Articles | Volume 16, issue 23
https://doi.org/10.5194/gmd-16-6943-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-16-6943-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| 
29 Nov 2023
Model evaluation paper |
| 29 Nov 2023
| 29 Nov 2023
A high-resolution physical–biogeochemical model for marine resource applications in the northwest Atlantic (MOM6-COBALT-NWA12 v1.0)
Andrew C. Ross
CORRESPONDING AUTHOR
NOAA OAR Geophysical Fluid Dynamics Laboratory, Princeton, NJ, USA
Charles A. Stock
NOAA OAR Geophysical Fluid Dynamics Laboratory, Princeton, NJ, USA
Alistair Adcroft
NOAA OAR Geophysical Fluid Dynamics Laboratory, Princeton, NJ, USA
Enrique Curchitser
Department of Environmental Sciences, Rutgers University, New Brunswick, NJ, USA
Robert Hallberg
NOAA OAR Geophysical Fluid Dynamics Laboratory, Princeton, NJ, USA
Matthew J. Harrison
NOAA OAR Geophysical Fluid Dynamics Laboratory, Princeton, NJ, USA
Katherine Hedstrom
College of Fisheries and Ocean Sciences, University of Alaska Fairbanks, Fairbanks, AK, USA
Niki Zadeh
NOAA OAR Geophysical Fluid Dynamics Laboratory, Princeton, NJ, USA
Michael Alexander
NOAA Physical Sciences Laboratory, Boulder, CO, USA
Wenhao Chen
Atmospheric and Oceanic Sciences Program, Princeton University, Princeton, NJ, USA
Elizabeth J. Drenkard
NOAA OAR Geophysical Fluid Dynamics Laboratory, Princeton, NJ, USA
Hubert du Pontavice
Atmospheric and Oceanic Sciences Program, Princeton University, Princeton, NJ, USA
Raphael Dussin
NOAA OAR Geophysical Fluid Dynamics Laboratory, Princeton, NJ, USA
University Corporation for Atmospheric Research, Boulder, CO, USA
Fabian Gomez
Northern Gulf Institute, Mississippi State University, Starkville, MS, USA
NOAA OAR Atlantic Oceanographic and Meteorological Laboratory, Miami, FL, USA
Jasmin G. John
NOAA OAR Atlantic Oceanographic and Meteorological Laboratory, Miami, FL, USA
Dujuan Kang
School of Oceanography, Shanghai Jiao Tong University, Shanghai, China
Department of Environmental Sciences, Rutgers University, New Brunswick, NJ, USA
Diane Lavoie
Maurice Lamontagne Institute, Fisheries and Oceans Canada, Mont-Joli, Québec, Canada
Laure Resplandy
Department of Geosciences, Princeton University, Princeton, NJ, USA
High Meadows Environmental Institute, Princeton University, Princeton, NJ, USA
Alizée Roobaert
Department of Geosciences, Environment and Society – BGeoSys, Université Libre de Bruxelles, Brussels, CP160/02, Belgium
Vincent Saba
NOAA Northeast Fisheries Science Center, Geophysical Fluid Dynamics Laboratory, Princeton, NJ, USA
Sang-Ik Shin
NOAA Physical Sciences Laboratory, Boulder, CO, USA
Samantha Siedlecki
Department of Marine Sciences, University of Connecticut, Groton, CT, USA
James Simkins
Department of Environmental Sciences, Rutgers University, New Brunswick, NJ, USA
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Simone R. Alin, Jan A. Newton, Richard A. Feely, Samantha Siedlecki, and Dana Greeley
Biogeosciences, 21, 1639–1673, https://doi.org/10.5194/bg-21-1639-2024, https://doi.org/10.5194/bg-21-1639-2024, 2024
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Katja Frieler, Jan Volkholz, Stefan Lange, Jacob Schewe, Matthias Mengel, María del Rocío Rivas López, Christian Otto, Christopher P. O. Reyer, Dirk Nikolaus Karger, Johanna T. Malle, Simon Treu, Christoph Menz, Julia L. Blanchard, Cheryl S. Harrison, Colleen M. Petrik, Tyler D. Eddy, Kelly Ortega-Cisneros, Camilla Novaglio, Yannick Rousseau, Reg A. Watson, Charles Stock, Xiao Liu, Ryan Heneghan, Derek Tittensor, Olivier Maury, Matthias Büchner, Thomas Vogt, Tingting Wang, Fubao Sun, Inga J. Sauer, Johannes Koch, Inne Vanderkelen, Jonas Jägermeyr, Christoph Müller, Sam Rabin, Jochen Klar, Iliusi D. Vega del Valle, Gitta Lasslop, Sarah Chadburn, Eleanor Burke, Angela Gallego-Sala, Noah Smith, Jinfeng Chang, Stijn Hantson, Chantelle Burton, Anne Gädeke, Fang Li, Simon N. Gosling, Hannes Müller Schmied, Fred Hattermann, Jida Wang, Fangfang Yao, Thomas Hickler, Rafael Marcé, Don Pierson, Wim Thiery, Daniel Mercado-Bettín, Robert Ladwig, Ana Isabel Ayala-Zamora, Matthew Forrest, and Michel Bechtold
Geosci. Model Dev., 17, 1–51, https://doi.org/10.5194/gmd-17-1-2024, https://doi.org/10.5194/gmd-17-1-2024, 2024
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Our paper provides an overview of all observational climate-related and socioeconomic forcing data used as input for the impact model evaluation and impact attribution experiments within the third round of the Inter-Sectoral Impact Model Intercomparison Project. The experiments are designed to test our understanding of observed changes in natural and human systems and to quantify to what degree these changes have already been induced by climate change.
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
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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.
Sam Ditkovsky, Laure Resplandy, and Julius Busecke
Biogeosciences, 20, 4711–4736, https://doi.org/10.5194/bg-20-4711-2023, https://doi.org/10.5194/bg-20-4711-2023, 2023
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The global ocean is losing oxygen due to warming. The Indian Ocean, however, is gaining oxygen in large parts of the basin, and its naturally occurring oxygen minimum zone is not expanding. This rather unexpected response is explained by the unique ocean circulation of the Indian Ocean, which is bounded by a continent to the north but connected to the Pacific Ocean by the Indonesian Throughflow.
Weiyi Tang, Bess B. Ward, Michael Beman, Laura Bristow, Darren Clark, Sarah Fawcett, Claudia Frey, François Fripiat, Gerhard J. Herndl, Mhlangabezi Mdutyana, Fabien Paulot, Xuefeng Peng, Alyson E. Santoro, Takuhei Shiozaki, Eva Sintes, Charles Stock, Xin Sun, Xianhui S. Wan, Min N. Xu, and Yao Zhang
Earth Syst. Sci. Data, 15, 5039–5077, https://doi.org/10.5194/essd-15-5039-2023, https://doi.org/10.5194/essd-15-5039-2023, 2023
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Nitrification and nitrifiers play an important role in marine nitrogen and carbon cycles by converting ammonium to nitrite and nitrate. Nitrification could affect microbial community structure, marine productivity, and the production of nitrous oxide – a powerful greenhouse gas. We introduce the newly constructed database of nitrification and nitrifiers in the marine water column and guide future research efforts in field observations and model development of nitrification.
Fabian A. Gomez, Sang-Ki Lee, Charles A. Stock, Andrew C. Ross, Laure Resplandy, Samantha A. Siedlecki, Filippos Tagklis, and Joseph E. Salisbury
Earth Syst. Sci. Data, 15, 2223–2234, https://doi.org/10.5194/essd-15-2223-2023, https://doi.org/10.5194/essd-15-2223-2023, 2023
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We present a river chemistry and discharge dataset for 140 rivers in the United States, which integrates information from the Water Quality Database of the US Geological Survey (USGS), the USGS’s Surface-Water Monthly Statistics for the Nation, and the U.S. Army Corps of Engineers. This dataset includes dissolved inorganic carbon and alkalinity, two key properties to characterize the carbonate system, as well as nutrient concentrations, such as nitrate, phosphate, and silica.
Alban Planchat, Lester Kwiatkowski, Laurent Bopp, Olivier Torres, James R. Christian, Momme Butenschön, Tomas Lovato, Roland Séférian, Matthew A. Chamberlain, Olivier Aumont, Michio Watanabe, Akitomo Yamamoto, Andrew Yool, Tatiana Ilyina, Hiroyuki Tsujino, Kristen M. Krumhardt, Jörg Schwinger, Jerry Tjiputra, John P. Dunne, and Charles Stock
Biogeosciences, 20, 1195–1257, https://doi.org/10.5194/bg-20-1195-2023, https://doi.org/10.5194/bg-20-1195-2023, 2023
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Ocean alkalinity is critical to the uptake of atmospheric carbon and acidification in surface waters. We review the representation of alkalinity and the associated calcium carbonate cycle in Earth system models. While many parameterizations remain present in the latest generation of models, there is a general improvement in the simulated alkalinity distribution. This improvement is related to an increase in the export of biotic calcium carbonate, which closer resembles observations.
Abigale M. Wyatt, Laure Resplandy, and Adrian Marchetti
Biogeosciences, 19, 5689–5705, https://doi.org/10.5194/bg-19-5689-2022, https://doi.org/10.5194/bg-19-5689-2022, 2022
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Marine heat waves (MHWs) are a frequent event in the northeast Pacific, with a large impact on the region's ecosystems. Large phytoplankton in the North Pacific Transition Zone are greatly affected by decreased nutrients, with less of an impact in the Alaskan Gyre. For small phytoplankton, MHWs increase the spring small phytoplankton population in both regions thanks to reduced light limitation. In both zones, this results in a significant decrease in the ratio of large to small phytoplankton.
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
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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.
Gustavo M. Marques, Nora Loose, Elizabeth Yankovsky, Jacob M. Steinberg, Chiung-Yin Chang, Neeraja Bhamidipati, Alistair Adcroft, Baylor Fox-Kemper, Stephen M. Griffies, Robert W. Hallberg, Malte F. Jansen, Hemant Khatri, and Laure Zanna
Geosci. Model Dev., 15, 6567–6579, https://doi.org/10.5194/gmd-15-6567-2022, https://doi.org/10.5194/gmd-15-6567-2022, 2022
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We present an idealized ocean model configuration and a set of simulations performed using varying horizontal grid spacing. While the model domain is idealized, it resembles important geometric features of the Atlantic and Southern oceans. The simulations described here serve as a framework to effectively study mesoscale eddy dynamics, to investigate the effect of mesoscale eddies on the large-scale dynamics, and to test and evaluate eddy parameterizations.
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
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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.
Alizée Roobaert, Laure Resplandy, Goulven G. Laruelle, Enhui Liao, and Pierre Regnier
Ocean Sci., 18, 67–88, https://doi.org/10.5194/os-18-67-2022, https://doi.org/10.5194/os-18-67-2022, 2022
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This study uses a global oceanic model to investigate the seasonal dynamics of the sea surface partial pressure of CO2 (pCO2) in the global coastal ocean. Our method quantifies the respective effects of thermal changes, biological activity, ocean circulation and freshwater fluxes on the temporal pCO2 variations. The performance of our model is also evaluated against a data product derived from observations to identify coastal regions where our approach is most robust.
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
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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.
Samantha A. Siedlecki, Darren Pilcher, Evan M. Howard, Curtis Deutsch, Parker MacCready, Emily L. Norton, Hartmut Frenzel, Jan Newton, Richard A. Feely, Simone R. Alin, and Terrie Klinger
Biogeosciences, 18, 2871–2890, https://doi.org/10.5194/bg-18-2871-2021, https://doi.org/10.5194/bg-18-2871-2021, 2021
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Future ocean conditions can be simulated using projected trends in fossil fuel use paired with Earth system models. Global models generally do not include local processes important to coastal ecosystems. These coastal processes can alter the degree of change projected. Higher-resolution models that include local processes predict modified changes in carbon stressors when compared to changes projected by global models in the California Current System.
Chia-Wei Hsu, Jianjun Yin, Stephen M. Griffies, and Raphael Dussin
Geosci. Model Dev., 14, 2471–2502, https://doi.org/10.5194/gmd-14-2471-2021, https://doi.org/10.5194/gmd-14-2471-2021, 2021
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The new surface forcing from JRA55-do (OMIP II) significantly improved the underestimated sea level trend across the entire Pacific Ocean along 10° N in the simulation forced by CORE (OMIP I). We summarize and list out the reasons for the existing sea level biases across all studied timescales as a reference for improving the sea level simulation in the future. This study on the evaluation and improvement of ocean climate models should be of broad interest to a large modeling community.
Claudia Tebaldi, Kevin Debeire, Veronika Eyring, Erich Fischer, John Fyfe, Pierre Friedlingstein, Reto Knutti, Jason Lowe, Brian O'Neill, Benjamin Sanderson, Detlef van Vuuren, Keywan Riahi, Malte Meinshausen, Zebedee Nicholls, Katarzyna B. Tokarska, George Hurtt, Elmar Kriegler, Jean-Francois Lamarque, Gerald Meehl, Richard Moss, Susanne E. Bauer, Olivier Boucher, Victor Brovkin, Young-Hwa Byun, Martin Dix, Silvio Gualdi, Huan Guo, Jasmin G. John, Slava Kharin, YoungHo Kim, Tsuyoshi Koshiro, Libin Ma, Dirk Olivié, Swapna Panickal, Fangli Qiao, Xinyao Rong, Nan Rosenbloom, Martin Schupfner, Roland Séférian, Alistair Sellar, Tido Semmler, Xiaoying Shi, Zhenya Song, Christian Steger, Ronald Stouffer, Neil Swart, Kaoru Tachiiri, Qi Tang, Hiroaki Tatebe, Aurore Voldoire, Evgeny Volodin, Klaus Wyser, Xiaoge Xin, Shuting Yang, Yongqiang Yu, and Tilo Ziehn
Earth Syst. Dynam., 12, 253–293, https://doi.org/10.5194/esd-12-253-2021, https://doi.org/10.5194/esd-12-253-2021, 2021
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We present an overview of CMIP6 ScenarioMIP outcomes from up to 38 participating ESMs according to the new SSP-based scenarios. Average temperature and precipitation projections according to a wide range of forcings, spanning a wider range than the CMIP5 projections, are documented as global averages and geographic patterns. Times of crossing various warming levels are computed, together with benefits of mitigation for selected pairs of scenarios. Comparisons with CMIP5 are also discussed.
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
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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.
Steven T. Turnock, Robert J. Allen, Martin Andrews, Susanne E. Bauer, Makoto Deushi, Louisa Emmons, Peter Good, Larry Horowitz, Jasmin G. John, Martine Michou, Pierre Nabat, Vaishali Naik, David Neubauer, Fiona M. O'Connor, Dirk Olivié, Naga Oshima, Michael Schulz, Alistair Sellar, Sungbo Shim, Toshihiko Takemura, Simone Tilmes, Kostas Tsigaridis, Tongwen Wu, and Jie Zhang
Atmos. Chem. Phys., 20, 14547–14579, https://doi.org/10.5194/acp-20-14547-2020, https://doi.org/10.5194/acp-20-14547-2020, 2020
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A first assessment is made of the historical and future changes in air pollutants from models participating in the 6th Coupled Model Intercomparison Project (CMIP6). Substantial benefits to future air quality can be achieved in future scenarios that implement measures to mitigate climate and involve reductions in air pollutant emissions, particularly methane. However, important differences are shown between models in the future regional projection of air pollutants under the same scenario.
Peter Landschützer, Goulven G. Laruelle, Alizee Roobaert, and Pierre Regnier
Earth Syst. Sci. Data, 12, 2537–2553, https://doi.org/10.5194/essd-12-2537-2020, https://doi.org/10.5194/essd-12-2537-2020, 2020
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In recent years, multiple estimates of the global air–sea CO2 flux emerged from upscaling shipboard pCO2 measurements. They are however limited to the open-ocean domain and do not consider the coastal ocean, i.e. a significant marine sink for CO2. We build towards an integrated pCO2 product that combines both the open-ocean and coastal-ocean domain and focus on the evaluation of the common overlap area of these products and how well the aquatic continuum is represented in the new climatology.
Friedrich A. Burger, Jasmin G. John, and Thomas L. Frölicher
Biogeosciences, 17, 4633–4662, https://doi.org/10.5194/bg-17-4633-2020, https://doi.org/10.5194/bg-17-4633-2020, 2020
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Ensemble simulations of an Earth system model reveal that ocean acidity extremes have increased in the past few decades and are projected to increase further in terms of frequency, intensity, duration, and volume extent. The increase is not only caused by the long-term ocean acidification due to the uptake of anthropogenic CO2, but also due to changes in short-term variability. The increase in ocean acidity extremes may enhance the risk of detrimental impacts on marine organisms.
Hiroyuki Tsujino, L. Shogo Urakawa, Stephen M. Griffies, Gokhan Danabasoglu, Alistair J. Adcroft, Arthur E. Amaral, Thomas Arsouze, Mats Bentsen, Raffaele Bernardello, Claus W. Böning, Alexandra Bozec, Eric P. Chassignet, Sergey Danilov, Raphael Dussin, Eleftheria Exarchou, Pier Giuseppe Fogli, Baylor Fox-Kemper, Chuncheng Guo, Mehmet Ilicak, Doroteaciro Iovino, Who M. Kim, Nikolay Koldunov, Vladimir Lapin, Yiwen Li, Pengfei Lin, Keith Lindsay, Hailong Liu, Matthew C. Long, Yoshiki Komuro, Simon J. Marsland, Simona Masina, Aleksi Nummelin, Jan Klaus Rieck, Yohan Ruprich-Robert, Markus Scheinert, Valentina Sicardi, Dmitry Sidorenko, Tatsuo Suzuki, Hiroaki Tatebe, Qiang Wang, Stephen G. Yeager, and Zipeng Yu
Geosci. Model Dev., 13, 3643–3708, https://doi.org/10.5194/gmd-13-3643-2020, https://doi.org/10.5194/gmd-13-3643-2020, 2020
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The OMIP-2 framework for global ocean–sea-ice model simulations is assessed by comparing multi-model means from 11 CMIP6-class global ocean–sea-ice models calculated separately for the OMIP-1 and OMIP-2 simulations. Many features are very similar between OMIP-1 and OMIP-2 simulations, and yet key improvements in transitioning from OMIP-1 to OMIP-2 are also identified. Thus, the present assessment justifies that future ocean–sea-ice model development and analysis studies use the OMIP-2 framework.
Robert J. Allen, Steven Turnock, Pierre Nabat, David Neubauer, Ulrike Lohmann, Dirk Olivié, Naga Oshima, Martine Michou, Tongwen Wu, Jie Zhang, Toshihiko Takemura, Michael Schulz, Kostas Tsigaridis, Susanne E. Bauer, Louisa Emmons, Larry Horowitz, Vaishali Naik, Twan van Noije, Tommi Bergman, Jean-Francois Lamarque, Prodromos Zanis, Ina Tegen, Daniel M. Westervelt, Philippe Le Sager, Peter Good, Sungbo Shim, Fiona O'Connor, Dimitris Akritidis, Aristeidis K. Georgoulias, Makoto Deushi, Lori T. Sentman, Jasmin G. John, Shinichiro Fujimori, and William J. Collins
Atmos. Chem. Phys., 20, 9641–9663, https://doi.org/10.5194/acp-20-9641-2020, https://doi.org/10.5194/acp-20-9641-2020, 2020
Claudine Hauri, Cristina Schultz, Katherine Hedstrom, Seth Danielson, Brita Irving, Scott C. Doney, Raphael Dussin, Enrique N. Curchitser, David F. Hill, and Charles A. Stock
Biogeosciences, 17, 3837–3857, https://doi.org/10.5194/bg-17-3837-2020, https://doi.org/10.5194/bg-17-3837-2020, 2020
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The coastal ecosystem of the Gulf of Alaska (GOA) is especially vulnerable to the effects of ocean acidification and climate change. To improve our conceptual understanding of the system, we developed a new regional biogeochemical model setup for the GOA. Model output suggests that bottom water is seasonally high in CO2 between June and January. Such extensive periods of reoccurring high CO2 may be harmful to ocean acidification-sensitive organisms.
