu, Z., Zheng, W., Yu, Y., Chi, X., and Liu, H.: The GPU version of LASG/IAP Climate System Ocean Model version 3 (LICOM3) under the heterogeneous-compute interface for portability (HIP) framework and its large-scale application, Geosci. Model Dev., 14, 2781–2799, https://doi.org/10.5194/gmd-14-2781-2021, 2021. a
Wicker, L. J. and Skamarock, W. C.: Time-Splitting Methods for Elastic Models Using Forward Time Schemes, Mon. Weather Rev., 130, 2088–2097, 2002. a
Wong, A. P., 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., Buck, J. J., 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., 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., Cancouët, R., Coatanoan, C., Dobbler, D., Juan, A. G., Gourrion, J., Kolodziejczyk, N., Bernard, V., Bourlès, B., Claustre, H., D'Ortenzio, F., Reste, S. L., Traon, P. Y. L., 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., Rao, E. P. R., Ravichandran, M., Freeland, H. J., Gaboury, I., Gilbert, D., Greenan, B. J., Ouellet, M., Ross, T., Tran, A., Dong, M., Liu, Z., Xu, J., Kang, K. R., Jo, H. J., 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, Frontiers in Marine Science, 7, 700, https://doi.org/10.3389/fmars.2020.00700, 2020. a
Worley, S. J., Woodruff, S. D., Reynolds, R. W., Lubker, S. J., and Lott, N.: ICOADS release 2.1 data and products, Int. J. Climatol., 25, 823–842, https://doi.org/10.1002/joc.1166, 2005. a
Short summary
To realistically simulate small-scale processes in the atmosphere and ocean, such as clouds or mixing, high-resolution numerical models are needed. However, these models are computationally very demanding. Here, we present a recently developed atmosphere–ocean model which is able to resolve most of these processes and is less expensive to run due to its computational design. Our model can be used for a wide range of applications like the investigation of marine heatwaves or future projections.
To realistically simulate small-scale processes in the atmosphere and ocean, such as clouds or...