Skillful Multi‐Month Predictions of Ecosystem Stressors in the Surface and Subsurface Ocean
Supporting Files
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2023
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Details
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Journal Title:Earth's Future
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Personal Author:
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NOAA Program & Office:NESDIS (National Environmental Satellite, Data, and Information Service) ; NMFS (National Marine Fisheries Service) ; OAR (Oceanic and Atmospheric Research) ; CICOES (Cooperative Institute for Climate, Ocean and Ecosystem Studies) ; NCEI (National Centers for Environmental Information) ; PMEL (Pacific Marine Environmental Laboratory) ; PSL (Physical Sciences Laboratory) ; SWFSC (Southwest Fisheries Science Center)
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Description: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 ecosystem stressors 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 forecast skill 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 (DIC), 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.
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Source:Earth's Future, 11(11)
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DOI:
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ISSN:2328-4277 ; 2328-4277
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Rights Information:CC BY-NC-ND
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Compliance:Library
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Main Document Checksum:urn:sha256:dce8ccb16d2750538bfeb47b42d9fb824448fa87041f59239cb753d76b139541
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Supporting Files
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