Lester Kwiatkowski, Olivier Torres, Laurent Bopp, Olivier Aumont, Matthew Chamberlain, James R. Christian, John P. Dunne, Marion Gehlen, Tatiana Ilyina, Jasmin G. John, Andrew Lenton, Hongmei Li, Nicole S. Lovenduski, James C. Orr, Julien Palmieri, Yeray Santana-Falcón, Jörg Schwinger, Roland Séférian, Charles A. Stock, Alessandro Tagliabue, Yohei Takano, Jerry Tjiputra, Katsuya Toyama, Hiroyuki Tsujino, Michio Watanabe, Akitomo Yamamoto, Andrew Yool, and Tilo Ziehn
Biogeosciences, 17, 3439–3470, https://doi.org/10.5194/bg-17-3439-2020, https://doi.org/10.5194/bg-17-3439-2020, 2020
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We assess 21st century projections of marine biogeochemistry in the CMIP6 Earth system models. These models represent the most up-to-date understanding of climate change. The models generally project greater surface ocean warming, acidification, subsurface deoxygenation, and euphotic nitrate reductions but lesser primary production declines than the previous generation of models. This has major implications for the impact of anthropogenic climate change on marine ecosystems.
Fabian A. Gomez, Rik Wanninkhof, Leticia Barbero, Sang-Ki Lee, and Frank J. Hernandez Jr.
Biogeosciences, 17, 1685–1700, https://doi.org/10.5194/bg-17-1685-2020, https://doi.org/10.5194/bg-17-1685-2020, 2020
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We use a numerical model to infer annual changes of surface carbon chemistry in the Gulf of Mexico (GoM). The main seasonality drivers of partial pressure of carbon dioxide and aragonite saturation state from the model are temperature and river runoff. The GoM basin is a carbon sink in winter–spring and carbon source in summer–fall, but uptake prevails near the Mississippi Delta year-round due to high biological production. Our model results show good correspondence with observational studies.
Pierre Friedlingstein, Matthew W. Jones, Michael O'Sullivan, Robbie M. Andrew, Judith Hauck, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Corinne Le Quéré, Dorothee C. E. Bakker, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Peter Anthoni, Leticia Barbero, Ana Bastos, Vladislav Bastrikov, Meike Becker, Laurent Bopp, Erik Buitenhuis, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Kim I. Currie, Richard A. Feely, Marion Gehlen, Dennis Gilfillan, Thanos Gkritzalis, Daniel S. Goll, Nicolas Gruber, Sören Gutekunst, Ian Harris, Vanessa Haverd, Richard A. Houghton, George Hurtt, Tatiana Ilyina, Atul K. Jain, Emilie Joetzjer, Jed O. Kaplan, Etsushi Kato, Kees Klein Goldewijk, Jan Ivar Korsbakken, Peter Landschützer, Siv K. Lauvset, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Danica Lombardozzi, Gregg Marland, Patrick C. McGuire, Joe R. Melton, Nicolas Metzl, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Craig Neill, Abdirahman M. Omar, Tsuneo Ono, Anna Peregon, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Roland Séférian, Jörg Schwinger, Naomi Smith, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco N. Tubiello, Guido R. van der Werf, Andrew J. Wiltshire, and Sönke Zaehle
Earth Syst. Sci. Data, 11, 1783–1838, https://doi.org/10.5194/essd-11-1783-2019, https://doi.org/10.5194/essd-11-1783-2019, 2019
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The Global Carbon Budget 2019 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.
Katja Fennel, Simone Alin, Leticia Barbero, Wiley Evans, Timothée Bourgeois, Sarah Cooley, John Dunne, Richard A. Feely, Jose Martin Hernandez-Ayon, Xinping Hu, Steven Lohrenz, Frank Muller-Karger, Raymond Najjar, Lisa Robbins, Elizabeth Shadwick, Samantha Siedlecki, Nadja Steiner, Adrienne Sutton, Daniela Turk, Penny Vlahos, and Zhaohui Aleck Wang
Biogeosciences, 16, 1281–1304, https://doi.org/10.5194/bg-16-1281-2019, https://doi.org/10.5194/bg-16-1281-2019, 2019
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We review and synthesize available information on coastal ocean carbon fluxes around North America (NA). There is overwhelming evidence, compiled and discussed here, that the NA coastal margins act as a sink. Our synthesis shows the great diversity in processes driving carbon fluxes in different coastal regions, highlights remaining gaps in observations and models, and discusses current and anticipated future trends with respect to carbon fluxes and acidification.
Riley X. Brady, Nicole S. Lovenduski, Michael A. Alexander, Michael Jacox, and Nicolas Gruber
Biogeosciences, 16, 329–346, https://doi.org/10.5194/bg-16-329-2019, https://doi.org/10.5194/bg-16-329-2019, 2019
Corinne Le Quéré, Robbie M. Andrew, Pierre Friedlingstein, Stephen Sitch, Judith Hauck, Julia Pongratz, Penelope A. Pickers, Jan Ivar Korsbakken, Glen P. Peters, Josep G. Canadell, Almut Arneth, Vivek K. Arora, Leticia Barbero, Ana Bastos, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Philippe Ciais, Scott C. Doney, Thanos Gkritzalis, Daniel S. Goll, Ian Harris, Vanessa Haverd, Forrest M. Hoffman, Mario Hoppema, Richard A. Houghton, George Hurtt, Tatiana Ilyina, Atul K. Jain, Truls Johannessen, Chris D. Jones, Etsushi Kato, Ralph F. Keeling, Kees Klein Goldewijk, Peter Landschützer, Nathalie Lefèvre, Sebastian Lienert, Zhu Liu, Danica Lombardozzi, Nicolas Metzl, David R. Munro, Julia E. M. S. Nabel, Shin-ichiro Nakaoka, Craig Neill, Are Olsen, Tsueno Ono, Prabir Patra, Anna Peregon, Wouter Peters, Philippe Peylin, Benjamin Pfeil, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Matthias Rocher, Christian Rödenbeck, Ute Schuster, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Tobias Steinhoff, Adrienne Sutton, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco N. Tubiello, Ingrid T. van der Laan-Luijkx, Guido R. van der Werf, Nicolas Viovy, Anthony P. Walker, Andrew J. Wiltshire, Rebecca Wright, Sönke Zaehle, and Bo Zheng
Earth Syst. Sci. Data, 10, 2141–2194, https://doi.org/10.5194/essd-10-2141-2018, https://doi.org/10.5194/essd-10-2141-2018, 2018
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The Global Carbon Budget 2018 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.
Fabian A. Gomez, Sang-Ki Lee, Yanyun Liu, Frank J. Hernandez Jr., Frank E. Muller-Karger, and John T. Lamkin
Biogeosciences, 15, 3561–3576, https://doi.org/10.5194/bg-15-3561-2018, https://doi.org/10.5194/bg-15-3561-2018, 2018
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Seasonal patterns in nanophytoplankton and diatom biomass in the Gulf of Mexico were examined with an ocean–biogeochemical model. We found silica limitation of model diatom growth in the deep GoM and Mississippi delta. Zooplankton grazing and both transport and vertical mixing of biomass substantially influence the model phytoplankton biomass seasonality. We stress the need for integrated analyses of biologically and physically driven biomass fluxes to describe phytoplankton seasonal changes.
Jaime B. Palter, Thomas L. Frölicher, David Paynter, and Jasmin G. John
Earth Syst. Dynam., 9, 817–828, https://doi.org/10.5194/esd-9-817-2018, https://doi.org/10.5194/esd-9-817-2018, 2018
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Limiting global warming to 1.5 °C may require carbon removal from the atmosphere. We explore how the climate system differs when we achieve the 1.5 °C limit by rapid emissions reductions versus when we overshoot this limit, hitting 2 °C at mid-century before removing CO2 from the atmosphere. We show that sea level, ocean acidification, regional warming, and ocean circulation are very different under the overshoot pathway at 2100, despite hitting the 1.5 °C target for surface warming.
Derek P. Tittensor, Tyler D. Eddy, Heike K. Lotze, Eric D. Galbraith, William Cheung, Manuel Barange, Julia L. Blanchard, Laurent Bopp, Andrea Bryndum-Buchholz, Matthias Büchner, Catherine Bulman, David A. Carozza, Villy Christensen, Marta Coll, John P. Dunne, Jose A. Fernandes, Elizabeth A. Fulton, Alistair J. Hobday, Veronika Huber, Simon Jennings, Miranda Jones, Patrick Lehodey, Jason S. Link, Steve Mackinson, Olivier Maury, Susa Niiranen, Ricardo Oliveros-Ramos, Tilla Roy, Jacob Schewe, Yunne-Jai Shin, Tiago Silva, Charles A. Stock, Jeroen Steenbeek, Philip J. Underwood, Jan Volkholz, James R. Watson, and Nicola D. Walker
Geosci. Model Dev., 11, 1421–1442, https://doi.org/10.5194/gmd-11-1421-2018, https://doi.org/10.5194/gmd-11-1421-2018, 2018
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Model intercomparison studies in the climate and Earth sciences communities have been crucial for strengthening future projections. Given the speed and magnitude of anthropogenic change in the marine environment, the time is ripe for similar comparisons among models of fisheries and marine ecosystems. We describe the Fisheries and Marine Ecosystem Model Intercomparison Project, which brings together the marine ecosystem modelling community to inform long-term projections of marine ecosystems.
Alizée Roobaert, Goulven G. Laruelle, Peter Landschützer, and Pierre Regnier
Biogeosciences, 15, 1701–1720, https://doi.org/10.5194/bg-15-1701-2018, https://doi.org/10.5194/bg-15-1701-2018, 2018
Giuliana Turi, Michael Alexander, Nicole S. Lovenduski, Antonietta Capotondi, James Scott, Charles Stock, John Dunne, Jasmin John, and Michael Jacox
Ocean Sci., 14, 69–86, https://doi.org/10.5194/os-14-69-2018, https://doi.org/10.5194/os-14-69-2018, 2018
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A high-resolution global model was used to study the influence of El Niño/La Niña events on the California Current System (CalCS). The mean surface oxygen (O2) response extends well offshore, where the pH response occurs within ~ 100 km of the coast. The surface O2 (pH) is primarily driven by temperature (upwelling) changes. Below 100 m, anomalously low O2 and low pH occurred during La Niña events near the coast, potentially stressing the ecosystem, but there are large variations between events.
James C. Orr, Raymond G. Najjar, Olivier Aumont, Laurent Bopp, John L. Bullister, Gokhan Danabasoglu, Scott C. Doney, John P. Dunne, Jean-Claude Dutay, Heather Graven, Stephen M. Griffies, Jasmin G. John, Fortunat Joos, Ingeborg Levin, Keith Lindsay, Richard J. Matear, Galen A. McKinley, Anne Mouchet, Andreas Oschlies, Anastasia Romanou, Reiner Schlitzer, Alessandro Tagliabue, Toste Tanhua, and Andrew Yool
Geosci. Model Dev., 10, 2169–2199, https://doi.org/10.5194/gmd-10-2169-2017, https://doi.org/10.5194/gmd-10-2169-2017, 2017
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The Ocean Model Intercomparison Project (OMIP) is a model comparison effort under Phase 6 of the Coupled Model Intercomparison Project (CMIP6). Its physical component is described elsewhere in this special issue. Here we describe its ocean biogeochemical component (OMIP-BGC), detailing simulation protocols and analysis diagnostics. Simulations focus on ocean carbon, other biogeochemical tracers, air-sea exchange of CO2 and related gases, and chemical tracers used to evaluate modeled circulation.
Venkatramani Balaji, Eric Maisonnave, Niki Zadeh, Bryan N. Lawrence, Joachim Biercamp, Uwe Fladrich, Giovanni Aloisio, Rusty Benson, Arnaud Caubel, Jeffrey Durachta, Marie-Alice Foujols, Grenville Lister, Silvia Mocavero, Seth Underwood, and Garrett Wright
Geosci. Model Dev., 10, 19–34, https://doi.org/10.5194/gmd-10-19-2017, https://doi.org/10.5194/gmd-10-19-2017, 2017
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Climate models are among the most computationally expensive scientific applications in the world. We present a set of measures of computational performance that can be used to compare models that are independent of underlying hardware and the model formulation. They are easy to collect and reflect performance actually achieved in practice. We are preparing a systematic effort to collect these metrics for the world's climate models during CMIP6, the next Climate Model Intercomparison Project.
Stephen M. Griffies, Gokhan Danabasoglu, Paul J. Durack, Alistair J. Adcroft, V. Balaji, Claus W. Böning, Eric P. Chassignet, Enrique Curchitser, Julie Deshayes, Helge Drange, Baylor Fox-Kemper, Peter J. Gleckler, Jonathan M. Gregory, Helmuth Haak, Robert W. Hallberg, Patrick Heimbach, Helene T. Hewitt, David M. Holland, Tatiana Ilyina, Johann H. Jungclaus, Yoshiki Komuro, John P. Krasting, William G. Large, Simon J. Marsland, Simona Masina, Trevor J. McDougall, A. J. George Nurser, James C. Orr, Anna Pirani, Fangli Qiao, Ronald J. Stouffer, Karl E. Taylor, Anne Marie Treguier, Hiroyuki Tsujino, Petteri Uotila, Maria Valdivieso, Qiang Wang, Michael Winton, and Stephen G. Yeager
Geosci. Model Dev., 9, 3231–3296, https://doi.org/10.5194/gmd-9-3231-2016, https://doi.org/10.5194/gmd-9-3231-2016, 2016
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The Ocean Model Intercomparison Project (OMIP) aims to provide a framework for evaluating, understanding, and improving the ocean and sea-ice components of global climate and earth system models contributing to the Coupled Model Intercomparison Project Phase 6 (CMIP6). This document defines OMIP and details a protocol both for simulating global ocean/sea-ice models and for analysing their output.
Chris D. Jones, Vivek Arora, Pierre Friedlingstein, Laurent Bopp, Victor Brovkin, John Dunne, Heather Graven, Forrest Hoffman, Tatiana Ilyina, Jasmin G. John, Martin Jung, Michio Kawamiya, Charlie Koven, Julia Pongratz, Thomas Raddatz, James T. Randerson, and Sönke Zaehle
Geosci. Model Dev., 9, 2853–2880, https://doi.org/10.5194/gmd-9-2853-2016, https://doi.org/10.5194/gmd-9-2853-2016, 2016
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How the carbon cycle interacts with climate will affect future climate change and how society plans emissions reductions to achieve climate targets. The Coupled Climate Carbon Cycle Model Intercomparison Project (C4MIP) is an endorsed activity of CMIP6 and aims to quantify these interactions and feedbacks in state-of-the-art climate models. This paper lays out the experimental protocol for modelling groups to follow to contribute to C4MIP. It is a contribution to the CMIP6 GMD Special Issue.
Charlotte Laufkötter, Meike Vogt, Nicolas Gruber, Olivier Aumont, Laurent Bopp, Scott C. Doney, John P. Dunne, Judith Hauck, Jasmin G. John, Ivan D. Lima, Roland Seferian, and Christoph Völker
Biogeosciences, 13, 4023–4047, https://doi.org/10.5194/bg-13-4023-2016, https://doi.org/10.5194/bg-13-4023-2016, 2016
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We compare future projections in marine export production, generated by four ecosystem models under IPCC's high-emission scenario RCP8.5. While all models project decreases in export, they differ strongly regarding the drivers. The formation of sinking particles of organic matter is the most uncertain process with models not agreeing on either magnitude or the direction of change. Changes in diatom concentration are a strong driver for export in some models but of low significance in others.
C. Laufkötter, M. Vogt, N. Gruber, M. Aita-Noguchi, O. Aumont, L. Bopp, E. Buitenhuis, S. C. Doney, J. Dunne, T. Hashioka, J. Hauck, T. Hirata, J. John, C. Le Quéré, I. D. Lima, H. Nakano, R. Seferian, I. Totterdell, M. Vichi, and C. Völker
Biogeosciences, 12, 6955–6984, https://doi.org/10.5194/bg-12-6955-2015, https://doi.org/10.5194/bg-12-6955-2015, 2015
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We analyze changes in marine net primary production (NPP) and its drivers for the 21st century in 9 marine ecosystem models under the RCP8.5 scenario. NPP decreases in 5 models and increases in 1 model; 3 models show no significant trend. The main drivers include stronger nutrient limitation, but in many models warming-induced increases in phytoplankton growth outbalance the nutrient effect. Temperature-driven increases in grazing and other loss processes cause a net decrease in biomass and NPP.
C. A. Stock, J. P. Dunne, and J. G. John
Biogeosciences, 11, 7125–7135, https://doi.org/10.5194/bg-11-7125-2014, https://doi.org/10.5194/bg-11-7125-2014, 2014
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Climate change projections suggest large regional ocean productivity shifts for mesozooplankton, an important food resource for fish, which are amplified relative to changes in phytoplankton production. Amplification is attributed to changes in planktonic food web dynamics under global warming. Results have implications for regional economies and food security. Improved understanding of the response of plankton food webs to climate change is essential to refine amplification estimates.
