A regional physical–biogeochemical ocean model for marine resource applications in the Northeast Pacific (MOM6-COBALT-NEP10k v1.0)
<p>Regional ocean models enable the generation of computationally affordable and regionally tailored ensembles of near-term forecasts and long-term projections of sufficient resolution to serve marine resource management. Climate change, however, has created marine resource challenges, such as...
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Copernicus Publications
2025-08-01
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| Series: | Geoscientific Model Development |
| Online Access: | https://gmd.copernicus.org/articles/18/5245/2025/gmd-18-5245-2025.pdf |
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| author | E. J. Drenkard C. A. Stock A. C. Ross Y.-C. Teng T. Cordero W. Cheng W. Cheng A. Adcroft A. Adcroft E. Curchitser R. Dussin R. Dussin R. Hallberg C. Hauri K. Hedstrom A. Hermann A. Hermann M. G. Jacox M. G. Jacox K. A. Kearney R. Pagès D. J. Pilcher D. J. Pilcher M. Pozo Buil V. Seelanki V. Seelanki N. Zadeh |
| author_facet | E. J. Drenkard C. A. Stock A. C. Ross Y.-C. Teng T. Cordero W. Cheng W. Cheng A. Adcroft A. Adcroft E. Curchitser R. Dussin R. Dussin R. Hallberg C. Hauri K. Hedstrom A. Hermann A. Hermann M. G. Jacox M. G. Jacox K. A. Kearney R. Pagès D. J. Pilcher D. J. Pilcher M. Pozo Buil V. Seelanki V. Seelanki N. Zadeh |
| author_sort | E. J. Drenkard |
| collection | DOAJ |
| description | <p>Regional ocean models enable the generation of computationally affordable and regionally tailored ensembles of near-term forecasts and long-term projections of sufficient resolution to serve marine resource management. Climate change, however, has created marine resource challenges, such as shifting stock distributions, that cut across domestic and international management boundaries and have pushed regional modeling efforts toward “coastwide” approaches. Here, we present and evaluate a multidecadal hindcast with a Northeast Pacific regional implementation of the Modular Ocean Model, version 6, with sea ice and biogeochemistry that extends from the Chukchi Sea to the Baja California Peninsula at 10 km horizontal resolution (MOM6-COBALT-NEP10k, or NEP10k). This domain includes an Arctic-adjacent system with a broad, shallow shelf seasonally covered by sea ice (the eastern Bering Sea), a sub-Arctic system with upwelling in the Alaska Gyre and predominant downwelling winds and large freshwater forcing along the coast (the Gulf of Alaska), and a temperate, eastern boundary upwelling ecosystem (the California Current Ecosystem). The coastwide model was able to recreate seasonal and cross-ecosystem contrasts in numerous ecosystem-critical properties including temperature, salinity, inorganic nutrients, oxygen, carbonate saturation states, and chlorophyll. Spatial consistency between modeled quantities and observations generally extended to plankton ecosystems, though small to moderate biases were also apparent. Fidelity with observed zooplankton biomass, for example, was limited to first-order seasonal and cross-system contrasts. Temporally, simulated monthly surface and bottom temperature anomalies in coastal regions (<span class="inline-formula"><500</span> m deep) closely matched estimates from data-assimilative ocean reanalyses. Performance, however, was reduced in some nearshore regions coarsely resolved by the model's 10 km resolution grid and for point<span id="page5246"/> measurements. The time series of satellite-based chlorophyll anomaly estimates proved more difficult to match than temperature. System-specific ecosystem indicators were also assessed. In the eastern Bering Sea, NEP10k robustly matched observed variations, including recent large declines, in the area of the summer bottom water “cold pool” (<span class="inline-formula"><2</span> <span class="inline-formula">°C</span>), which exerts a profound influence on eastern Bering Sea fisheries. In the Gulf of Alaska, the simulation captured patterns of sea surface height variability and variations in thermal, oxygen, and acidification risk associated with local modes of interannual