Skillful Multi‐Month Predictions of Ecosystem Stressors in the Surface and Subsurface Ocean

Author:

Mogen Samuel C.1ORCID,Lovenduski Nicole S.1ORCID,Yeager Stephen2,Keppler Lydia3ORCID,Sharp Jonathan45ORCID,Bograd Steven J.6ORCID,Quiros Nathali Cordero67ORCID,Di Lorenzo Emanuele8ORCID,Hazen Elliott L.6ORCID,Jacox Michael G.69ORCID,Buil Mercedes Pozo68ORCID

Affiliation:

1. Department of Atmospheric and Oceanic Sciences Institute of Arctic and Alpine Research University of Colorado Boulder CO USA

2. National Center for Atmospheric Research Climate and Global Dynamics Lab Boulder CO USA

3. Scripps Institution of Oceanography University of California San Diego La Jolla CA USA

4. Cooperative Institute for Climate, Ocean, and Ecosystem Studies University of Washington Seattle WA USA

5. National Oceanic and Atmospheric Administration Pacific Marine Environmental Lab Seattle WA USA

6. National Oceanic and Atmospheric Administration Southwest Fisheries Science Center Monterey CA USA

7. Institute of Marine Sciences University of California Santa Cruz CA USA

8. Department of Earth, Environmental and Planetary Sciences Brown University Providence RI USA

9. National Oceanic and Atmospheric Administration Physical Sciences Laboratory Boulder CO USA

Abstract

AbstractAnthropogenic 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.

Funder

National Oceanic and Atmospheric Administration

National Science Foundation

Publisher

American Geophysical Union (AGU)

Subject

Earth and Planetary Sciences (miscellaneous),General Environmental Science

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