J. G. John, A. M. Fiore, V. Naik, L. W. Horowitz, and J. P. Dunne
Atmos. Chem. Phys., 12, 12021–12036, https://doi.org/10.5194/acp-12-12021-2012, https://doi.org/10.5194/acp-12-12021-2012, 2012
Related subject area
Oceanography
GREAT v1.0: Global Real-time Early Assessment of Tsunamis
Using automatic calibration to improve the physics behind complex numerical models: an example from a 3D lake model using Delft3D (v6.02.10) and DYNO-PODS (v1.0)
Improvements to the Met Office's global ocean–sea ice forecasting system including model and data assimilation changes
Resolution dependence of interlinked Southern Ocean biases in global coupled HadGEM3 models
A new global high-resolution wave model for the tropical ocean using WAVEWATCH III version 7.14
sedInterFoam 1.0: a three-phase numerical model for sediment transport applications with free surfaces
The Ross Sea and Amundsen Sea Ice–Sea Model (RAISE v1.0): a high-resolution ocean–sea ice–ice shelf coupling model for simulating the Dense Shelf Water and Antarctic Bottom Water in the Ross Sea, Antarctica
Sensitivity of the tropical Atlantic to vertical mixing in two ocean models (ICON-O v2.6.6 and FESOM v2.5)
HIDRA3: a deep-learning model for multipoint ensemble sea level forecasting in the presence of tide gauge sensor failures
A wave-resolving two-dimensional vertical Lagrangian approach to model microplastic transport in nearshore waters based on TrackMPD 3.0
HOTSSea v1: a NEMO-based physical Hindcast of the Salish Sea (1980–2018) supporting ecosystem model development
Comparing an idealized deterministic-stochastic model (SUP model, version 1) of the tide-and-wind driven sea surface currents in the Gulf of Trieste to HF Radar observations
ISWFM-NSCS v2.0: advancing the internal solitary wave forecasting model with background currents and horizontally inhomogeneous stratifications
Impacts of CICE sea ice model and ERA atmosphere on an Antarctic MetROMS ocean model, MetROMS-UHel-v1.0
DalROMS-NWA12 v1.0, a coupled circulation–ice–biogeochemistry modelling system for the northwest Atlantic Ocean: development and validation
A revised ocean mixed layer model for better simulating the diurnal variation in ocean skin temperature
Evaluating an accelerated forcing approach for improving computational efficiency in coupled ice sheet–ocean modelling
An optimal transformation method for inferring ocean tracer sources and sinks
Data-driven rolling model for global wave height
PPCon 1.0: Biogeochemical-Argo profile prediction with 1D convolutional networks
Wave forecast investigations on downscaling, source terms, and tides for Aotearoa New Zealand
An Effective Communication Topology for Performance Optimization: A Case Study of the Finite Volume WAve Modeling (FVWAM)
Experimental design for the Marine Ice Sheet–Ocean Model Intercomparison Project – phase 2 (MISOMIP2)
Development of a total variation diminishing (TVD) sea ice transport scheme and its application in an ocean (SCHISM v5.11) and sea ice (Icepack v1.3.4) coupled model on unstructured grids
Spurious numerical mixing under strong tidal forcing: a case study in the south-east Asian seas using the Symphonie model (v3.1.2)
Modelling the water isotope distribution in the Mediterranean Sea using a high-resolution oceanic model (NEMO-MED12-watiso v1.0): evaluation of model results against in situ observations
LIGHT-bgcArgo-1.0: using synthetic float capabilities in E3SMv2 to assess spatiotemporal variability in ocean physics and biogeochemistry
PIBM 1.0: An individual-based model for simulating phytoplankton acclimation, diversity, and evolution in the ocean
Towards a real-time modeling of global ocean waves by the fully GPU-accelerated spectral wave model WAM6-GPU v1.0
A simple approach to represent precipitation-derived freshwater fluxes into nearshore ocean models: an FVCOM4.1 case study of Quatsino Sound, British Columbia
An optimal transformation method applied to diagnose the ocean carbon budget
Implementation and assessment of a model including mixotrophs and the carbonate cycle (Eco3M_MIX-CarbOx v1.0) in a highly dynamic Mediterranean coastal environment (Bay of Marseille, France) – Part 2: Towards a better representation of total alkalinity when modeling the carbonate system and air–sea CO2 fluxes
Development of a novel storm surge inundation model framework for efficient prediction
Skin sea surface temperature schemes in coupled ocean–atmosphere modelling: the impact of chlorophyll-interactive e-folding depth
DELWAVE 1.0: deep learning surrogate model of surface wave climate in the Adriatic Basin
StraitFlux – precise computations of water strait fluxes on various modeling grids
Comparison of the Coastal and Regional Ocean COmmunity model (CROCO) and NCAR-LES in non-hydrostatic simulations
Intercomparisons of Tracker v1.1 and four other ocean particle-tracking software packages in the Regional Ocean Modeling System
CAR36, a regional high-resolution ocean forecasting system for improving drift and beaching of Sargassum in the Caribbean archipelago
Implementation of additional spectral wave field exchanges in a three-dimensional wave–current coupled WAVEWATCH-III (version 6.07) and CROCO (version 1.2) configuration: assessment of their implications for macro-tidal coastal hydrodynamics
Comparison of 4-dimensional variational and ensemble optimal interpolation data assimilation systems using a Regional Ocean Modeling System (v3.4) configuration of the eddy-dominated East Australian Current system
LOCATE v1.0: numerical modelling of floating marine debris dispersion in coastal regions using Parcels v2.4.2
New insights into the South China Sea throughflow and water budget seasonal cycle: evaluation and analysis of a high-resolution configuration of the ocean model SYMPHONIE version 2.4
MQGeometry-1.0: a multi-layer quasi-geostrophic solver on non-rectangular geometries
Parameter estimation for ocean background vertical diffusivity coefficients in the Community Earth System Model (v1.2.1) and its impact on El Niño–Southern Oscillation forecasts
Great Lakes wave forecast system on high-resolution unstructured meshes
Impact of increased resolution on Arctic Ocean simulations in Ocean Model Intercomparison Project phase 2 (OMIP-2)
A flexible z-layers approach for the accurate representation of free surface flows in a coastal ocean model (SHYFEM v. 7_5_71)
Implementation and assessment of a model including mixotrophs and the carbonate cycle (Eco3M_MIX-CarbOx v1.0) in a highly dynamic Mediterranean coastal environment (Bay of Marseille, France) – Part 1: Evolution of ecosystem composition under limited light and nutrient conditions
Ocean wave tracing v.1: a numerical solver of the wave ray equations for ocean waves on variable currents at arbitrary depths
Usama Kadri, Ali Abdolali, and Maxim Filimonov
Geosci. Model Dev., 18, 3487–3507, https://doi.org/10.5194/gmd-18-3487-2025, https://doi.org/10.5194/gmd-18-3487-2025, 2025
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The GREAT v1.0 software introduces a novel tsunami warning technology for global real-time analysis. It leverages acoustic signals generated by tsunamis, which propagate faster than the tsunami itself, enabling real-time detection and assessment. Integrating various models, the software provides reliable and rapid assessment, maps risk areas, and estimates tsunami amplitude. This advancement reduces false alarms and enhances global tsunami warning systems' accuracy and efficiency.
Marina Amadori, Abolfazl Irani Rahaghi, Damien Bouffard, and Marco Toffolon
Geosci. Model Dev., 18, 3473–3486, https://doi.org/10.5194/gmd-18-3473-2025, https://doi.org/10.5194/gmd-18-3473-2025, 2025
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Models simplify reality using assumptions, which can sometimes introduce flaws and affect their accuracy. Properly calibrating model parameters is essential, and although automated tools can speed up this process, they may occasionally produce incorrect values due to inconsistencies in the model. We demonstrate that by carefully applying automated tools, we were able to identify and correct a flaw in a widely used model for lake environments.
Davi Mignac, Jennifer Waters, Daniel J. Lea, Matthew J. Martin, James While, Anthony T. Weaver, Arthur Vidard, Catherine Guiavarc'h, Dave Storkey, David Ford, Edward W. Blockley, Jonathan Baker, Keith Haines, Martin R. Price, Michael J. Bell, and Richard Renshaw
Geosci. Model Dev., 18, 3405–3425, https://doi.org/10.5194/gmd-18-3405-2025, https://doi.org/10.5194/gmd-18-3405-2025, 2025
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We describe major improvements of the Met Office's global ocean–sea ice forecasting system. The models and the way observations are used to improve the forecasts were changed, which led to a significant error reduction of 1 d forecasts. The new system performance in past conditions, where subsurface observations are scarce, was improved with more consistent ocean heat content estimates. The new system will be of better use for climate studies and will provide improved forecasts for end users.
David Storkey, Pierre Mathiot, Michael J. Bell, Dan Copsey, Catherine Guiavarc'h, Helene T. Hewitt, Jeff Ridley, and Malcolm J. Roberts
Geosci. Model Dev., 18, 2725–2745, https://doi.org/10.5194/gmd-18-2725-2025, https://doi.org/10.5194/gmd-18-2725-2025, 2025
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The Southern Ocean is a key region of the world ocean in the context of climate change studies. We show that the Met Office Hadley Centre coupled model with intermediate ocean resolution struggles to accurately simulate the Southern Ocean. Increasing the frictional drag that the seafloor exerts on ocean currents and introducing a representation of unresolved ocean eddies both appear to reduce the large-scale biases in this model.
Axelle Gaffet, Xavier Bertin, Damien Sous, Héloïse Michaud, Aron Roland, and Emmanuel Cordier
Geosci. Model Dev., 18, 1929–1946, https://doi.org/10.5194/gmd-18-1929-2025, https://doi.org/10.5194/gmd-18-1929-2025, 2025
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This study presents a new global wave model that improves predictions of sea states in tropical areas by using a high-resolution grid and corrected wind fields. The model is validated globally with satellite data and nearshore using in situ data. The model allows for the first time direct comparisons with in situ data collected at 10–30 m water depth, which is very close to shore due to the steep slope usually surrounding volcanic islands.
Antoine Mathieu, Yeulwoo Kim, Tian-Jian Hsu, Cyrille Bonamy, and Julien Chauchat
Geosci. Model Dev., 18, 1561–1573, https://doi.org/10.5194/gmd-18-1561-2025, https://doi.org/10.5194/gmd-18-1561-2025, 2025
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Most of the tools available to model sediment transport do not account for complex physical mechanisms such as surface-wave-driven processes. In this study, a new model, sedInterFoam, allows us to reproduce numerically complex configurations in order to investigate coastal sediment transport applications dominated by surface waves and to gain insight into the complex physical processes associated with breaking waves and morphodynamics.
Zhaoru Zhang, Chuan Xie, Chuning Wang, Yuanjie Chen, Heng Hu, and Xiaoqiao Wang
Geosci. Model Dev., 18, 1375–1393, https://doi.org/10.5194/gmd-18-1375-2025, https://doi.org/10.5194/gmd-18-1375-2025, 2025
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A coupled fine-resolution ocean–ice model is developed for the Ross Sea and adjacent regions in Antarctica, a key area for the formation of global ocean bottom water, the Antarctic Bottom Water (AABW), which affects global ocean circulation. The model has a high skill level in simulating sea ice production driving the AABW source water formation and AABW properties when assessed against observations. A model experiment shows a significant impact of ice shelf melting on the AABW characteristics.
Swantje Bastin, Aleksei Koldunov, Florian Schütte, Oliver Gutjahr, Marta Agnieszka Mrozowska, Tim Fischer, Radomyra Shevchenko, Arjun Kumar, Nikolay Koldunov, Helmuth Haak, Nils Brüggemann, Rebecca Hummels, Mia Sophie Specht, Johann Jungclaus, Sergey Danilov, Marcus Dengler, and Markus Jochum
Geosci. Model Dev., 18, 1189–1220, https://doi.org/10.5194/gmd-18-1189-2025, https://doi.org/10.5194/gmd-18-1189-2025, 2025
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Vertical mixing is an important process, for example, for tropical sea surface temperature, but cannot be resolved by ocean models. Comparisons of mixing schemes and settings have usually been done with a single model, sometimes yielding conflicting results. We systematically compare two widely used schemes with different parameter settings in two different ocean models and show that most effects from mixing scheme parameter changes are model-dependent.
Marko Rus, Hrvoje Mihanović, Matjaž Ličer, and Matej Kristan
Geosci. Model Dev., 18, 605–620, https://doi.org/10.5194/gmd-18-605-2025, https://doi.org/10.5194/gmd-18-605-2025, 2025
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HIDRA3 is a deep-learning model for predicting sea levels and storm surges, offering significant improvements over previous models and numerical simulations. It utilizes data from multiple tide gauges, enhancing predictions even with limited historical data and during sensor outages. With its advanced architecture, HIDRA3 outperforms current state-of-the-art models by achieving a mean absolute error of up to 15 % lower, proving effective for coastal flood forecasting under diverse conditions.
Isabel Jalón-Rojas, Damien Sous, and Vincent Marieu
Geosci. Model Dev., 18, 319–336, https://doi.org/10.5194/gmd-18-319-2025, https://doi.org/10.5194/gmd-18-319-2025, 2025
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This study presents a novel modeling approach for understanding microplastic transport in coastal waters. The model accurately replicates experimental data and reveals key transport mechanisms. The findings enhance our knowledge of how microplastics move in nearshore environments, aiding in coastal management and efforts to combat plastic pollution globally.
Greig Oldford, Tereza Jarníková, Villy Christensen, and Michael Dunphy
Geosci. Model Dev., 18, 211–237, https://doi.org/10.5194/gmd-18-211-2025, https://doi.org/10.5194/gmd-18-211-2025, 2025
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We developed a 3D ocean model called the Hindcast of the Salish Sea (HOTSSea v1) that recreates physical conditions throughout the Salish Sea from 1980 to 2018. It was not clear that acceptable accuracy could be achieved because of computational and data limitations, but the model's predictions agreed well with observations. When we used the model to examine ocean temperature trends in areas that lack observations, it indicated that some seasons and areas are warming faster than others.
Sofia Flora, Laura Ursella, and Achim Wirth
EGUsphere, https://doi.org/10.5194/egusphere-2024-3391, https://doi.org/10.5194/egusphere-2024-3391, 2025
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We developed a hierarchy of idealized deterministic-stochastic models to simulate the sea surface currents in the Gulf of Trieste. They include tide-and-wind driven sea surface current components, resolving the slowly varying part of the flow and a stochastic signal, representing the fast-varying small-scale dynamics. The comparison with High Frequency Radar observations shows that the non-Gaussian stochastic model captures the essential dynamics and permits to mimic the observed fat-tailed PDF.
Yankun Gong, Xueen Chen, Jiexin Xu, Zhiwu Chen, Qingyou He, Ruixiang Zhao, Xiao-Hua Zhu, and Shuqun Cai
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-165, https://doi.org/10.5194/gmd-2024-165, 2024
Revised manuscript accepted for GMD
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A new internal solitary wave forecasting (ISW) model in the northern South China Sea (ISWFM-NSCS v2.0) improves ISW predictions by incorporating background currents and inhomogeneous stratifications. Additionally, viscosity and diffusivity coefficients are optimized to maintain stable stratifications, extending the forecasting period. Sensitivity experiments illustrate that ISWFM-NSCS v2.0 significantly enhances predictions of various wave properties.
Cecilia Äijälä, Yafei Nie, Lucía Gutiérrez-Loza, Chiara De Falco, Siv Kari Lauvset, Bin Cheng, David A. Bailey, and Petteri Uotila
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-213, https://doi.org/10.5194/gmd-2024-213, 2024
Revised manuscript accepted for GMD
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The sea ice around Antarctica has experienced record lows in recent years. To understand these changes, models are needed. MetROMS-UHel is a new version of an ocean–sea ice model with updated sea ice code and the atmospheric data. We investigate the effect of our updates on different variables with a focus on sea ice and show an improved sea ice representation as compared with observations.
Kyoko Ohashi, Arnaud Laurent, Christoph Renkl, Jinyu Sheng, Katja Fennel, and Eric Oliver
Geosci. Model Dev., 17, 8697–8733, https://doi.org/10.5194/gmd-17-8697-2024, https://doi.org/10.5194/gmd-17-8697-2024, 2024
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We developed a modelling system of the northwest Atlantic Ocean that simulates the currents, temperature, salinity, and parts of the biochemical cycle of the ocean, as well as sea ice. The system combines advanced, open-source models and can be used to study, for example, the ocean capture of atmospheric carbon dioxide, which is a key process in the global climate. The system produces realistic results, and we use it to investigate the roles of tides and sea ice in the northwest Atlantic Ocean.
Eui-Jong Kang, Byung-Ju Sohn, Sang-Woo Kim, Wonho Kim, Young-Cheol Kwon, Seung-Bum Kim, Hyoung-Wook Chun, and Chao Liu
Geosci. Model Dev., 17, 8553–8568, https://doi.org/10.5194/gmd-17-8553-2024, https://doi.org/10.5194/gmd-17-8553-2024, 2024
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Sea surface temperature (SST) is vital in climate, weather, and ocean sciences because it influences air–sea interactions. Errors in the ECMWF model's scheme for predicting ocean skin temperature prompted a revision of the ocean mixed layer model. Validation against infrared measurements and buoys showed a good correlation with minimal deviations. The revised model accurately simulates SST variations and aligns with solar radiation distributions, showing promise for weather and climate models.
Qin Zhou, Chen Zhao, Rupert Gladstone, Tore Hattermann, David Gwyther, and Benjamin Galton-Fenzi
Geosci. Model Dev., 17, 8243–8265, https://doi.org/10.5194/gmd-17-8243-2024, https://doi.org/10.5194/gmd-17-8243-2024, 2024
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We introduce an accelerated forcing approach to address timescale discrepancies between the ice sheets and ocean components in coupled modelling by reducing the ocean simulation duration. The approach is evaluated using idealized coupled models, and its limitations in real-world applications are discussed. Our results suggest it can be a valuable tool for process-oriented coupled ice sheet–ocean modelling and downscaling climate simulations with such models.
Jan D. Zika and Taimoor Sohail
Geosci. Model Dev., 17, 8049–8068, https://doi.org/10.5194/gmd-17-8049-2024, https://doi.org/10.5194/gmd-17-8049-2024, 2024
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We describe a method to relate fluxes of heat and freshwater at the sea surface to the resulting distribution of seawater among categories such as warm and salty or cold and salty. The method exploits the laws that govern how heat and salt change when water mixes. The method will allow the climate community to improve estimates of how much heat the ocean is absorbing and how rainfall and evaporation are changing across the globe.
Xinxin Wang, Jiuke Wang, Wenfang Lu, Changming Dong, Hao Qin, and Haoyu Jiang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-181, https://doi.org/10.5194/gmd-2024-181, 2024
Revised manuscript accepted for GMD
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Large-scale wave modeling is essential for science and society, typically relying on resource-intensive numerical methods to simulate wave dynamics. In this study, we introduce a rolling AI-based method for modeling global significant wave height. Our model achieves accuracy comparable to traditional numerical methods while significantly improving speed, making it operable on standard laptops. This work demonstrates AI's potential to enhance the accuracy and efficiency of global wave modeling.
Gloria Pietropolli, Luca Manzoni, and Gianpiero Cossarini
Geosci. Model Dev., 17, 7347–7364, https://doi.org/10.5194/gmd-17-7347-2024, https://doi.org/10.5194/gmd-17-7347-2024, 2024
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Monitoring the ocean is essential for studying marine life and human impact. Our new software, PPCon, uses ocean data to predict key factors like nitrate and chlorophyll levels, which are hard to measure directly. By leveraging machine learning, PPCon offers more accurate and efficient predictions.
Rafael Santana, Richard Gorman, Emily Lane, Stuart Moore, Cyprien Bosserelle, Glen Reeve, and Christo Rautenbach
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-110, https://doi.org/10.5194/gmd-2024-110, 2024
Revised manuscript accepted for GMD
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This research explores improving wave forecasts in New Zealand, particularly at Banks Peninsula and Baring Head. We used detailed models, finding that forecasts at Baring Head improved significantly due to its strong tidal currents, but changes at Banks Peninsula were minimal. The study demonstrates that local conditions greatly influence the effectiveness of wave prediction models, highlighting the need for tailored approaches in coastal forecasting to enhance accuracy in the predictions.
Renbo Pang, Fujiang Yu, Yuanyong Gao, Ye Yuan, Liang Yuan, and Zhiyi Gao
EGUsphere, https://doi.org/10.5194/egusphere-2024-2515, https://doi.org/10.5194/egusphere-2024-2515, 2024
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The application of the distributed graph communication topology in earth models has been rarely studied. We tested and compared this topology with the traditional point-to-point communication method using a global wave model. We found that this topology is more efficient. Additionally, using this topology can greatly improve the performance of the wave model and could help improve the performance of other earth models.
