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Skillful multi-month predictions of ecosystem stressors in the surface and subsurface ocean
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  • Samuel Mogen,
  • Nicole Suzanne Lovenduski,
  • Stephen Yeager,
  • Lydia Keppler,
  • Jonathan Sharp,
  • Steven J. Bograd,
  • Nathalí Cordero Quirós,
  • Emanuele Di Lorenzo,
  • Elliott L. Hazen,
  • Michael G Jacox,
  • Mercedes Pozo Buil
Samuel Mogen
University of Colorado Boulder

Corresponding Author:samuel.mogen@colorado.edu

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Nicole Suzanne Lovenduski
University of Colorado Boulder
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Stephen Yeager
National Center for Atmospheric Research
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Lydia Keppler
Scripps Institution of Oceanography
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Jonathan Sharp
University of Washington
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Steven J. Bograd
Southwest Fisheries Science Centre, NOAA Fisheries Service
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Nathalí Cordero Quirós
University of California Santa Cruz
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Emanuele Di Lorenzo
Georgia Institute of Technology
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Elliott L. Hazen
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Michael G Jacox
NOAA Fisheries
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Mercedes Pozo Buil
University of California Santa Cruz
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Anthropogenic carbon emissions and associated climate change are driving rapid warming, acidification, and deoxygenation in the ocean, which increasingly stress marine ecosystems. On top of long-term trends, short term variability of marine stressors can have major implications for marine ecosystems and their management. As such, there is a growing need for predictions of marine ecosystems on monthly, seasonal, and multi-month timescales. Previous studies have demonstrated the ability to make reliable predictions of the surface ocean physical and biogeochemical state months to years in advance, but few studies have investigated forecasts of multiple stressors simultaneously or assessed the forecast skill below the surface. Here, we use the Community Earth System Model (CESM) Seasonal to Multiyear Large Ensemble (SMYLE) along with novel observation-based biogeochemical and physical products to quantify the predictive skill of dissolved inorganic carbon, dissolved oxygen, and temperature in the surface and subsurface ocean. CESM SMYLE demonstrates high physical and biogeochemical predictive skill multiple months in advance in key oceanic regions and frequently outperforms persistence forecasts. We find up to 10 months of skillful forecasts, with particularly high skill in the Northeast Pacific (Gulf of Alaska and California Current Large Marine Ecosystems) for temperature, surface DIC, and subsurface oxygen. Our findings suggest that dynamical marine ecosystem prediction could support actionable advice for decision making.
03 Apr 2023Submitted to ESS Open Archive
04 Apr 2023Published in ESS Open Archive