to decadal climate variability. In the California Current Ecosystem, the simulation robustly captured variations in upwelling indices and coastal water masses, though discrepancies in the latter were evident in the Southern California Bight. Enhanced model resolution may reduce such discrepancies, but any benefits must be carefully weighed against computational costs given the intended use of this system for ensemble predictions and projections. Meanwhile, the demonstrated NEP10k skill level herein, particularly in recreating cross-ecosystem contrasts and the time variation of ecosystem indicators over multiple decades, suggests considerable immediate utility for coastwide retrospective and predictive applications.</p> |
| format | Article |
| id | doaj-art-fb5af2dde27448cd9235af58f5598706 |
| institution | Kabale University |
| issn | 1991-959X 1991-9603 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Geoscientific Model Development |
| spelling | doaj-art-fb5af2dde27448cd9235af58f55987062025-08-26T04:56:15ZengCopernicus PublicationsGeoscientific Model Development1991-959X1991-96032025-08-01185245529010.5194/gmd-18-5245-2025A regional physical–biogeochemical ocean model for marine resource applications in the Northeast Pacific (MOM6-COBALT-NEP10k v1.0)E. J. Drenkard0C. A. Stock1A. C. Ross2Y.-C. Teng3T. Cordero4W. Cheng5W. Cheng6A. Adcroft7A. Adcroft8E. Curchitser9R. Dussin10R. Dussin11R. Hallberg12C. Hauri13K. Hedstrom14A. Hermann15A. Hermann16M. G. Jacox17M. G. Jacox18K. A. Kearney19R. Pagès20D. J. Pilcher21D. J. Pilcher22M. Pozo Buil23V. Seelanki24V. Seelanki25N. Zadeh26NOAA/OAR/GFDL, Princeton, NJ 08540, USANOAA/OAR/GFDL, Princeton, NJ 08540, USANOAA/OAR/GFDL, Princeton, NJ 08540, USANOAA/OAR/GFDL, Princeton, NJ 08540, USANOAA/OAR/GFDL, Princeton, NJ 08540, USANOAA/OAR/PMEL, Seattle, WA 98115, USACooperative Institute for Climate, Ocean, and Ecosystem Studies, University of Washington, Seattle, WA 98195, USANOAA/OAR/GFDL, Princeton, NJ 08540, USAAtmospheric and Oceanic Science, Princeton University, Princeton, NJ 08544, USARutgers the State University of New Jersey, New Brunswick, NJ 08901, USANOAA/OAR/GFDL, Princeton, NJ 08540, USACooperative Programs for the Advancement of Earth System Science, University Corporation for Atmospheric Research, Boulder, CO 80307, USANOAA/OAR/GFDL, Princeton, NJ 08540, USAInternational Arctic Research Center, University of Alaska Fairbanks, Fairbanks, AK 99775, USACollege of Fisheries and Ocean Sciences, University of Alaska Fairbanks, Fairbanks, AK 99775, USANOAA/OAR/PMEL, Seattle, WA 98115, USACooperative Institute for Climate, Ocean, and Ecosystem Studies, University of Washington, Seattle, WA 98195, USANOAA/NMFS/SWFSC, Monterey, CA 93940, USANOAA/OAR/PSL, Boulder, CO 80305, USANOAA/NMFS/AFSC, Seattle, WA 98115, USAInternational Arctic Research Center, University of Alaska Fairbanks, Fairbanks, AK 99775, USANOAA/OAR/PMEL, Seattle, WA 98115, USACooperative Institute for Climate, Ocean, and Ecosystem Studies, University of Washington, Seattle, WA 98195, USAInstitute of Marine Sciences, University of California, Santa Cruz, Santa Cruz, CA 95064, USANOAA/OAR/PMEL, Seattle, WA 98115, USACooperative Institute for Climate, Ocean, and Ecosystem Studies, University of Washington, Seattle, WA 98195, USANOAA/OAR/GFDL, Princeton, NJ 08540, USA<p>Regional ocean models enable the generation of computationally affordable and regionally tailored ensembles of near-term forecasts and long-term projections of sufficient resolution to serve marine resource management. Climate change, however, has created marine resource challenges, such as shifting stock distributions, that cut across domestic and international management boundaries and have pushed regional modeling efforts toward “coastwide” approaches. Here, we present and evaluate a multidecadal hindcast with a Northeast Pacific regional implementation of the Modular Ocean Model, version 6, with sea ice and biogeochemistry that extends from the Chukchi Sea to the Baja California Peninsula at 10 km horizontal resolution (MOM6-COBALT-NEP10k, or NEP10k). This domain includes an Arctic-adjacent system with a broad, shallow