Jan De Rydt, Nicolas C. Jourdain, Yoshihiro Nakayama, Mathias van Caspel, Ralph Timmermann, Pierre Mathiot, Xylar S. Asay-Davis, Hélène Seroussi, Pierre Dutrieux, Ben Galton-Fenzi, David Holland, and Ronja Reese
Geosci. Model Dev., 17, 7105–7139, https://doi.org/10.5194/gmd-17-7105-2024, https://doi.org/10.5194/gmd-17-7105-2024, 2024
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Global climate models do not reliably simulate sea-level change due to ice-sheet–ocean interactions. We propose a community modelling effort to conduct a series of well-defined experiments to compare models with observations and study how models respond to a range of perturbations in climate and ice-sheet geometry. The second Marine Ice Sheet–Ocean Model Intercomparison Project will continue to lay the groundwork for including ice-sheet–ocean interactions in global-scale IPCC-class models.
Qian Wang, Yang Zhang, Fei Chai, Y. Joseph Zhang, and Lorenzo Zampieri
Geosci. Model Dev., 17, 7067–7081, https://doi.org/10.5194/gmd-17-7067-2024, https://doi.org/10.5194/gmd-17-7067-2024, 2024
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We coupled an unstructured hydro-model with an advanced column sea ice model to meet the growing demand for increased resolution and complexity in unstructured sea ice models. Additionally, we present a novel tracer transport scheme for the sea ice coupled model and demonstrate that this scheme fulfills the requirements for conservation, accuracy, efficiency, and monotonicity in an idealized test. Our new coupled model also has good performance in realistic tests.
Adrien Garinet, Marine Herrmann, Patrick Marsaleix, and Juliette Pénicaud
Geosci. Model Dev., 17, 6967–6986, https://doi.org/10.5194/gmd-17-6967-2024, https://doi.org/10.5194/gmd-17-6967-2024, 2024
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Mixing is a crucial aspect of the ocean, but its accurate representation in computer simulations is made challenging by errors that result in unwanted mixing, compromising simulation realism. Here we illustrate the spurious effect that tides can have on simulations of south-east Asia. Although they play an important role in determining the state of the ocean, they can increase numerical errors and make simulation outputs less realistic. We also provide insights into how to reduce these errors.
Mohamed Ayache, Jean-Claude Dutay, Anne Mouchet, Kazuyo Tachikawa, Camille Risi, and Gilles Ramstein
Geosci. Model Dev., 17, 6627–6655, https://doi.org/10.5194/gmd-17-6627-2024, https://doi.org/10.5194/gmd-17-6627-2024, 2024
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Water isotopes (δ18O, δD) are one of the most widely used proxies in ocean climate research. Previous studies using water isotope observations and modelling have highlighted the importance of understanding spatial and temporal isotopic variability for a quantitative interpretation of these tracers. Here we present the first results of a high-resolution regional dynamical model (at 1/12° horizontal resolution) developed for the Mediterranean Sea, one of the hotspots of ongoing climate change.
Cara Nissen, Nicole S. Lovenduski, Mathew Maltrud, Alison R. Gray, Yohei Takano, Kristen Falcinelli, Jade Sauvé, and Katherine Smith
Geosci. Model Dev., 17, 6415–6435, https://doi.org/10.5194/gmd-17-6415-2024, https://doi.org/10.5194/gmd-17-6415-2024, 2024
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Autonomous profiling floats have provided unprecedented observational coverage of the global ocean, but uncertainties remain about whether their sampling frequency and density capture the true spatiotemporal variability of physical, biogeochemical, and biological properties. Here, we present the novel synthetic biogeochemical float capabilities of the Energy Exascale Earth System Model version 2 and demonstrate their utility as a test bed to address these uncertainties.
Iria Sala and Bingzhang Chen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-130, https://doi.org/10.5194/gmd-2024-130, 2024
Revised manuscript accepted for GMD
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Phytoplankton, tiny photosynthetic organisms, produce nearly half of Earth's oxygen. To analyze their physiology, diversity, and evolution in the ocean, we developed a model that treats phytoplankton as individual particles. Moreover, our model considers phytoplankton size, temperature, and light traits, and allows for mutations in phytoplankton cells. Thus, our model provides a valuable tool for advancing the study of phytoplankton physiology, diversity, and evolution.
Ye Yuan, Fujiang Yu, Zhi Chen, Xueding Li, Fang Hou, Yuanyong Gao, Zhiyi Gao, and Renbo Pang
Geosci. Model Dev., 17, 6123–6136, https://doi.org/10.5194/gmd-17-6123-2024, https://doi.org/10.5194/gmd-17-6123-2024, 2024
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Accurate and timely forecasting of ocean waves is of great importance to the safety of marine transportation and offshore engineering. In this study, GPU-accelerated computing is introduced in WAve Modeling Cycle 6 (WAM6). With this effort, global high-resolution wave simulations can now run on GPUs up to tens of times faster than the currently available models can on a CPU node with results that are just as accurate.
Krysten Rutherford, Laura Bianucci, and William Floyd
Geosci. Model Dev., 17, 6083–6104, https://doi.org/10.5194/gmd-17-6083-2024, https://doi.org/10.5194/gmd-17-6083-2024, 2024
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Nearshore ocean models often lack complete information about freshwater fluxes due to numerous ungauged rivers and streams. We tested a simple rain-based hydrological model as inputs into an ocean model of Quatsino Sound, Canada, with the aim of improving the representation of the land–ocean connection in the nearshore model. Through multiple tests, we found that the performance of the ocean model improved when providing 60 % or more of the freshwater inputs from the simple runoff model.
Neill Mackay, Taimoor Sohail, Jan David Zika, Richard G. Williams, Oliver Andrews, and Andrew James Watson
Geosci. Model Dev., 17, 5987–6005, https://doi.org/10.5194/gmd-17-5987-2024, https://doi.org/10.5194/gmd-17-5987-2024, 2024
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The ocean absorbs carbon dioxide from the atmosphere, mitigating climate change, but estimates of the uptake do not always agree. There is a need to reconcile these differing estimates and to improve our understanding of ocean carbon uptake. We present a new method for estimating ocean carbon uptake and test it with model data. The method effectively diagnoses the ocean carbon uptake from limited data and therefore shows promise for reconciling different observational estimates.
Lucille Barré, Frédéric Diaz, Thibaut Wagener, Camille Mazoyer, Christophe Yohia, and Christel Pinazo
Geosci. Model Dev., 17, 5851–5882, https://doi.org/10.5194/gmd-17-5851-2024, https://doi.org/10.5194/gmd-17-5851-2024, 2024
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The carbonate system is typically studied using measurements, but modeling can contribute valuable insights. Using a biogeochemical model, we propose a new representation of total alkalinity, dissolved inorganic carbon, pCO2, and pH in a highly dynamic Mediterranean coastal area, the Bay of Marseille, a useful addition to measurements. Through a detailed analysis of pCO2 and air–sea CO2 fluxes, we show that variations are strongly impacted by the hydrodynamic processes that affect the bay.
Xuanxuan Gao, Shuiqing Li, Dongxue Mo, Yahao Liu, and Po Hu
Geosci. Model Dev., 17, 5497–5509, https://doi.org/10.5194/gmd-17-5497-2024, https://doi.org/10.5194/gmd-17-5497-2024, 2024
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Storm surges generate coastal inundation and expose populations and properties to danger. We developed a novel storm surge inundation model for efficient prediction. Estimates compare well with in situ measurements and results from a numerical model. The new model is a significant improvement on existing numerical models, with much higher computational efficiency and stability, which allows timely disaster prevention and mitigation.
Vincenzo de Toma, Daniele Ciani, Yassmin Hesham Essa, Chunxue Yang, Vincenzo Artale, Andrea Pisano, Davide Cavaliere, Rosalia Santoleri, and Andrea Storto
Geosci. Model Dev., 17, 5145–5165, https://doi.org/10.5194/gmd-17-5145-2024, https://doi.org/10.5194/gmd-17-5145-2024, 2024
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This study explores methods to reconstruct diurnal variations in skin sea surface temperature in a model of the Mediterranean Sea. Our new approach, considering chlorophyll concentration, enhances spatial and temporal variations in the warm layer. Comparative analysis shows context-dependent improvements. The proposed "chlorophyll-interactive" method brings the surface net total heat flux closer to zero annually, despite a net heat loss from the ocean to the atmosphere.
Peter Mlakar, Antonio Ricchi, Sandro Carniel, Davide Bonaldo, and Matjaž Ličer
Geosci. Model Dev., 17, 4705–4725, https://doi.org/10.5194/gmd-17-4705-2024, https://doi.org/10.5194/gmd-17-4705-2024, 2024
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We propose a new point-prediction model, the DEep Learning WAVe Emulating model (DELWAVE), which successfully emulates the Simulating WAves Nearshore model (SWAN) over synoptic to climate timescales. Compared to control climatology over all wind directions, the mismatch between DELWAVE and SWAN is generally small compared to the difference between scenario and control conditions, suggesting that the noise introduced by surrogate modelling is substantially weaker than the climate change signal.
Susanna Winkelbauer, Michael Mayer, and Leopold Haimberger
Geosci. Model Dev., 17, 4603–4620, https://doi.org/10.5194/gmd-17-4603-2024, https://doi.org/10.5194/gmd-17-4603-2024, 2024
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Oceanic transports shape the global climate, but the evaluation and validation of this key quantity based on reanalysis and model data are complicated by the distortion of the used modelling grids and the large number of different grid types. We present two new methods that allow the calculation of oceanic fluxes of volume, heat, salinity, and ice through almost arbitrary sections for various models and reanalyses that are independent of the used modelling grids.
Xiaoyu Fan, Baylor Fox-Kemper, Nobuhiro Suzuki, Qing Li, Patrick Marchesiello, Peter P. Sullivan, and Paul S. Hall
Geosci. Model Dev., 17, 4095–4113, https://doi.org/10.5194/gmd-17-4095-2024, https://doi.org/10.5194/gmd-17-4095-2024, 2024
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Simulations of the oceanic turbulent boundary layer using the nonhydrostatic CROCO ROMS and NCAR-LES models are compared. CROCO and the NCAR-LES are accurate in a similar manner, but CROCO’s additional features (e.g., nesting and realism) and its compressible turbulence formulation carry additional costs.
Jilian Xiong and Parker MacCready
Geosci. Model Dev., 17, 3341–3356, https://doi.org/10.5194/gmd-17-3341-2024, https://doi.org/10.5194/gmd-17-3341-2024, 2024
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The new offline particle tracking package, Tracker v1.1, is introduced to the Regional Ocean Modeling System, featuring an efficient nearest-neighbor algorithm to enhance particle-tracking speed. Its performance was evaluated against four other tracking packages and passive dye. Despite unique features, all packages yield comparable results. Running multiple packages within the same circulation model allows comparison of their performance and ease of use.
Sylvain Cailleau, Laurent Bessières, Léonel Chiendje, Flavie Dubost, Guillaume Reffray, Jean-Michel Lellouche, Simon van Gennip, Charly Régnier, Marie Drevillon, Marc Tressol, Matthieu Clavier, Julien Temple-Boyer, and Léo Berline
Geosci. Model Dev., 17, 3157–3173, https://doi.org/10.5194/gmd-17-3157-2024, https://doi.org/10.5194/gmd-17-3157-2024, 2024
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In order to improve Sargassum drift forecasting in the Caribbean area, drift models can be forced by higher-resolution ocean currents. To this goal a 3 km resolution regional ocean model has been developed. Its assessment is presented with a particular focus on the reproduction of fine structures representing key features of the Caribbean region dynamics and Sargassum transport. The simulated propagation of a North Brazil Current eddy and its dissipation was found to be quite realistic.
Gaetano Porcile, Anne-Claire Bennis, Martial Boutet, Sophie Le Bot, Franck Dumas, and Swen Jullien
Geosci. Model Dev., 17, 2829–2853, https://doi.org/10.5194/gmd-17-2829-2024, https://doi.org/10.5194/gmd-17-2829-2024, 2024
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Here a new method of modelling the interaction between ocean currents and waves is presented. We developed an advanced coupling of two models, one for ocean currents and one for waves. In previous couplings, some wave-related calculations were based on simplified assumptions. Our method uses more complex calculations to better represent wave–current interactions. We tested it in a macro-tidal coastal area and found that it significantly improves the model accuracy, especially during storms.
Colette Gabrielle Kerry, Moninya Roughan, Shane Keating, David Gwyther, Gary Brassington, Adil Siripatana, and Joao Marcos A. C. Souza
Geosci. Model Dev., 17, 2359–2386, https://doi.org/10.5194/gmd-17-2359-2024, https://doi.org/10.5194/gmd-17-2359-2024, 2024
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Ocean forecasting relies on the combination of numerical models and ocean observations through data assimilation (DA). Here we assess the performance of two DA systems in a dynamic western boundary current, the East Australian Current, across a common modelling and observational framework. We show that the more advanced, time-dependent method outperforms the time-independent method for forecast horizons of 5 d. This advocates the use of advanced methods for highly variable oceanic regions.
Ivan Hernandez, Leidy M. Castro-Rosero, Manuel Espino, and Jose M. Alsina Torrent
Geosci. Model Dev., 17, 2221–2245, https://doi.org/10.5194/gmd-17-2221-2024, https://doi.org/10.5194/gmd-17-2221-2024, 2024
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The LOCATE numerical model was developed to conduct Lagrangian simulations of the transport and dispersion of marine debris at coastal scales. High-resolution hydrodynamic data and a beaching module that used particle distance to the shore for land–water boundary detection were used on a realistic debris discharge scenario comparing hydrodynamic data at various resolutions. Coastal processes and complex geometric structures were resolved when using nested grids and distance-to-shore beaching.
Ngoc B. Trinh, Marine Herrmann, Caroline Ulses, Patrick Marsaleix, Thomas Duhaut, Thai To Duy, Claude Estournel, and R. Kipp Shearman
Geosci. Model Dev., 17, 1831–1867, https://doi.org/10.5194/gmd-17-1831-2024, https://doi.org/10.5194/gmd-17-1831-2024, 2024
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A high-resolution model was built to study the South China Sea (SCS) water, heat, and salt budgets. Model performance is demonstrated by comparison with observations and simulations. Important discards are observed if calculating offline, instead of online, lateral inflows and outflows of water, heat, and salt. The SCS mainly receives water from the Luzon Strait and releases it through the Mindoro, Taiwan, and Karimata straits. SCS surface interocean water exchanges are driven by monsoon winds.
Louis Thiry, Long Li, Guillaume Roullet, and Etienne Mémin
Geosci. Model Dev., 17, 1749–1764, https://doi.org/10.5194/gmd-17-1749-2024, https://doi.org/10.5194/gmd-17-1749-2024, 2024
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We present a new way of solving the quasi-geostrophic (QG) equations, a simple set of equations describing ocean dynamics. Our method is solely based on the numerical methods used to solve the equations and requires no parameter tuning. Moreover, it can handle non-rectangular geometries, opening the way to study QG equations on realistic domains. We release a PyTorch implementation to ease future machine-learning developments on top of the presented method.
Zheqi Shen, Yihao Chen, Xiaojing Li, and Xunshu Song
Geosci. Model Dev., 17, 1651–1665, https://doi.org/10.5194/gmd-17-1651-2024, https://doi.org/10.5194/gmd-17-1651-2024, 2024
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Parameter estimation is the process that optimizes model parameters using observations, which could reduce model errors and improve forecasting. In this study, we conducted parameter estimation experiments using the CESM and the ensemble adjustment Kalman filter. The obtained initial conditions and parameters are used to perform ensemble forecast experiments for ENSO forecasting. The results revealed that parameter estimation could reduce analysis errors and improve ENSO forecast skills.
Ali Abdolali, Saeideh Banihashemi, Jose Henrique Alves, Aron Roland, Tyler J. Hesser, Mary Anderson Bryant, and Jane McKee Smith
Geosci. Model Dev., 17, 1023–1039, https://doi.org/10.5194/gmd-17-1023-2024, https://doi.org/10.5194/gmd-17-1023-2024, 2024
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This article presents an overview of the development and implementation of Great Lake Wave Unstructured (GLWUv2.0), including the core model and workflow design and development. The validation was conducted against in situ data for the re-forecasted duration for summer and wintertime (ice season). The article describes the limitations and challenges encountered in the operational environment and the path forward for the next generation of wave forecast systems in enclosed basins like the GL.
Qiang Wang, Qi Shu, Alexandra Bozec, Eric P. Chassignet, Pier Giuseppe Fogli, Baylor Fox-Kemper, Andy McC. Hogg, Doroteaciro Iovino, Andrew E. Kiss, Nikolay Koldunov, Julien Le Sommer, Yiwen Li, Pengfei Lin, Hailong Liu, Igor Polyakov, Patrick Scholz, Dmitry Sidorenko, Shizhu Wang, and Xiaobiao Xu
Geosci. Model Dev., 17, 347–379, https://doi.org/10.5194/gmd-17-347-2024, https://doi.org/10.5194/gmd-17-347-2024, 2024
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Increasing resolution improves model skills in simulating the Arctic Ocean, but other factors such as parameterizations and numerics are at least of the same importance for obtaining reliable simulations.
Luca Arpaia, Christian Ferrarin, Marco Bajo, and Georg Umgiesser
Geosci. Model Dev., 16, 6899–6919, https://doi.org/10.5194/gmd-16-6899-2023, https://doi.org/10.5194/gmd-16-6899-2023, 2023
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We propose a discrete multilayer shallow water model based on z-layers which, thanks to the insertion and removal of surface layers, can deal with an arbitrarily large tidal oscillation independently of the vertical resolution. The algorithm is based on a two-step procedure used in numerical simulations with moving boundaries (grid movement followed by a grid topology change, that is, the insertion/removal of surface layers), which avoids the appearance of very thin surface layers.
Lucille Barré, Frédéric Diaz, Thibaut Wagener, France Van Wambeke, Camille Mazoyer, Christophe Yohia, and Christel Pinazo
Geosci. Model Dev., 16, 6701–6739, https://doi.org/10.5194/gmd-16-6701-2023, https://doi.org/10.5194/gmd-16-6701-2023, 2023
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While several studies have shown that mixotrophs play a crucial role in the carbon cycle, the impact of environmental forcings on their dynamics remains poorly investigated. Using a biogeochemical model that considers mixotrophs, we study the impact of light and nutrient concentration on the ecosystem composition in a highly dynamic Mediterranean coastal area: the Bay of Marseille. We show that mixotrophs cope better with oligotrophic conditions compared to strict auto- and heterotrophs.
Trygve Halsne, Kai Håkon Christensen, Gaute Hope, and Øyvind Breivik
Geosci. Model Dev., 16, 6515–6530, https://doi.org/10.5194/gmd-16-6515-2023, https://doi.org/10.5194/gmd-16-6515-2023, 2023
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Surface waves that propagate in oceanic or coastal environments get influenced by their surroundings. Changes in the ambient current or the depth profile affect the wave propagation path, and the change in wave direction is called refraction. Some analytical solutions to the governing equations exist under ideal conditions, but for realistic situations, the equations must be solved numerically. Here we present such a numerical solver under an open-source license.
