Observational Needs Supporting Marine Ecosystems Modeling and Forecasting: From the Global Ocean to Regional and Coastal Systems Public Deposited

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  • Capotondi, A.
    • Other Affiliation: University of Colorado Boulder
  • Jacox, M.
    • Other Affiliation: University of California, Santa Cruz
  • Bowler, C.
    • Other Affiliation: Université PSL
  • Kavanaugh, M.
    • Other Affiliation: Oregon State University
  • Lehodey, P.,
    • Other Affiliation: Collecte Localisation Satellites
  • Barrie, D.
    • Other Affiliation: NOAA Climate Program Office
  • Brodie, S.
    • Other Affiliation: University of California, Santa Cruz
  • Chaffron, S.
    • Other Affiliation: Université de Nantes
  • Cheng, W.
    • Other Affiliation: University of Washington
  • Dias, D.F.
    • Other Affiliation: University of California, San Diego
  • Eveillard, D.
    • Other Affiliation: Université de Nantes
  • Guidi, L.
    • Other Affiliation: Sorbonne Université
  • Iudicone, D.
    • Other Affiliation: Stazione Zoologica Anton Dohrn
  • Lovenduski, N.S.
    • Other Affiliation: University of Colorado Boulder
  • Nye, J.A.
    • Affiliation: Institute of Marine Sciences
    • Other Affiliation: Stony Brook University
  • Ortiz, I.
    • Other Affiliation: University of Washington
  • Pirhalla, D.
    • Other Affiliation: NOAA/NOS/NCCOS
  • Pozo Buil, M.
    • Other Affiliation: University of California, Santa Cruz
  • Saba, V.
    • Other Affiliation: Princeton University
  • Sheridan, S.
    • Other Affiliation: Kent State University
  • Siedlecki, S.
    • Other Affiliation: University of Connecticut
  • Subramanian, A.
    • Other Affiliation: University of Colorado Boulder
  • de Vargas, C.
    • Other Affiliation: Sorbonne Université
  • Di Lorenzo, E.
    • Other Affiliation: Georgia Institute of Technology
  • Doney, S.C.
    • Other Affiliation: University of Virginia
  • Hermann, A.J.
    • Other Affiliation: University of Washington
  • Joyce, T.
    • Other Affiliation: Woods Hole Oceanographic Institution
  • Merrifield, M.
    • Other Affiliation: University of California, San Diego
  • Miller, A.J.
    • Other Affiliation: University of California, San Diego
  • Not, F.
    • Other Affiliation: Sorbonne Université
  • Pesant, S.
    • Other Affiliation: University of Bremen
Abstract
  • Many coastal areas host rich marine ecosystems and are also centers of economic activities, including fishing, shipping and recreation. Due to the socioeconomic and ecological importance of these areas, predicting relevant indicators of the ecosystem state on sub-seasonal to interannual timescales is gaining increasing attention. Depending on the application, forecasts may be sought for variables and indicators spanning physics (e.g., sea level, temperature, currents), chemistry (e.g., nutrients, oxygen, pH), and biology (from viruses to top predators). Many components of the marine ecosystem are known to be influenced by leading modes of climate variability, which provide a physical basis for predictability. However, prediction capabilities remain limited by the lack of a clear understanding of the physical and biological processes involved, as well as by insufficient observations for forecast initialization and verification. The situation is further complicated by the influence of climate change on ocean conditions along coastal areas, including sea level rise, increased stratification, and shoaling of oxygen minimum zones. Observations are thus vital to all aspects of marine forecasting: statistical and/or dynamical model development, forecast initialization, and forecast validation, each of which has different observational requirements, which may be also specific to the study region. Here, we use examples from United States (U.S.) coastal applications to identify and describe the key requirements for an observational network that is needed to facilitate improved process understanding, as well as for sustaining operational ecosystem forecasting. We also describe new holistic observational approaches, e.g., approaches based on acoustics, inspired by Tara Oceans or by landscape ecology, which have the potential to support and expand ecosystem modeling and forecasting activities by bridging global and local observations.
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  • Article
Rights statement
  • In Copyright
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  • Attribution 4.0 International
Journal title
  • Frontiers in Marine Science
Journal volume
  • 6
Language
  • English
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  • Publisher
ISSN
  • 2296-7745
Publisher
  • Frontiers Media S.A.
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