shelf seasonally covered by sea ice (the eastern Bering Sea), a sub-Arctic system with upwelling in the Alaska Gyre and predominant downwelling winds and large freshwater forcing along the coast (the Gulf of Alaska), and a temperate, eastern boundary upwelling ecosystem (the California Current Ecosystem). The coastwide model was able to recreate seasonal and cross-ecosystem contrasts in numerous ecosystem-critical properties including temperature, salinity, inorganic nutrients, oxygen, carbonate saturation states, and chlorophyll. Spatial consistency between modeled quantities and observations generally extended to plankton ecosystems, though small to moderate biases were also apparent. Fidelity with observed zooplankton biomass, for example, was limited to first-order seasonal and cross-system contrasts. Temporally, simulated monthly surface and bottom temperature anomalies in coastal regions (<span class="inline-formula"><500</span> m deep) closely matched estimates from data-assimilative ocean reanalyses. Performance, however, was reduced in some nearshore regions coarsely resolved by the model's 10 km resolution grid and for point<span id="page5246"/> measurements. The time series of satellite-based chlorophyll anomaly estimates proved more difficult to match than temperature. System-specific ecosystem indicators were also assessed. In the eastern Bering Sea, NEP10k robustly matched observed variations, including recent large declines, in the area of the summer bottom water “cold pool” (<span class="inline-formula"><2</span> <span class="inline-formula">°C</span>), which exerts a profound influence on eastern Bering Sea fisheries. In the Gulf of Alaska, the simulation captured patterns of sea surface height variability and variations in thermal, oxygen, and acidification risk associated with local modes of interannual to decadal climate variability. In the California Current Ecosystem, the simulation robustly captured variations in upwelling indices and coastal water masses, though discrepancies in the latter were evident in the Southern California Bight. Enhanced model resolution may reduce such discrepancies, but any benefits must be carefully weighed against computational costs given the intended use of this system for ensemble predictions and projections. Meanwhile, the demonstrated NEP10k skill level herein, particularly in recreating cross-ecosystem contrasts and the time variation of ecosystem indicators over multiple decades, suggests considerable immediate utility for coastwide retrospective and predictive applications.</p>https://gmd.copernicus.org/articles/18/5245/2025/gmd-18-5245-2025.pdf |
| spellingShingle | E. J. Drenkard C. A. Stock A. C. Ross Y.-C. Teng T. Cordero W. Cheng W. Cheng A. Adcroft A. Adcroft E. Curchitser R. Dussin R. Dussin R. Hallberg C. Hauri K. Hedstrom A. Hermann A. Hermann M. G. Jacox M. G. Jacox K. A. Kearney R. Pagès D. J. Pilcher D. J. Pilcher M. Pozo Buil V. Seelanki V. Seelanki N. Zadeh A regional physical–biogeochemical ocean model for marine resource applications in the Northeast Pacific (MOM6-COBALT-NEP10k v1.0) Geoscientific Model Development |
| title | A regional physical–biogeochemical ocean model for marine resource applications in the Northeast Pacific (MOM6-COBALT-NEP10k v1.0) |
| title_full | A regional physical–biogeochemical ocean model for marine resource applications in the Northeast Pacific (MOM6-COBALT-NEP10k v1.0) |
| title_fullStr | A regional physical–biogeochemical ocean model for marine resource applications in the Northeast Pacific (MOM6-COBALT-NEP10k v1.0) |
| title_full_unstemmed | A regional physical–biogeochemical ocean model for marine resource applications in the Northeast Pacific (MOM6-COBALT-NEP10k v1.0) |
| title_short | A regional physical–biogeochemical ocean model for marine resource applications in the Northeast Pacific (MOM6-COBALT-NEP10k v1.0) |
| title_sort | regional physical biogeochemical ocean model for marine resource applications in the northeast pacific mom6 cobalt nep10k v1 0 |
| url | https://gmd.copernicus.org/articles/18/5245/2025/gmd-18-5245-2025.pdf |
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