Cited articles
Accad, Y. and Pekeris, C. L.: Solution of the Tidal Equations for the M2 and S2 Tides in the World Oceans from a Knowledge of the Tidal Potential Alone, Philos. T. Roy. Soc. Lond. A-Math., 290, 235–266, https://doi.org/10.1098/rsta.1978.0083, 1978. a, b
Adcroft, A. and Campin, J.-M.: Rescaled Height Coordinates for Accurate Representation of Free-Surface Flows in Ocean Circulation Models, Ocean Model., 7, 269–284, https://doi.org/10.1016/j.ocemod.2003.09.003, 2004. a
Adcroft, A., Anderson, W., Balaji, V., Blanton, C., Bushuk, M., Dufour, C. O., Dunne, J. P., Griffies, S. M., Hallberg, R. W., Harrison, M. J., Held, I., Jansen, M. F., John, J., Krasting, J. P., Langenhorst, A., Legg, S., Liang, Z., McHugh, C., Radhakrishnan, A., Reichl, B. G., Rosati, T., Samuels, B. L., Shao, A., Stouffer, R., Winton, M., Wittenberg, A. T., Xiang, B., Zadeh, N., and Zhang, R.: The GFDL Global Ocean and Sea Ice Model OM4.0: Model Description and Simulation Features, J. Adv. Model. Earth Sy., 11, 3167–3211, https://doi.org/10.1029/2019MS001726, 2019. a, b, c, d, e, f, g
Alexander, M. and Scott, J.: The Influence of ENSO on Air-Sea Interaction in the Atlantic, Geophys. Res. Lett., 29, 46–1–46–4, https://doi.org/10.1029/2001GL014347, 2002. a
Alexander, M. A., Shin, S.-i., Scott, J. D., Curchitser, E., and Stock, C.: The Response of the Northwest Atlantic Ocean to Climate Change, J. Climate, 33, 405–428, https://doi.org/10.1175/JCLI-D-19-0117.1, 2020. a
Alfieri, L., Lorini, V., Hirpa, F. A., Harrigan, S., Zsoter, E., Prudhomme, C., and Salamon, P.: A Global Streamflow Reanalysis for 1980–2018, J. Hydrol., 6, 100049, https://doi.org/10.1016/j.hydroa.2019.100049, 2020. a
Amaya, D. J., Alexander, M. A., Scott, J. D., and Jacox, M. G.: An evaluation of high-resolution ocean reanalyses in the California current system, Prog. Oceanogr., 210, 102951, https://doi.org/10.1016/j.pocean.2022.102951, 2023. a
Andres, M.: On the Recent Destabilization of the Gulf Stream Path Downstream of Cape Hatteras, Geophys. Res. Lett., 43, 9836–9842, https://doi.org/10.1002/2016GL069966, 2016. a
Arakawa, A. and Lamb, V. R.: Computational Design of the Basic Dynamical Processes of the UCLA General Circulation Model, in: General Circulation Models of the Atmosphere, edited by: Chang, J., vol. 17, Methods in Computational Physics: Advances in Research and Applications, Elsevier, 173–265, https://doi.org/10.1016/B978-0-12-460817-7.50009-4, 1977. a
Baker, A. R. and Croot, P. L.: Atmospheric and Marine Controls on Aerosol Iron Solubility in Seawater, Mar. Chem., 120, 4–13, https://doi.org/10.1016/j.marchem.2008.09.003, 2010. a
Bakker, D. C. E., Pfeil, B., Landa, C. S., Metzl, N., O'Brien, K. M., Olsen, A., Smith, K., Cosca, C., Harasawa, S., Jones, S. D., Nakaoka, S., Nojiri, Y., Schuster, U., Steinhoff, T., Sweeney, C., Takahashi, T., Tilbrook, B., Wada, C., Wanninkhof, R., Alin, S. R., Balestrini, C. F., Barbero, L., Bates, N. R., Bianchi, A. A., Bonou, F., Boutin, J., Bozec, Y., Burger, E. F., Cai, W.-J., Castle, R. D., Chen, L., Chierici, M., Currie, K., Evans, W., Featherstone, C., Feely, R. A., Fransson, A., Goyet, C., Greenwood, N., Gregor, L., Hankin, S., Hardman-Mountford, N. J., Harlay, J., Hauck, J., Hoppema, M., Humphreys, M. P., Hunt, C. W., Huss, B., Ibánhez, J. S. P., Johannessen, T., Keeling, R., Kitidis, V., Körtzinger, A., Kozyr, A., Krasakopoulou, E., Kuwata, A., Landschützer, P., Lauvset, S. K., Lefèvre, N., Lo Monaco, C., Manke, A., Mathis, J. T., Merlivat, L., Millero, F. J., Monteiro, P. M. S., Munro, D. R., Murata, A., Newberger, T., Omar, A. M., Ono, T., Paterson, K., Pearce, D., Pierrot, D., Robbins, L. L., Saito, S., Salisbury, J., Schlitzer, R., Schneider, B., Schweitzer, R., Sieger, R., Skjelvan, I., Sullivan, K. F., Sutherland, S. C., Sutton, A. J., Tadokoro, K., Telszewski, M., Tuma, M., van Heuven, S. M. A. C., Vandemark, D., Ward, B., Watson, A. J., and Xu, S.: A multi-decade record of high-quality fCO2 data in version 3 of the Surface Ocean CO2 Atlas (SOCAT), Earth Syst. Sci. Data, 8, 383–413, https://doi.org/10.5194/essd-8-383-2016, 2016. a, b, c
Bakker, D. C. E., Alin, S. R., Castaño-Primo, R., Cronin, M., Gkritzalis, T., Kozyr, A., Lauvset, S. K., Metzl, N., Munro, D. R., Nakaoka, S., O'Brien, K. M., Olsen, A., Omar, A. M., Pfeil, B., Pierrot, D., Rodriguez, C., Steinhoff, T., Sutton, A. J., Tilbrook, B., Wanninkhof, R., Willstrand Wranne, A., Ahmed, M., Andersson, A., Apelthun, L. B., Bates, N., Battisti, R., Beaumont, L., Becker, M., Benoit-Cattin, A., Berghoff, C. F., Boutin, J., Burger, E. F., Burgers, T. M., Cantoni, C., Cattrijsse, A., Chierici, M., Cross, J. N., Coppola, L., Cosca, C. E., Currie, K. I., De Carlo, E. H., Else, B., Enright, M. P., Ericson, Y., Evans, W., Feely, R. A., Fiedler, B., Fransson, A., García-Ibáñez, M. I., Gehrung, M., Glockzin, M., González-Dávila, M., Gutekunst, S., Hermes, R., Humphreys, M. P., Hunt, C. W., Ibánhez, J., Severino P., Jones, S. D., Kitidis, V., Körtzinger, A., Kosugi, N., Landa, C. S., Landschützer, P., Lefèvre, N., Lo Monaco, C., Luchetta, A., Lutz, V. A., Macovei, V. A., Manke, A. B., Merlivat, L., Millero, F. J., Monacci, N. M., Negri, R. M., Newberger, T., Newton, J., Nickford, S. E., Nojiri, Y., Ohman, M., Ólafsdóttir, S. R., Sweeney, C., Ono, T., Palter, J. B., Papakyriakou, T., Peterson, W. T., Plueddemann, A. J., Qi, D., Rehder, G., Ritschel, M., Rutgersson, A., Sabine, C. L., Salisbury, J. E., Santana-Casiano, J. M., Schlitzer, R., Send, U., Skjelvan, I., Smith, K., Sparnocchia, S., Sullivan, K. F., Sutherland, S. C., Szuts, Z. B., Tadokoro, K., Tanhua, T., Telszewski, M., Theetaert, H., Vandemark, D., Voynova, Y. G., Wada, C., Weller, R. A., and Woosley, T. J.: Surface Ocean CO2 Atlas Database Version 2021 (SOCATv2021) (NCEI Accession 0235360), NOAA National Centers for Environmental Information [data set], https://doi.org/10.25921/yg69-jd96, 2021. a
Balch, W. M., Drapeau, D. T., Bowler, B. C., Record, N. R., Bates, N. R., Pinkham, S., Garley, R., and Mitchell, C.: Changing Hydrographic, Biogeochemical, and Acidification Properties in the Gulf of Maine as Measured by the Gulf of Maine North Atlantic Time Series, GNATS, Between 1998 and 2018, J. Geophys. Res.-Biogeo., 127, e2022JG006790, https://doi.org/10.1029/2022JG006790, 2022. a, b, c
Baumann, H., Jones, L., Murray, C., Siedlecki, S., Alexander, M., and Cross, E.: Impaired Hatching Exacerbates the High CO2 Sensitivity of Embryonic Sand Lance Ammodytes Dubius, Mar. Ecol. Prog. Ser., 687, 147–162, https://doi.org/10.3354/meps14010, 2022. a
Bell, R., Spring, A., Brady, R., Huang, A., Squire, D., Blackwood, Z., Sitter, M. C., and Chegini, T.: xarray-contrib/xskillscore: Metrics for verifying forecasts, Zenodo [code], https://doi.org/10.5281/zenodo.5173153, 2021. a
Bell, R. J., Richardson, D. E., Hare, J. A., Lynch, P. D., and Fratantoni, P. S.: Disentangling the Effects of Climate, Abundance, and Size on the Distribution of Marine Fish: An Example Based on Four Stocks from the Northeast US Shelf, ICES J. Marine Sci., 72, 1311–1322, https://doi.org/10.1093/icesjms/fsu217, 2015. a, b
Bennett, A. F. and Kloeden, P. E.: The Ill-Posedness of Open Ocean Models, J. Phys. Oceanogr., 11, 1027–1029, https://doi.org/10.1175/1520-0485(1981)011<1027:TIPOOO>2.0.CO;2, 1981. a
Bisagni, J. J. and Sano, M. H.: Satellite Observations of Sea Surface Temperature Variability on Southern Georges Bank, Cont. Shelf Res., 13, 1045–1064, https://doi.org/10.1016/0278-4343(93)90040-5, 1993. a
Bodner, A. S., Fox-Kemper, B., Johnson, L., Roekel, L. P. V., McWilliams, J. C., Sullivan, P. P., Hall, P. S., and Dong, J.: Modifying the Mixed Layer Eddy Parameterization to Include Frontogenesis Arrest by Boundary Layer Turbulence, J. Phys. Oceanogr., 53, 323–339, https://doi.org/10.1175/JPO-D-21-0297.1, 2023. a, b, c
Boivin-Rioux, A., Starr, M., Chassé, J., Scarratt, M., Perrie, W., Long, Z., and Lavoie, D.: Harmful Algae and Climate Change on the Canadian East Coast: Exploring Occurrence Predictions of Dinophysis Acuminata, D. Norvegica, and Pseudo-nitzschia Seriata, Harmful Algae, 112, 102183, https://doi.org/10.1016/j.hal.2022.102183, 2022. a
Brickman, D., Hebert, D., and Wang, Z.: Mechanism for the Recent Ocean Warming Events on the Scotian Shelf of Eastern Canada, Cont. Shelf Res., 156, 11–22, https://doi.org/10.1016/j.csr.2018.01.001, 2018. a, b
Bryan, F. O., Hecht, M. W., and Smith, R. D.: Resolution Convergence and Sensitivity Studies with North Atlantic Circulation Models. Part I: The Western Boundary Current System, Ocean Model., 16, 141–159, https://doi.org/10.1016/j.ocemod.2006.08.005, 2007. a, b
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. a, b
Cai, W.-J., Hu, X., Huang, W.-J., Murrell, M. C., Lehrter, J. C., Lohrenz, S. E., Chou, W.-C., Zhai, W., Hollibaugh, J. T., Wang, Y., Zhao, P., Guo, X., Gundersen, K., Dai, M., and Gong, G.-C.: Acidification of Subsurface Coastal Waters Enhanced by Eutrophication, Nat. Geosci., 4, 766–770, https://doi.org/10.1038/ngeo1297, 2011. a
Carolina Castillo-Trujillo, A., Kwon, Y.-O., Fratantoni, P., Chen, K., Seo, H., Alexander, M. A., and Saba, V. S.: An evaluation of eight global ocean reanalyses for the Northeast U.S. continental shelf, Prog. Oceanogr., 219, 103126, https://doi.org/10.1016/j.pocean.2023.103126, 2023. a, b
Carter, B. R., Bittig, H. C., Fassbender, A. J., Sharp, J. D., Takeshita, Y., Xu, Y.-Y., Álvarez, M., Wanninkhof, R., Feely, R. A., and Barbero, L.: New and Updated Global Empirical Seawater Property Estimation Routines, Limnol. Oceanogr. Meth., 19, 785–809, https://doi.org/10.1002/lom3.10461, 2021. a, b, c, d, e
Cavalieri, D. J., Parkinson, C. L., Gloersen, P., and Zwally, H. J.: Sea Ice Concentrations from Nimbus-7 SMMR and DMSP SSM/I-SSMIS Passive Microwave Data, Version 1, National Snow and Ice Data Center [data set], https://doi.org/10.5067/8GQ8LZQVL0VL, 1996. a, b, c, d
Chassignet, E. P. and Garaffo, Z. D.: Viscosity Parameterization and the Gulf Stream Separation, in: From stirring to mixing in a stratified ocean: Proceedings of the 12th `Aha Huliko'a Hawaiian Winter Workshop, University of Hawai'i at Mānoa, 37–41, https://www.coaps.fsu.edu/pub/eric/papers_html/Chassignet_Garraffo_01.pdf (last access: 23 November 2023), 2001 a, b, c
Chassignet, E. P. and Marshall, D. P.: Gulf Stream Separation in Numerical Ocean Models, in: Geophysical Monograph Series, edited by: Hecht, M. W. and Hasumi, H., American Geophysical Union, Washington, D. C., vol. 177, 39–61, ISBN 978-0-87590-442-9, https://doi.org/10.1029/177GM05, 2008. a, b
Chassignet, E. P. and Xu, X.: Impact of Horizontal Resolution (1/12∘ to 1/50∘) on Gulf Stream Separation, Penetration, and Variability, J. Phys. Oceanogr., 47, 1999–2021, https://doi.org/10.1175/JPO-D-17-0031.1, 2017. a, b, c
Chassignet, E. P. and Xu, X.: On the Importance of High-Resolution in Large-Scale Ocean Models, Adv. Atmos. Sci., 38, 1621–1634, https://doi.org/10.1007/s00376-021-0385-7, 2021. a, b, c
Chen, K. and Kwon, Y.-O.: Does Pacific Variability Influence the Northwest Atlantic Shelf Temperature?, J. Geophys. Res.-Oceans, 123, 4110–4131, https://doi.org/10.1029/2017JC013414, 2018. a
Chen, Z., Kwon, Y.-O., Chen, K., Fratantoni, P., Gawarkiewicz, G., Joyce, T. M., Miller, T. J., Nye, J. A., Saba, V. S., and Stock, B. C.: Seasonal Prediction of Bottom Temperature on the Northeast U.S. Continental Shelf, J. Geophys. Rese.-Oceans, 126, e2021JC017187, https://doi.org/10.1029/2021JC017187, 2021. a
Chi, L., Wolfe, C. L., and Hameed, S.: Intercomparison of the Gulf Stream in Ocean Reanalyses: 1993–2010, Ocean Model., 125, 1–21, https://doi.org/10.1016/j.ocemod.2018.02.008, 2018. a
Chi, L., Wolfe, C. L. P., and Hameed, S.: The Distinction Between the Gulf Stream and Its North Wall, Geophys. Res. Lett., 46, 8943–8951, https://doi.org/10.1029/2019GL083775, 2019. a
Claret, M., Galbraith, E. D., Palter, J. B., Bianchi, D., Fennel, K., Gilbert, D., and Dunne, J. P.: Rapid Coastal Deoxygenation Due to Ocean Circulation Shift in the Northwest Atlantic, Nat. Clim. Change, 8, 868–872, https://doi.org/10.1038/s41558-018-0263-1, 2018. a
Clark, S., Hubbard, K. A., Anderson, D. M., McGillicuddy, D. J., Ralston, D. K., and Townsend, D. W.: Pseudo-Nitzschia Bloom Dynamics in the Gulf of Maine: 2012–2016, Harmful Algae, 88, 101656, https://doi.org/10.1016/j.hal.2019.101656, 2019. a
Clark, S., Hubbard, K. A., Ralston, D. K., McGillicuddy, D. J., Stock, C., Alexander, M. A., and Curchitser, E.: Projected Effects of Climate Change on Pseudo-nitzschia Bloom Dynamics in the Gulf of Maine, J. Marine Syst., 230, 103737, https://doi.org/10.1016/j.jmarsys.2022.103737, 2022. a
Codiga, D. L.: Unified Tidal Analysis and Prediction Using the UTide Matlab Functions, Technical Report 2011-01, Graduate School of Oceanography, University of Rhode Island, Narragansett, RI, 59 pp., https://www.po.gso.uri.edu/~codiga/utide/2011Codiga-UTide-Report.pdf (last access: 23 November 2023), 2011. a
Dagg, M. J. and Breed, G. A.: Biological Effects of Mississippi River Nitrogen on the Northern Gulf of Mexico – a Review and Synthesis, J. Marine Syst., 43, 133–152, https://doi.org/10.1016/j.jmarsys.2003.09.002, 2003. a
de Baar, H. and de Jong, J.: Distributions, Sources and Sinks of Iron in Seawater, in: Biogeochemistry of Iron in Seawater, edited by: Turner, D. and Hunter, K. A., Wiley, New York, 123–253, ISBN 978-0-471-49068-5, 2001. a
de Boyer Montégut, C.: Mixed Layer Depth over the Global Ocean: An Examination of Profile Data and a Profile-Based Climatology, J. Geophys. Res., 109, C12003, https://doi.org/10.1029/2004JC002378, 2004. a, b, c, d
de Boyer Montégut, C.: Mixed layer depth climatology computed with a density threshold criterion of 0.03kg/m3 from 10 m depth value, SEANOE [dataset], https://doi.org/10.17882/91774, 2023. a, b
Dierssen, H. M.: Perspectives on Empirical Approaches for Ocean Color Remote Sensing of Chlorophyll in a Changing Climate, P. Natl. Acad. Sci. USA, 107, 17073–17078, https://doi.org/10.1073/pnas.0913800107, 2010. a
Dietze, M. C., Fox, A., Beck-Johnson, L. M., Betancourt, J. L., Hooten, M. B., Jarnevich, C. S., Keitt, T. H., Kenney, M. A., Laney, C. M., Larsen, L. G., Loescher, H. W., Lunch, C. K., Pijanowski, B. C., Randerson, J. T., Read, E. K., Tredennick, A. T., Vargas, R., Weathers, K. C., and White, E. P.: Iterative Near-Term Ecological Forecasting: Needs, Opportunities, and Challenges, P. Natl. Acad. Sci. USA, 115, 1424–1432, https://doi.org/10.1073/pnas.1710231115, 2018. a
DiGirolamo, N., Parkinson, C. L., Cavalieri, D. J., Gloersen, P., and Zwally, H. J.: Sea Ice Concentrations from Nimbus-7 SMMR and DMSP SSM/I-SSMIS Passive Microwave Data, Version 2, ASA National Snow and Ice Data Center Distributed Active Archive Center [data set], https://doi.org/10.5067/MPYG15WAA4WX, 2022. a
Dinnel, S. P. and Wiseman, W. J.: Fresh Water on the Louisiana and Texas Shelf, Cont. Shelf Res., 6, 765–784, https://doi.org/10.1016/0278-4343(86)90036-1, 1986. a
Donovan, M. K., Burkepile, D. E., Kratochwill, C., Shlesinger, T., Sully, S., Oliver, T. A., Hodgson, G., Freiwald, J., and van Woesik, R.: Local Conditions Magnify Coral Loss after Marine Heatwaves, Science, 372, 977–980, https://doi.org/10.1126/science.abd9464, 2021. a
