Articles | Volume 22, issue 5
https://doi.org/10.5194/os-22-3017-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/os-22-3017-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
05 Oct 2026
Research article |
| 05 Oct 2026
| 05 Oct 2026
Decadal biogeochemical predictions for the changing bottom marine environment of the Gulf of Maine
Vimal Koul
CORRESPONDING AUTHOR
Cooperative Institute for Modeling the Earth System, Princeton University, Princeton, New Jersey, United States
now at: Centre for Atmospheric Sciences, Indian Institute of Technology Delhi, New Delhi, India
Andrew C. Ross
NOAA/OAR/Geophysical Fluid Dynamics Laboratory, Princeton, New Jersey, United States
Charles Stock
NOAA/OAR/Geophysical Fluid Dynamics Laboratory, Princeton, New Jersey, United States
Liping Zhang
NOAA/OAR/Geophysical Fluid Dynamics Laboratory, Princeton, New Jersey, United States
Andrew T. Wittenberg
NOAA/OAR/Geophysical Fluid Dynamics Laboratory, Princeton, New Jersey, United States
Thomas Delworth
NOAA/OAR/Geophysical Fluid Dynamics Laboratory, Princeton, New Jersey, United States
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Andrew C. Ross, Charles A. Stock, Alistair Adcroft, Enrique Curchitser, Robert Hallberg, Matthew J. Harrison, Katherine Hedstrom, Niki Zadeh, Michael Alexander, Wenhao Chen, Elizabeth J. Drenkard, Hubert du Pontavice, Raphael Dussin, Fabian Gomez, Jasmin G. John, Dujuan Kang, Diane Lavoie, Laure Resplandy, Alizée Roobaert, Vincent Saba, Sang-Ik Shin, Samantha Siedlecki, and James Simkins
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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
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Fabian A. Gomez, Sang-Ki Lee, Charles A. Stock, Andrew C. Ross, Laure Resplandy, Samantha A. Siedlecki, Filippos Tagklis, and Joseph E. Salisbury
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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.
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Short summary
Predicting coastal ocean conditions years ahead has been difficult due to complex regional dynamics. This work shows we can forecast bottom temperature, oxygen, and acidity up to a decade ahead for the Northeast US Shelf. Our forecasts indicate increasing Labrador water may accelerate acidification, threatening shell-forming organisms. This provides a foundation for early warning systems to help communities and fisheries adapt proactively.
Predicting coastal ocean conditions years ahead has been difficult due to complex regional...