Drenkard, E. J., Stock, C., Ross, A. C., Dixon, K. W., Adcroft, A., Alexander, M., Balaji, V., Bograd, S. J., Butenschön, M., Cheng, W., Curchitser, E., Lorenzo, E. D., Dussin, R., Haynie, A. C., Harrison, M., Hermann, A., Hollowed, A., Holsman, K., Holt, J., Jacox, M. G., Jang, C. J., Kearney, K. A., Muhling, B. A., Buil, M. P., Saba, V., Sandø, A. B., Tommasi, D., and Wang, M.: Next-Generation Regional Ocean Projections for Living Marine Resource Management in a Changing Climate, ICES J. Marine Sci., 78, 1969–1987, https://doi.org/10.1093/icesjms/fsab100, 2021. a, b, c
Du, J., Zhang, W. G., and Li, Y.: Variability of Deep Water in Jordan Basin of the Gulf of Maine: Influence of Gulf Stream Warm Core Rings and the Nova Scotia Current, J. Geophys. Res.-Oceans, 126, e2020JC017136, https://doi.org/10.1029/2020JC017136, 2021. a
Dunne, J. P., Horowitz, L. W., Adcroft, A. J., Ginoux, P., Held, I. M., John, J. G., Krasting, J. P., Malyshev, S., Naik, V., Paulot, F., Shevliakova, E., Stock, C. A., Zadeh, N., Balaji, V., Blanton, C., Dunne, K. A., Dupuis, C., Durachta, J., Dussin, R., Gauthier, P. P. G., Griffies, S. M., Guo, H., Hallberg, R. W., Harrison, M., He, J., Hurlin, W., McHugh, C., Menzel, R., Milly, P. C. D., Nikonov, S., Paynter, D. J., Ploshay, J., Radhakrishnan, A., Rand, K., Reichl, B. G., Robinson, T., Schwarzkopf, D. M., Sentman, L. T., Underwood, S., Vahlenkamp, H., Winton, M., Wittenberg, A. T., Wyman, B., Zeng, Y., and Zhao, M.: The GFDL Earth System Model Version 4.1 (GFDL-ESM 4.1): Overall Coupled Model Description and Simulation Characteristics, J. Adv. Model. Earth Sy., 12, e2019MS002015, https://doi.org/10.1029/2019MS002015, 2020. a
Egbert, G. D. and Erofeeva, S. Y.: Efficient Inverse Modeling of Barotropic Ocean Tides, J. Atmos. Ocean. Tec., 19, 183–204, https://doi.org/10.1175/1520-0426(2002)019<0183:EIMOBO>2.0.CO;2, 2002 (data available at: https://www.tpxo.net/home, last access: 23 November 2023). a, b, c
Estrada-Allis, S. N., Sheinbaum Pardo, J., Azevedo Correia de Souza, J. M., Enríquez Ortiz, C. E., Mariño Tapia, I., and Herrera-Silveira, J. A.: Dissolved inorganic nitrogen and particulate organic nitrogen budget in the Yucatán shelf: driving mechanisms through a physical–biogeochemical coupled model, Biogeosciences, 17, 1087–1111, https://doi.org/10.5194/bg-17-1087-2020, 2020. a
Ezer, T. and Atkinson, L. P.: Accelerated Flooding along the U.S. East Coast: On the Impact of Sea-Level Rise, Tides, Storms, the Gulf Stream, and the North Atlantic Oscillations, Earth's Future, 2, 362–382, https://doi.org/10.1002/2014EF000252, 2014. a
Fennel, K., Hu, J., Laurent, A., Marta-Almeida, M., and Hetland, R.: Sensitivity of Hypoxia Predictions for the Northern Gulf of Mexico to Sediment Oxygen Consumption and Model Nesting, J. Geophys. Rese.-Oceans, 118, 990–1002, https://doi.org/10.1002/jgrc.20077, 2013. a
Finkel, Z. V., Beardall, J., Flynn, K. J., Quigg, A., Rees, T. A. V., and Raven, J. A.: Phytoplankton in a Changing World: Cell Size and Elemental Stoichiometry, J. Plankton Res., 32, 119–137, https://doi.org/10.1093/plankt/fbp098, 2010. a
Fisher, J. A. D., Frank, K. T., Petrie, B., Leggett, W. C., and Shackell, N. L.: Temporal Dynamics within a Contemporary Latitudinal Diversity Gradient, Ecol. Lett., 11, 883–897, https://doi.org/10.1111/j.1461-0248.2008.01216.x, 2008. a
Fox-Kemper, B., Danabasoglu, G., Ferrari, R., Griffies, S. M., Hallberg, R. W., Holland, M. M., Maltrud, M. E., Peacock, S., and Samuels, B. L.: Parameterization of Mixed Layer Eddies. III: Implementation and Impact in Global Ocean Climate Simulations, Ocean Model., 39, 61–78, https://doi.org/10.1016/j.ocemod.2010.09.002, 2011. a, b
Franks, P. J. and Chen, C.: Plankton Production in Tidal Fronts: A Model of Georges Bank in Summer, J. Marine Res., 54, 631–651, https://doi.org/10.1357/0022240963213718, 1996. a
Friedland, K. D., Morse, R. E., Manning, J. P., Melrose, D. C., Miles, T., Goode, A. G., Brady, D. C., Kohut, J. T., and Powell, E. N.: Trends and Change Points in Surface and Bottom Thermal Environments of the US Northeast Continental Shelf Ecosystem, Fisheries Oceanogr., 29, 396–414, https://doi.org/10.1111/fog.12485, 2020a. a
Friedland, K. D., Morse, R. E., Shackell, N., Tam, J. C., Morano, J. L., Moisan, J. R., and Brady, D. C.: Changing Physical Conditions and Lower and Upper Trophic Level Responses on the US Northeast Shelf, Front. Mar. Sci., 7, 567445, https://doi.org/10.3389/fmars.2020.567445, 2020b. a
Friedland, K. D., Record, N. R., Pendleton, D. E., Balch, W. M., Stamieszkin, K., Moisan, J. R., and Brady, D. C.: Asymmetry in the Rate of Warming and the Phenology of Seasonal Blooms in the Northeast US Shelf Ecosystem, ICES J. Marine Sci., 80, 775–786, https://doi.org/10.1093/icesjms/fsad007, 2023. a
Froelich, P. N.: Kinetic Control of Dissolved Phosphate in Natural Rivers and Estuaries: A Primer on the Phosphate Buffer Mechanism, Limnol. Oceanogr., 33, 649–668, https://doi.org/10.4319/lo.1988.33.4part2.0649, 1988. a
Fuchs, H. L. and Franks, P. J. S.: Plankton Community Properties Determined by Nutrients and Size-Selective Feeding, Mar. Ecol. Prog. Ser., 413, 1–15, https://doi.org/10.3354/meps08716, 2010. a
Fuglister, F. C. and Voorhis, A. D.: A New Method of Tracking the Gulf Stream, Limnol. Oceanogr., 10, R115–R124, https://doi.org/10.4319/lo.1965.10.suppl2.r115, 1965. a
Galbraith, E. D. and Martiny, A. C.: A Simple Nutrient-Dependence Mechanism for Predicting the Stoichiometry of Marine Ecosystems, P. Natl. Acad. Sci. USA, 112, 8199–8204, https://doi.org/10.1073/pnas.1423917112, 2015. a, b
Gangopadhyay, A., Gawarkiewicz, G., Silva, E. N. S., Monim, M., and Clark, J.: An Observed Regime Shift in the Formation of Warm Core Rings from the Gulf Stream, Sci. Rep., 9, 12319, https://doi.org/10.1038/s41598-019-48661-9, 2019. a
Gangopadhyay, A., Gawarkiewicz, G., Silva, E. N. S., Silver, A. M., Monim, M., and Clark, J.: A Census of the Warm-Core Rings of the Gulf Stream: 1980–2017, J. Geophys. Res.-Oceans, 125, e2019JC016033, https://doi.org/10.1029/2019JC016033, 2020. a
Gawarkiewicz, G., Chen, K., Forsyth, J., Bahr, F., Mercer, A. M., Ellertson, A., Fratantoni, P., Seim, H., Haines, S., and Han, L.: Characteristics of an Advective Marine Heatwave in the Middle Atlantic Bight in Early 2017, Front. Mar. Sci., 6, 712, https://doi.org/10.3389/fmars.2019.00712, 2019. a
Gawarkiewicz, G., Fratantoni, P., Bahr, F., and Ellertson, A.: Increasing Frequency of Mid–Depth Salinity Maximum Intrusions in the Middle Atlantic Bight, J. Geophys. Res.-Oceans, 127, e2021JC018233, https://doi.org/10.1029/2021JC018233, 2022. a
Ghantous, M., Ayoub, N., De Mey-Frémaux, P., Vervatis, V., and Marsaleix, P.: Ensemble Downscaling of a Regional Ocean Model, Ocean Model., 145, 101511, https://doi.org/10.1016/j.ocemod.2019.101511, 2020. a
Gilbert, D., Sundby, B., Gobeil, C., Mucci, A., and Tremblay, G.-H.: A Seventy-Two-Year Record of Diminishing Deep-Water Oxygen in the St. Lawrence Estuary: The Northwest Atlantic Connection, Limnol. Oceanogr., 50, 1654–1666, https://doi.org/10.4319/lo.2005.50.5.1654, 2005. a
Glenn, E., Comarazamy, D., González, J. E., and Smith, T.: Detection of Recent Regional Sea Surface Temperature Warming in the Caribbean and Surrounding Region, Geophys. Res. Lett., 42, 6785–6792, https://doi.org/10.1002/2015GL065002, 2015. a
Global Ocean Gridded L4 Sea Surface Heights And Derived Variables Reprocessed 1993 Ongoing: E.U. Copernicus Marine Service Information Marine Data Store, https://doi.org/10.48670/moi-00148, 2023. a, b
Global Ocean Physics Reanalysis: E.U. Copernicus Marine Service Information (CMEMS), Marine Data Store (MDS), https://doi.org/10.48670/moi-00021, 2021. a, b
Gomez, F. A., Lee, S.-K., Hernandez, F. J., Chiaverano, L. M., Muller-Karger, F. E., Liu, Y., and Lamkin, J. T.: ENSO-induced Co-Variability of Salinity, Plankton Biomass and Coastal Currents in the Northern Gulf of Mexico, Sci. Rep., 9, 178, https://doi.org/10.1038/s41598-018-36655-y, 2019. a, b, c, d
Gomez, F. A., Wanninkhof, R., Barbero, L., and Lee, S.-K.: Increasing River Alkalinity Slows Ocean Acidification in the Northern Gulf of Mexico, Geophys. Res. Lett., 48, e2021GL096521, https://doi.org/10.1029/2021GL096521, 2021. a, b
Gomez, F. A., Lee, S.-K., Stock, C. A., Ross, A. C., Resplandy, L., Siedlecki, S. A., Tagklis, F., and Salisbury, J. E.: RC4USCoast: a river chemistry dataset for regional ocean model applications in the US East Coast, Gulf of Mexico, and US West Coast, Earth Syst. Sci. Data, 15, 2223–2234, https://doi.org/10.5194/essd-15-2223-2023, 2023. a
Gomez, F. A., Lee, S.-K., Stock, C. A., Ross, A. C., Resplandy, L., Siedlecki, S. A., Tagklis, F., and Salisbury, J. E.: RC4USCoast: A river chemistry dataset for regional ocean model application in the U.S. East, Gulf of Mexico, and West Coasts from 1950-01-01 to 2022-12-31 (NCEI Accession 0260455), NOAA National Centers for Environmental Information [data set], https://doi.org/10.25921/9jfw-ph50, 2022. a
Gonçalves Neto, A., Langan, J. A., and Palter, J. B.: Changes in the Gulf Stream Preceded Rapid Warming of the Northwest Atlantic Shelf, Commun. Earth Environ., 2, 74, https://doi.org/10.1038/s43247-021-00143-5, 2021. a
Gregg, M., D'Asaro, E., Riley, J., and Kunze, E.: Mixing Efficiency in the Ocean, Annua. Rev. Mar. Sci., 10, 443–473, https://doi.org/10.1146/annurev-marine-121916-063643, 2018. a
Griffies, S. M. and Hallberg, R. W.: Biharmonic Friction with a Smagorinsky-Like Viscosity for Use in Large-Scale Eddy-Permitting Ocean Models, Mon. Weather Rev., 128, 2935–2946, https://doi.org/10.1175/1520-0493(2000)128<2935:BFWASL>2.0.CO;2, 2000. a, b
Griffies, S. M., Pacanowski, R. C., and Hallberg, R. W.: Spurious Diapycnal Mixing Associated with Advection in a Z-Coordinate Ocean Model, Mon. Weather Rev., 128, 538–564, https://doi.org/10.1175/1520-0493(2000)128<0538:SDMAWA>2.0.CO;2, 2000. a
Griffies, S. M., Danabasoglu, G., Durack, P. J., Adcroft, A. J., Balaji, V., Böning, C. W., Chassignet, E. P., Curchitser, E., Deshayes, J., Drange, H., Fox-Kemper, B., Gleckler, P. J., Gregory, J. M., Haak, H., Hallberg, R. W., Heimbach, P., Hewitt, H. T., Holland, D. M., Ilyina, T., Jungclaus, J. H., Komuro, Y., Krasting, J. P., Large, W. G., Marsland, S. J., Masina, S., McDougall, T. J., Nurser, A. J. G., Orr, J. C., Pirani, A., Qiao, F., Stouffer, R. J., Taylor, K. E., Treguier, A. M., Tsujino, H., Uotila, P., Valdivieso, M., Wang, Q., Winton, M., and Yeager, S. G.: OMIP contribution to CMIP6: experimental and diagnostic protocol for the physical component of the Ocean Model Intercomparison Project, Geosci. Model Dev., 9, 3231–3296, https://doi.org/10.5194/gmd-9-3231-2016, 2016. a
Griffith, A. W. and Gobler, C. J.: Transgenerational Exposure of North Atlantic Bivalves to Ocean Acidification Renders Offspring More Vulnerable to Low pH and Additional Stressors, Sci. Rep., 7, 11394, https://doi.org/10.1038/s41598-017-11442-3, 2017. a
Grodsky, S. A., Reul, N., Chapron, B., Carton, J. A., and Bryan, F. O.: Interannual Surface Salinity on Northwest Atlantic Shelf, J. Geophys. Rese.-Oceans, 122, 3638–3659, https://doi.org/10.1002/2016JC012580, 2017. a
Hall, S. R., Smith, V. H., Lytle, D. A., and Leibold, M. A.: Constraints on Primary Producer N:P Stoichiometry Along N:P Supply Ratio Gradients, Ecology, 86, 1894–1904, https://doi.org/10.1890/04-1045, 2005. a
Hallberg, R.: Stable Split Time Stepping Schemes for Large-Scale Ocean Modeling, J. Comput. Phys., 135, 54–65, https://doi.org/10.1006/jcph.1997.5734, 1997. a
Hallberg, R.: Using a Resolution Function to Regulate Parameterizations of Oceanic Mesoscale Eddy Effects, Ocean Model., 72, 92–103, https://doi.org/10.1016/j.ocemod.2013.08.007, 2013. a, b
Hallberg, R. and Adcroft, A.: Reconciling Estimates of the Free Surface Height in Lagrangian Vertical Coordinate Ocean Models with Mode-Split Time Stepping, Ocean Model., 29, 15–26, https://doi.org/10.1016/j.ocemod.2009.02.008, 2009. a
Hansen, B., Bjornsen, P. K., and Hansen, P. J.: The Size Ratio between Planktonic Predators and Their Prey, Limnol. Oceanogr., 39, 395–403, https://doi.org/10.4319/lo.1994.39.2.0395, 1994. a
Heil, C. A. and Muni-Morgan, A. L.: Florida's Harmful Algal Bloom (HAB) Problem: Escalating Risks to Human, Environmental and Economic Health With Climate Change, Front. Ecol. Evol., 9, 646080, 2021. a
Herbert, R. J., Krom, M. D., Carslaw, K. S., Stockdale, A., Mortimer, R. J. G., Benning, L. G., Pringle, K., and Browse, J.: The Effect of Atmospheric Acid Processing on the Global Deposition of Bioavailable Phosphorus From Dust, Global Biogeochem. Cy., 32, 1367–1385, https://doi.org/10.1029/2018GB005880, 2018. a
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., De Chiara, G., 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
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., and Thépaut, J.-N.: ERA5 hourly data on single levels from 1940 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.adbb2d47, 2023. a
Hervieux, G., Alexander, M. A., Stock, C. A., Jacox, M. G., Pegion, K., Becker, E., Castruccio, F., and Tommasi, D.: More Reliable Coastal SST Forecasts from the North American Multimodel Ensemble, Clim. Dynam., 53, 7153–7168, https://doi.org/10.1007/s00382-017-3652-7, 2017. a
Hoegh-Guldberg, O., Mumby, P. J., Hooten, A. J., Steneck, R. S., Greenfield, P., Gomez, E., Harvell, C. D., Sale, P. F., Edwards, A. J., Caldeira, K., Knowlton, N., Eakin, C. M., Iglesias-Prieto, R., Muthiga, N., Bradbury, R. H., Dubi, A., and Hatziolos, M. E.: Coral Reefs Under Rapid Climate Change and Ocean Acidification, Science, 318, 1737–1742, https://doi.org/10.1126/science.1152509, 2007. a
Holt, J., Hyder, P., Ashworth, M., Harle, J., Hewitt, H. T., Liu, H., New, A. L., Pickles, S., Porter, A., Popova, E., Allen, J. I., Siddorn, J., and Wood, R.: Prospects for improving the representation of coastal and shelf seas in global ocean models, Geosci. Model Dev., 10, 499–523, https://doi.org/10.5194/gmd-10-499-2017, 2017. a
Hu, S., Townsend, D. W., Chen, C., Cowles, G., Beardsley, R. C., Ji, R., and Houghton, R. W.: Tidal Pumping and Nutrient Fluxes on Georges Bank: A Process-Oriented Modeling Study, J. Marine Syst., 74, 528–544, https://doi.org/10.1016/j.jmarsys.2008.04.007, 2008. a, b
Irazoqui Apecechea, M., Verlaan, M., Zijl, F., Le Coz, C., and Kernkamp, H.: Effects of Self-Attraction and Loading at a Regional Scale: A Test Case for the Northwest European Shelf, Ocean Dynam., 67, 729–749, https://doi.org/10.1007/s10236-017-1053-4, 2017. a, b
Jackson, L., Hallberg, R., and Legg, S.: A Parameterization of Shear-Driven Turbulence for Ocean Climate Models, J. Phys. Oceanogr., 38, 1033–1053, https://doi.org/10.1175/2007JPO3779.1, 2008. a
Jackson, L. C., Biastoch, A., Buckley, M. W., Desbruyères, D. G., Frajka-Williams, E., Moat, B., and Robson, J.: The Evolution of the North Atlantic Meridional Overturning Circulation since 1980, Nature Rev. Earth Environ., 3, 241–254, https://doi.org/10.1038/s43017-022-00263-2, 2022. a
Jerlov, N. G.: Marine Optics, no. 14 in Elsevier Oceanography Series, Elsevier, ISBN 978-0-08-087050-2, 1976. a
Jiang, L.-Q., Feely, R. A., Wanninkhof, R., Greeley, D., Barbero, L., Alin, S., Carter, B. R., Pierrot, D., Featherstone, C., Hooper, J., Melrose, C., Monacci, N., Sharp, J. D., Shellito, S., Xu, Y.-Y., Kozyr, A., Byrne, R. H., Cai, W.-J., Cross, J., Johnson, G. C., Hales, B., Langdon, C., Mathis, J., Salisbury, J., and Townsend, D. W.: Coastal Ocean Data Analysis Product in North America (CODAP-NA) – an internally consistent data product for discrete inorganic carbon, oxygen, and nutrients on the North American ocean margins, Earth Syst. Sci. Data, 13, 2777–2799, https://doi.org/10.5194/essd-13-2777-2021, 2021. a
Jiang, L.-Q., Boyer, T. P., Paver, C. R., Reagan, J. R., Alin, S. R., Barbero, L., Carter, B. R., Feely, R. A., and Wanninkhof, R.: Climatological Distribution of Ocean Acidification Indicators from Surface to 500 Meters Water Depth on the North American Ocean Margins from 2003-12-06 to 2018-11-22 (NCEI Accession 0270962), NOAA National Centers for Environmental Information [data set] https://doi.org/10.25921/g8pb-zy76, 2022. a, b, c, d
Jutras, M., Dufour, C. O., Mucci, A., Cyr, F., and Gilbert, D.: Temporal Changes in the Causes of the Observed Oxygen Decline in the St. Lawrence Estuary, J. Geophys. Res.-Oceans, 125, e2020JC016577, https://doi.org/10.1029/2020JC016577, 2020. a
Jutras, M., Mucci, A., Chaillou, G., Nesbitt, W. A., and Wallace, D. W. R.: Temporal and spatial evolution of bottom-water hypoxia in the St Lawrence estuarine system, Biogeosciences, 20, 839–849, https://doi.org/10.5194/bg-20-839-2023, 2023. a
Kang, D. and Curchitser, E. N.: Gulf Stream Eddy Characteristics in a High-Resolution Ocean Model, J. Geophys. Res.-Oceans, 118, 4474–4487, https://doi.org/10.1002/jgrc.20318, 2013. a
Kang, D. and Curchitser, E. N.: Energetics of Eddy–Mean Flow Interactions in the Gulf Stream Region, J. Phys. Oceanogr., 45, 1103–1120, https://doi.org/10.1175/JPO-D-14-0200.1, 2015. a
Kirk, J. T. O.: Light and Photosynthesis in Aquatic Ecosystems, Cambridge University Press, Cambridge, 2nd edn., https://doi.org/10.1017/CBO9780511623370, 1994. a
Kleisner, K. M., Fogarty, M. J., McGee, S., Barnett, A., Fratantoni, P., Greene, J., Hare, J. A., Lucey, S. M., McGuire, C., Odell, J., Saba, V. S., Smith, L., Weaver, K. J., and Pinsky, M. L.: The Effects of Sub-Regional Climate Velocity on the Distribution and Spatial Extent of Marine Species Assemblages, PLOS ONE, 11, e0149220, https://doi.org/10.1371/journal.pone.0149220, 2016. a
Laliberté, J. and Larouche, P.: Chlorophyll-a Concentration Climatology, Phenology, and Trends in the Optically Complex Waters of the St. Lawrence Estuary and Gulf, J. Marine Syst., 238, 103830, https://doi.org/10.1016/j.jmarsys.2022.103830, 2023. a, b
Landschützer, P., Laruelle, G. G., Roobaert, A., and Regnier, P.: A combined global ocean pCO2 climatology combining open ocean and coastal areas (NCEI Accession 0209633), NOAA National Centers for Environmental Information [data set], https://doi.org/10.25921/qb25-f418, 2020b. a
Large, W. G. and Yeager, S. G.: Diurnal to Decadal Global Forcing For Ocean and Sea-Ice Models: The Data Sets and Flux Climatologies, Tech. rep., National Center for Atmospheric Research, https://doi.org/10.5065/D6KK98Q6, 2004. a, b
Lauvset, S. K., Lange, N., Tanhua, T., Bittig, H. C., Olsen, A., Kozyr, A., Álvarez, M., Becker, S., Brown, P. J., Carter, B. R., Cotrim da Cunha, L., Feely, R. A., van Heuven, S., Hoppema, M., Ishii, M., Jeansson, E., Jutterström, S., Jones, S. D., Karlsen, M. K., Lo Monaco, C., Michaelis, P., Murata, A., Pérez, F. F., Pfeil, B., Schirnick, C., Steinfeldt, R., Suzuki, T., Tilbrook, B., Velo, A., Wanninkhof, R., Woosley, R. J., and Key, R. M.: An updated version of the global interior ocean biogeochemical data product, GLODAPv2.2021, Earth Syst. Sci. Data, 13, 5565–5589, https://doi.org/10.5194/essd-13-5565-2021, 2021. a, b
Lavoie, D., Lambert, N., Starr, M., Chassé, J., Riche, O., Le Clainche, Y., Azetsu-Scott, K., Béjaoui, B., Christian, J. R., and Gilbert, D.: The Gulf of St. Lawrence Biogeochemical Model: A Modelling Tool for Fisheries and Ocean Management, Front. Mar. Sci., 8, 732269, https://doi.org/10.3389/fmars.2021.732269, 2021. a, b, c
Legg, S., Hallberg, R. W., and Girton, J. B.: Comparison of Entrainment in Overflows Simulated by Z-Coordinate, Isopycnal and Non-Hydrostatic Models, Ocean Model., 11, 69–97, https://doi.org/10.1016/j.ocemod.2004.11.006, 2006. a
Leggat, W. P., Camp, E. F., Suggett, D. J., Heron, S. F., Fordyce, A. J., Gardner, S., Deakin, L., Turner, M., Beeching, L. J., Kuzhiumparambil, U., Eakin, C. M., and Ainsworth, T. D.: Rapid Coral Decay Is Associated with Marine Heatwave Mortality Events on Reefs, Current Biol., 29, 2723–2730.e4, https://doi.org/10.1016/j.cub.2019.06.077, 2019. a
Lellouche, J., Greiner, E., Bourdallé-Badie, R., Garric, G., Melet, A., Drévillon, M., Bricaud, C., Hamon, M., Le Galloudec, O., Regnier, C., Candela, T., Testut, C., Gasparin, F., Ruggiero, G., Benkiran, M., Drillet, Y., and Le Traon, P.: The Copernicus Global 1/12∘ Oceanic and Sea Ice GLORYS12 Reanalysis, Front. Earth Sci.e, 9, 698876, https://doi.org/10.3389/feart.2021.698876, 2021. a
Lewis, A. S. L., Woelmer, W. M., Wander, H. L., Howard, D. W., Smith, J. W., McClure, R. P., Lofton, M. E., Hammond, N. W., Corrigan, R. S., Thomas, R. Q., and Carey, C. C.: Increased Adoption of Best Practices in Ecological Forecasting Enables Comparisons of Forecastability, Ecol. Appl., 32, e02500, https://doi.org/10.1002/eap.2500, 2022. a
Li, D., Chang, P., Yeager, S. G., Danabasoglu, G., Castruccio, F. S., Small, J., Wang, H., Zhang, Q., and Gopal, A.: The Impact of Horizontal Resolution on Projected Sea-level Rise along US East Continental Shelf with the Community Earth System Model, J. Adv. Model. Earth Sy., https://doi.org/10.1029/2021MS002868, 2022. a, b
Liu, Y., Lee, S.-K., Muhling, B. A., Lamkin, J. T., and Enfield, D. B.: Significant Reduction of the Loop Current in the 21st Century and Its Impact on the Gulf of Mexico, J. Geophys. Res.-Oceans, 117, C05039, https://doi.org/10.1029/2011JC007555, 2012. a
Lucey, S. and Nye, J.: Shifting Species Assemblages in the Northeast US Continental Shelf Large Marine Ecosystem, Mar. Ecol. Prog. Ser.s, 415, 23–33, https://doi.org/10.3354/meps08743, 2010. a
Manizza, M.: Bio-Optical Feedbacks among Phytoplankton, Upper Ocean Physics and Sea-Ice in a Global Model, Geophys. Res. Lett., 32, L05603, https://doi.org/10.1029/2004GL020778, 2005. a, b, c
Marchesiello, P., McWilliams, J. C., and Shchepetkin, A.: Open Boundary Conditions for Long-Term Integration of Regional Oceanic Models, Ocean Model., 3, 1–20, https://doi.org/10.1016/S1463-5003(00)00013-5, 2001. a, b, c
Matli, V. R. R., Laurent, A., Fennel, K., Craig, K., Krause, J., and Obenour, D. R.: Fusion-Based Hypoxia Estimates: Combining Geostatistical and Mechanistic Models of Dissolved Oxygen Variability, Environ. Sci. Technol., 54, 13016–13025, https://doi.org/10.1021/acs.est.0c03655, 2020. a, b, c, d, e, f, g
Mayorga, E., Seitzinger, S. P., Harrison, J. A., Dumont, E., Beusen, A. H., Bouwman, A., Fekete, B. M., Kroeze, C., and Van Drecht, G.: Global Nutrient Export from WaterSheds 2 (NEWS 2): Model Development and Implementation, Environ. Model. Softw., 25, 837–853, https://doi.org/10.1016/j.envsoft.2010.01.007, 2010. a, b
Mazur, M. D., Friedland, K. D., McManus, M. C., and Goode, A. G.: Dynamic Changes in American Lobster Suitable Habitat Distribution on the Northeast U.S. Shelf Linked to Oceanographic Conditions, Fisheries Oceanogr., 29, 349–365, https://doi.org/10.1111/fog.12476, 2020. a
Meinshausen, M. and Nicholls, Z. R. J.: UoM-MESSAGE-GLOBIOM-ssp245-1-2-1 GHG concentrations. Version YYYYMMDD[1], Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/input4MIPs.9866, 2018. a
Meinshausen, M. and Vogel, E.: input4MIPs.UoM.GHGConcentrations.CMIP.UoM-CMIP-1-2-0. Version YYYYMMDD[1], Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/input4MIPs.1118, 2016. a
Meinshausen, M., Vogel, E., Nauels, A., Lorbacher, K., Meinshausen, N., Etheridge, D. M., Fraser, P. J., Montzka, S. A., Rayner, P. J., Trudinger, C. M., Krummel, P. B., Beyerle, U., Canadell, J. G., Daniel, J. S., Enting, I. G., Law, R. M., Lunder, C. R., O'Doherty, S., Prinn, R. G., Reimann, S., Rubino, M., Velders, G. J. M., Vollmer, M. K., Wang, R. H. J., and Weiss, R.: Historical greenhouse gas concentrations for climate modelling (CMIP6), Geosci. Model Dev., 10, 2057–2116, https://doi.org/10.5194/gmd-10-2057-2017, 2017. a, b, c
Meinshausen, M., Nicholls, Z. R. J., Lewis, J., Gidden, M. J., Vogel, E., Freund, M., Beyerle, U., Gessner, C., Nauels, A., Bauer, N., Canadell, J. G., Daniel, J. S., John, A., Krummel, P. B., Luderer, G., Meinshausen, N., Montzka, S. A., Rayner, P. J., Reimann, S., Smith, S. J., van den Berg, M., Velders, G. J. M., Vollmer, M. K., and Wang, R. H. J.: The shared socio-economic pathway (SSP) greenhouse gas concentrations and their extensions to 2500, Geosci. Model Dev., 13, 3571–3605, https://doi.org/10.5194/gmd-13-3571-2020, 2020. a
Meyer-Gutbrod, E. L., Greene, C. H., Davies, K. T., and Johns, D. G.: Ocean Regime Shift Is Driving Collapse of the North Atlantic Right Whale Population, Oceanography, 34, 22–31, 2021. a
Miller, T. J., Hare, J. A., and Alade, L. A.: A State-Space Approach to Incorporating Environmental Effects on Recruitment in an Age-Structured Assessment Model with an Application to Southern New England Yellowtail Flounder, Can. J. Fisher. Aquatic Sci., 73, 1261–1270, https://doi.org/10.1139/cjfas-2015-0339, 2016. a
Mills, K., Pershing, A., Brown, C., Chen, Y., Chiang, F.-S., Holland, D., Lehuta, S., Nye, J., Sun, J., Thomas, A., and Wahle, R.: Fisheries Management in a Changing Climate: Lessons From the 2012 Ocean Heat Wave in the Northwest Atlantic, Oceanography, 26, 191–195, https://doi.org/10.5670/oceanog.2013.27, 2013. a
Mills, K. E., Pershing, A. J., and Hernández, C. M.: Forecasting the Seasonal Timing of Maine's Lobster Fishery, Front. Mar. Sci., 4, 337, https://doi.org/10.3389/fmars.2017.00337, 2017. a
Moriarty, R. and O'Brien, T. D.: Distribution of mesozooplankton biomass in the global ocean, Earth Syst. Sci. Data, 5, 45–55, https://doi.org/10.5194/essd-5-45-2013, 2013 (data available at: https://www.st.nmfs.noaa.gov/copepod/biomass/biomass-fields.html, last access: 23 November 2023). a, b, c
Morse, R., Friedland, K., Tommasi, D., Stock, C., and Nye, J.: Distinct Zooplankton Regime Shift Patterns across Ecoregions of the U.S. Northeast Continental Shelf Large Marine Ecosystem, J. Marine Syst., 165, 77–91, https://doi.org/10.1016/j.jmarsys.2016.09.011, 2017. a
Mountain, D. G.: The Volume of Shelf Water in the Middle Atlantic Bight: Seasonal and Interannual Variability, 1977–1987, Cont. Shelf Res., 11, 251–267, https://doi.org/10.1016/0278-4343(91)90068-H, 1991. a
Mountain, D. G.: Labrador Slope Water Entering the Gulf of Maine – Response to the North Atlantic Oscillation, Cont. Shelf Res., 47, 150–155, https://doi.org/10.1016/j.csr.2012.07.008, 2012. a, b, c
Murphy, A. H. and Epstein, E. S.: Skill Scores and Correlation Coefficients in Model Verification, Mon. Weather Rev., 117, 572–582, https://doi.org/10.1175/1520-0493(1989)117<0572:SSACCI>2.0.CO;2, 1989. a
NERACOOS: ERDDAP [dataset], http://www.neracoos.org/erddap/info/index.html?, last access: 14 June 2021. a
NOAA Fisheries: 2022 State of the Ecosystem: Mid-Atlantic, Tech. rep., https://doi.org/10.25923/vy6j-w454, 2022a. a, b, c
Nye, J., Link, J., Hare, J., and Overholtz, W.: Changing Spatial Distribution of Fish Stocks in Relation to Climate and Population Size on the Northeast United States Continental Shelf, Marine Ecol. Prog. Ser., 393, 111–129, https://doi.org/10.3354/meps08220, 2009. a, b
O'Brien, T. D.: COPEPOD, a Global Plankton Database : a review of the 2005 database contents and creation of new global zooplankton biomass fields, Tech. Rep. NOAA technical memorandum NMFS-F/SPO-73, U.S. Department of Commerce, https://repository.library.noaa.gov/view/noaa/3497 (last access: 23 April 2020), 2005. a
Oey, L.-Y., Ezer, T., and Lee, H.-C.: Loop Current, Rings and Related Circulation in the Gulf of Mexico: A Review of Numerical Models and Future Challenges, in: Geophysical Monograph Series, edited by Sturges, W. and Lugo-Fernandez, A., American Geophysical Union, Washington, D. C., 31–56, ISBN 978-1-118-66616-6 978-0-87590-426-9, https://doi.org/10.1029/161GM04, 2013. a
Oliger, J. and Sundstrom, A.: Theoretical and Practical Aspects of Some Initial Boundary Value Problems in Fluid Dynamics, SIAM J. Appl. Math., 35, 419–446, 1978. a
Oremus, K. L.: Climate Variability Reduces Employment in New England Fisheries, P. Natl. Acad. Sci. USA, 116, 26444–26449, https://doi.org/10.1073/pnas.1820154116, 2019. a
Orlanski, I.: A Simple Boundary Condition for Unbounded Hyperbolic Flows, J. Comput. Phys., 21, 251–269, https://doi.org/10.1016/0021-9991(76)90023-1, 1976. a, b
Pérez-Hernández, M. D. and Joyce, T. M.: Two Modes of Gulf Stream Variability Revealed in the Last Two Decades of Satellite Altimeter Data, J. Phys. Oceanogr., 44, 149–163, https://doi.org/10.1175/JPO-D-13-0136.1, 2014. a
Pershing, A. J., Alexander, M. A., Hernandez, C. M., Kerr, L. A., Le Bris, A., Mills, K. E., Nye, J. A., Record, N. R., Scannell, H. A., Scott, J. D., Sherwood, G. D., and Thomas, A. C.: Slow Adaptation in the Face of Rapid Warming Leads to Collapse of the Gulf of Maine Cod Fishery, Science, 350, 809–812, https://doi.org/10.1126/science.aac9819, 2015. a, b, c, d
Petrie, B. and Yeats, P.: Annual and Interannual Variability of Nutrients and Their Estimated Fluxes in the Scotian Shelf – Gulf of Maine Region, Can. J. Fisher. Aquat. Sci., 57, 2536–2546, https://doi.org/10.1139/f00-235, 2000. a
Piecuch, C. G., Bittermann, K., Kemp, A. C., Ponte, R. M., Little, C. M., Engelhart, S. E., and Lentz, S. J.: River-Discharge Effects on United States Atlantic and Gulf Coast Sea-Level Changes, P. Natl. Acad. Sci. USA, 115, 7729–7734, https://doi.org/10.1073/pnas.1805428115, 2018. a
Pinsky, M. L. and Fogarty, M.: Lagged Social-Ecological Responses to Climate and Range Shifts in Fisheries, Climatic Change, 115, 883–891, https://doi.org/10.1007/s10584-012-0599-x, 2012. a, b
Pinsky, M. L., Reygondeau, G., Caddell, R., Palacios-Abrantes, J., Spijkers, J., and Cheung, W. W. L.: Preparing Ocean Governance for Species on the Move, Science, 360, 1189–1191, https://doi.org/10.1126/science.aat2360, 2018. a
Rabalais, N. N., Turner, R. E., JustiĆ, D., Dortch, Q., Wiseman, W. J., and Sen Gupta, B. K.: Nutrient Changes in the Mississippi River and System Responses on the Adjacent Continental Shelf, Estuaries, 19, 386–407, https://doi.org/10.2307/1352458, 1996. a
Rabalais, N. N., Turner, R. E., Sen Gupta, B. K., Boesch, D. F., Chapman, P., and Murrell, M. C.: Hypoxia in the Northern Gulf of Mexico: Does the Science Support the Plan to Reduce, Mitigate, and Control Hypoxia?, Estuar. Coasts, 30, 753–772, https://doi.org/10.1007/BF02841332, 2007. a
Ramos, M. H., van Andel, S. J., and Pappenberger, F.: Do probabilistic forecasts lead to better decisions?, Hydrol. Earth Syst. Sci., 17, 2219–2232, https://doi.org/10.5194/hess-17-2219-2013, 2013. a
Ray, R. D.: Ocean Self-attraction and Loading in Numerical Tidal Models, Marine Geod., 21, 181–192, https://doi.org/10.1080/01490419809388134, 1998. a, b
Reichl, B. G. and Hallberg, R.: A Simplified Energetics Based Planetary Boundary Layer (ePBL) Approach for Ocean Climate Simulations, Ocean Model., 132, 112–129, https://doi.org/10.1016/j.ocemod.2018.10.004, 2018. a, b
Reichl, B. G. and Li, Q.: A Parameterization with a Constrained Potential Energy Conversion Rate of Vertical Mixing Due to Langmuir Turbulence, J. Phys. Oceanogr., 49, 2935–2959, https://doi.org/10.1175/JPO-D-18-0258.1, 2019. a
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 (data available at: https://psl.noaa.gov/data/gridded/data.noaa.oisst.v2.highres.html, last acces: 23 November 2023). a, b
Roman, M. R., Adolf, H. A., Landry, M. R., Madin, L. P., Steinberg, D. K., and Zhang, X.: Estimates of Oceanic Mesozooplankton Production: A Comparison Using the Bermuda and Hawaii Time-Series Data, Deep-Sea Res. Pt. II, 49, 175–192, https://doi.org/10.1016/S0967-0645(01)00099-6, 2001. a
Roobaert, A., Resplandy, L., Laruelle, G. G., Liao, E., and Regnier, P.: A framework to evaluate and elucidate the driving mechanisms of coastal sea surface pCO2 seasonality using an ocean general circulation model (MOM6-COBALT), Ocean Sci., 18, 67–88, https://doi.org/10.5194/os-18-67-2022, 2022. a
Ross, A., Stock, C. A., Adcroft, A., Curchitser, E., Hallberg, R., Harrison, M. J., Hedstrom, K., Zadeh, N., Alexander, M., Chen, W., Drenkard, E. J., du Pontavice, H., Dussin, R., Gomez, F., John, J. G., Kang, D., Lavoie, D., Resplandy, L., Roobaert, A., Saba, V., Shin, S., Siedlecki, S., and Simkins, J.: Model output for A high-resolution physical- biogeochemical model for marine resource applications in the Northwest Atlantic (MOM6-COBALT-NWA12), Zenodo [data set], https://doi.org/10.5281/zenodo.7893387, 2023a. a
Ross, A. C., Stock, C. A., Adcroft, A., Curchitser, E., Hallberg, R., Harrison, M. J., Hedstrom, K., Zadeh, N., Alexander, M., Chen, W., Drenkard, E. J., du Pontavice, H., Dussin, R., Gomez, F., John, J. G., Kang, D., Lavoie, D., Resplandy, L., Roobaert, A., Saba, V., Shin, S., Siedlecki, S., and Simkins, J.: Model source code for A high-resolution physical- biogeochemical model for marine resource applications in the Northwest Atlantic (MOM6-COBALT-NWA12), Zenodo [data set], https://doi.org/10.5281/zenodo.7893349, 2023b. a, b
Ross, A. C., Stock, C. A., Adcroft, A., Curchitser, E., Hallberg, R., Harrison, M. J., Hedstrom, K., Zadeh, N., Alexander, M., Chen, W., Drenkard, E. J., du Pontavice, H., Dussin, R., Gomez, F., John, J. G., Kang, D., Lavoie, D., Resplandy, L., Roobaert, A., Saba, V., Shin, S., Siedlecki, S., and Simkins, J.: Model input for A high-resolution physical- biogeochemical model for marine resource applications in the Northwest Atlantic (MOM6-COBALT-NWA12), Zenodo [data set], https://doi.org/10.5281/zenodo.7893727, 2023c. a
Roulston, M. S., Bolton, G. E., Kleit, A. N., and Sears-Collins, A. L.: A Laboratory Study of the Benefits of Including Uncertainty Information in Weather Forecasts, Weather Forecast., 21, 116–122, https://doi.org/10.1175/WAF887.1, 2006. a
Saba, V. S., Griffies, S. M., Anderson, W. G., Winton, M., Alexander, M. A., Delworth, T. L., Hare, J. A., Harrison, M. J., Rosati, A., Vecchi, G. A., and Zhang, R.: Enhanced Warming of the Northwest Atlantic Ocean under Climate Change, J. Geophys. Res.-Oceans, 121, 118–132, https://doi.org/10.1002/2015JC011346, 2016. a, b, c, d
Salisbury, J. E. and Jönsson, B. F.: Rapid Warming and Salinity Changes in the Gulf of Maine Alter Surface Ocean Carbonate Parameters and Hide Ocean Acidification, Biogeochemistry, 141, 401–418, https://doi.org/10.1007/s10533-018-0505-3, 2018. a
Sasaki, H., Kida, S., Furue, R., Aiki, H., Komori, N., Masumoto, Y., Miyama, T., Nonaka, M., Sasai, Y., and Taguchi, B.: A global eddying hindcast ocean simulation with OFES2, Geosci. Model Dev., 13, 3319–3336, https://doi.org/10.5194/gmd-13-3319-2020, 2020. a
Sathyendranath, S., Brewin, R. J. W., Brockmann, C., Brotas, V., Calton, B., Chuprin, A., Cipollini, P., Couto, A. B., Dingle, J., Doerffer, R., Donlon, C., Dowell, M., Farman, A., Grant, M., Groom, S., Horseman, A., Jackson, T., Krasemann, H., Lavender, S., Martinez-Vicente, V., Mazeran, C., Mélin, F., Moore, T. S., Müller, D., Regner, P., Roy, S., Steele, C. J., Steinmetz, F., Swinton, J., Taberner, M., Thompson, A., Valente, A., Zühlke, M., Brando, V. E., Feng, H., Feldman, G., Franz, B. A., Frouin, R., Gould, R. W., Hooker, S. B., Kahru, M., Kratzer, S., Mitchell, B. G., Muller-Karger, F. E., Sosik, H. M., Voss, K. J., Werdell, J., and Platt, T.: An Ocean-Colour Time Series for Use in Climate Studies: The Experience of the Ocean-Colour Climate Change Initiative (OC-CCI), Sensors, 19, 4285, https://doi.org/10.3390/s19194285, 2019 (data available at: https://www.oceancolour.org/, last access: 23 November 2023). a, b
Scaife, A. A., Copsey, D., Gordon, C., Harris, C., Hinton, T., Keeley, S., O'Neill, A., Roberts, M., and Williams, K.: Improved Atlantic Winter Blocking in a Climate Model, Geophys. Res. Lett., 38, L23703, https://doi.org/10.1029/2011GL049573, 2011. a
Schaeffer, B. A., Sinclair, G. A., Lehrter, J. C., Murrell, M. C., Kurtz, J. C., Gould, R. W., and Yates, D. F.: An Analysis of Diffuse Light Attenuation in the Northern Gulf of Mexico Hypoxic Zone Using the SeaWiFS Satellite Data Record, Remote Sens. Environ., 115, 3748–3757, https://doi.org/10.1016/j.rse.2011.09.013, 2011. a
Schofield, O., Arnone, R., Bissett, P., Dickey, T., Davis, C., Finkel, Z., Oliver, M., and Moline, M.: Watercolors in the Coastal Zone: What Can We See?, Oceanography, 17, 24–31, https://doi.org/10.5670/oceanog.2004.44, 2004. a
Seidov, D., Mishonov, A., Reagan, J., Baranova, O., Cross, S., and Parsons, R.: Regional Climatology of the Northwest Atlantic Ocean: High-Resolution Mapping of Ocean Structure and Change, B. Ame. Meteorol. Soc., 99, 2129–2138, https://doi.org/10.1175/BAMS-D-17-0205.1, 2018 (data available at: https://www.ncei.noaa.gov/products/regional-ocean-climatologies, last access: 23 November 2023). a, b
Seidov, D., Mishonov, A., Reagan, J., and Parsons, R.: Eddy-Resolving In Situ Ocean Climatologies of Temperature and Salinity in the Northwest Atlantic Ocean, J. Geophys. Res.-Oceans, 124, 41–58, https://doi.org/10.1029/2018JC014548, 2019. a
Seidov, D., Mishonov, A., and Parsons, R.: Recent Warming and Decadal Variability of Gulf of Maine and Slope Water, Limnol. Oceanogr., 66, 3472–3488, https://doi.org/10.1002/lno.11892, 2021. a, b, c, d
Sein, D. V., Koldunov, N. V., Danilov, S., Wang, Q., Sidorenko, D., Fast, I., Rackow, T., Cabos, W., and Jung, T.: Ocean Modeling on a Mesh With Resolution Following the Local Rossby Radius, J. Adv. Model. Earth Sy., 9, 2601–2614, https://doi.org/10.1002/2017MS001099, 2017. a
Shin, S.-I. and Newman, M.: Seasonal Predictability of Global and North American Coastal Sea Surface Temperature and Height Anomalies, Geophys. Res. Lett., 48, e2020GL091886, https://doi.org/10.1029/2020GL091886, 2021. a
Shropshire, T. A., Morey, S. L., Chassignet, E. P., Bozec, A., Coles, V. J., Landry, M. R., Swalethorp, R., Zapfe, G., and Stukel, M. R.: Quantifying spatiotemporal variability in zooplankton dynamics in the Gulf of Mexico with a physical–biogeochemical model, Biogeosciences, 17, 3385–3407, https://doi.org/10.5194/bg-17-3385-2020, 2020. a
Siedlecki, S., Salisbury, J., Gledhill, D., Bastidas, C., Meseck, S., McGarry, K., Hunt, C., Alexander, M., Lavoie, D., Wang, Z., Scott, J., Brady, D., Mlsna, I., Azetsu-Scott, K., Liberti, C., Melrose, D., White, M., Pershing, A., Vandemark, D., Townsend, D., Chen, C., Mook, W., and Morrison, R.: Projecting Ocean Acidification Impacts for the Gulf of Maine to 2050, Elementa, 9, 00062, https://doi.org/10.1525/elementa.2020.00062, 2021. a
Skákala, J., Bruggeman, J., Brewin, R. J. W., Ford, D. A., and Ciavatta, S.: Improved Representation of Underwater Light Field and Its Impact on Ecosystem Dynamics: A Study in the North Sea, J. Geophys. Res.-Oceans, 125, e2020JC016122, https://doi.org/10.1029/2020JC016122, 2020. a
Skjoldal, H. R., Wiebe, P. H., Postel, L., Knutsen, T., Kaartvedt, S., and Sameoto, D. D.: Intercomparison of Zooplankton (Net) Sampling Systems: Results from the ICES/GLOBEC Sea-Going Workshop, Prog. Oceanogr., 108, 1–42, https://doi.org/10.1016/j.pocean.2012.10.006, 2013. a, b
Stepanov, V. N. and Hughes, C. W.: Parameterization of Ocean Self-Attraction and Loading in Numerical Models of the Ocean Circulation, J. Geophys. Res.-Oceans, 109, C03037, https://doi.org/10.1029/2003JC002034, 2004. a, b, c, d
Sterner, R. W. and Elser, J. J.: Ecological Stoichiometry: The Biology of Elements from Molecules to the Biosphere, Princeton University Press, ISBN 978-1-4008-8569-5, https://doi.org/10.1515/9781400885695, 2003. a
Stets, E. G., Kelly, V. J., and Crawford, C. G.: Long-Term Trends in Alkalinity in Large Rivers of the Conterminous US in Relation to Acidification, Agriculture, and Hydrologic Modification, Sci. Total Environ., 488–489, 280–289, https://doi.org/10.1016/j.scitotenv.2014.04.054, 2014. a
Stock, C. A., Powell, T. M., and Levin, S. A.: Bottom–up and Top–down Forcing in a Simple Size-Structured Plankton Dynamics Model, J. Marine Syst., 74, 134–152, https://doi.org/10.1016/j.jmarsys.2007.12.004, 2008. a
Stock, C. A., Dunne, J. P., and John, J. G.: Global-Scale Carbon and Energy Flows through the Marine Planktonic Food Web: An Analysis with a Coupled Physical–Biological Model, Prog. Oceanogr., 120, 1–28, https://doi.org/10.1016/j.pocean.2013.07.001, 2014. a, b, c
Stock, C. A., Pegion, K., Vecchi, G. A., Alexander, M. A., Tommasi, D., Bond, N. A., Fratantoni, P. S., Gudgel, R. G., Kristiansen, T., O'Brien, T. D., Xue, Y., and Yang, X.: Seasonal Sea Surface Temperature Anomaly Prediction for Coastal Ecosystems, Prog. Oceanogr., 137, 219–236, https://doi.org/10.1016/j.pocean.2015.06.007, 2015. a, b
Stock, C. A., Dunne, J. P., Fan, S., Ginoux, P., John, J., Krasting, J. P., Laufkötter, C., Paulot, F., and Zadeh, N.: Ocean Biogeochemistry in GFDL's Earth System Model 4.1 and Its Response to Increasing Atmospheric CO2, J. Adv. Model. Earth Sy., 12, e2019MS002043, https://doi.org/10.1029/2019MS002043, 2020. a, b, c, d, e
Sutula, M., Bianchi, T. S., and McKee, B. A.: Effect of Seasonal Sediment Storage in the Lower Mississippi River on the Flux of Reactive Particulate Phosphorus to the Gulf of Mexico, Limnol. Oceanogr., 49, 2223–2235, https://doi.org/10.4319/lo.2004.49.6.2223, 2004. a
Talmy, D., Blackford, J., Hardman-Mountford, N. J., Dumbrell, A. J., and Geider, R. J.: An Optimality Model of Photoadaptation in Contrasting Aquatic Light Regimes, Limnol. Oceanogr., 58, 1802–1818, https://doi.org/10.4319/lo.2013.58.5.1802, 2013. a
Taylor, M. H. and Mountain, D. G.: The Influence of Surface Layer Salinity on Wintertime Convection in Wilkinson Basin, Gulf of Maine, Cont. Shelf Res., 29, 433–444, https://doi.org/10.1016/j.csr.2008.11.002, 2009. a
Ting, M., Kushnir, Y., Seager, R., and Li, C.: Forced and Internal Twentieth-Century SST Trends in the North Atlantic, J. Climate, 22, 1469–1481, https://doi.org/10.1175/2008JCLI2561.1, 2009. a
Tommasi, D., Stock, C. A., Alexander, M. A., Yang, X., Rosati, A., and Vecchi, G. A.: Multi-Annual Climate Predictions for Fisheries: An Assessment of Skill of Sea Surface Temperature Forecasts for Large Marine Ecosystems, Front. Mar. Sci., 4, https://doi.org/10.3389/fmars.2017.00201, 2017a. a, b
Tommasi, D., Stock, C. A., Hobday, A. J., Methot, R., Kaplan, I. C., Eveson, J. P., Holsman, K., Miller, T. J., Gaichas, S., Gehlen, M., Pershing, A., Vecchi, G. A., Msadek, R., Delworth, T., Eakin, C. M., Haltuch, M. A., Séférian, R., Spillman, C. M., Hartog, J. R., Siedlecki, S., Samhouri, J. F., Muhling, B., Asch, R. G., Pinsky, M. L., Saba, V. S., Kapnick, S. B., Gaitan, C. F., Rykaczewski, R. R., Alexander, M. A., Xue, Y., Pegion, K. V., Lynch, P., Payne, M. R., Kristiansen, T., Lehodey, P., and Werner, F. E.: Managing Living Marine Resources in a Dynamic Environment: The Role of Seasonal to Decadal Climate Forecasts, Prog. Oceanogr., 152, 15–49, https://doi.org/10.1016/j.pocean.2016.12.011, 2017b. a, b
Tommasi, D., Stock, C. A., Pegion, K., Vecchi, G. A., Methot, R. D., Alexander, M. A., and Checkley, D. M.: Improved Management of Small Pelagic Fisheries through Seasonal Climate Prediction, Ecol. Appl., 27, 378–388, https://doi.org/10.1002/eap.1458, 2017c. a
Townsend, D. W., McGillicuddy, D. J., Thomas, M. A., and Rebuck, N. D.: Nutrients and Water Masses in the Gulf of Maine–Georges Bank Region: Variability and Importance to Blooms of the Toxic Dinoflagellate Alexandrium Fundyense, Deep-Sea Res. Pt. II, 103, 238–263, https://doi.org/10.1016/j.dsr2.2013.08.003, 2014. a
Turley, B. D., Karnauskas, M., Campbell, M. D., Hanisko, D. S., and Kelble, C. R.: Relationships between Blooms of Karenia Brevis and Hypoxia across the West Florida Shelf, Harmful Algae, 114, 102223, https://doi.org/10.1016/j.hal.2022.102223, 2022. a
Turner, R. E.: Declining Bacteria, Lead, and Sulphate, and Rising pH and Oxygen in the Lower Mississippi River, Ambio, 50, 1731–1738, https://doi.org/10.1007/s13280-020-01499-2, 2021. a
Van Oostende, N., Dussin, R., Stock, C., Barton, A., Curchitser, E., Dunne, J., and Ward, B.: Simulating the Ocean's Chlorophyll Dynamic Range from Coastal Upwelling to Oligotrophy, Prog. Oceanogr., 168, 232–247, https://doi.org/10.1016/j.pocean.2018.10.009, 2018. a, b
Waldbusser, G. G., Hales, B., Langdon, C. J., Haley, B. A., Schrader, P., Brunner, E. L., Gray, M. W., Miller, C. A., and Gimenez, I.: Saturation-State Sensitivity of Marine Bivalve Larvae to Ocean Acidification, Nat. Clim. Change, 5, 273–280, https://doi.org/10.1038/nclimate2479, 2015. a
Wallinga, J., Pettirew, N., and Irish, J.: The GoMOOS moored buoy design, in: Oceans 2003, Celebrating the Past ... Teaming Toward the Future, vol. 5, 2596–2599, https://doi.org/10.1109/OCEANS.2003.178318, 2003. a
Wang, Z., Yang, J., Johnson, C., and DeTracey, B.: Changes in Deep Ocean Contribute to a “See-Sawing” Gulf Stream Path, Geophys. Res. Lett., 49, e2022GL100937, https://doi.org/10.1029/2022GL100937, 2022. a
Wang, Z., Boyer, T., Reagan, J., and Hogan, P.: Upper Oceanic Warming in the Gulf of Mexico between 1950 and 2020, J. Climate, 36, 2721–2734, https://doi.org/10.1175/JCLI-D-22-0409.1, 2023. a
Wiegner, T. N., Seitzinger, S. P., Glibert, P. M., and Bronk, D. A.: Bioavailability of Dissolved Organic Nitrogen and Carbon from Nine Rivers in the Eastern United States, Aquat. Microb. Ecol., 43, 277–287, https://doi.org/10.3354/ame043277, 2006. a
Xu, H., Kim, H.-M., Nye, J. A., and Hameed, S.: Impacts of the North Atlantic Oscillation on Sea Surface Temperature on the Northeast US Continental Shelf, Cont. Shelf Res., 105, 60–66, https://doi.org/10.1016/j.csr.2015.06.005, 2015. a
Xu, X., Schmitz Jr., W. J., Hurlburt, H. E., Hogan, P. J., and Chassignet, E. P.: Transport of Nordic Seas Overflow Water into and within the Irminger Sea: An Eddy-Resolving Simulation and Observations, J. Geophys. Res.-Oceans, 115, C12048, https://doi.org/10.1029/2010JC006351, 2010. a
Zaron, E. D.: Predictability of non-phase-locked baroclinic tides in the Caribbean Sea, Ocean Sci., 15, 1287–1305, https://doi.org/10.5194/os-15-1287-2019, 2019. a
Zsoter, E., Harrigan, S., Barnard, C., Wetterhall, F., Ferrario, I., Mazzetti, C., Alfieri, L., Salamon, P., ad Prudhomme, C.: River discharge and related historical data from the Global Flood Awareness System, v3.1., Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.a4fdd6b9, 2021. a
Short summary
We evaluate a model for northwest Atlantic Ocean dynamics and biogeochemistry that balances high resolution with computational economy by building on the new regional features in the MOM6 ocean model and COBALT biogeochemical model. We test the model's ability to simulate impactful historical variability and find that the model simulates the mean state and variability of most features well, which suggests the model can provide information to inform living-marine-resource applications.
We evaluate a model for northwest Atlantic Ocean dynamics and biogeochemistry that balances high...
