Observational needs supporting marine ecosystems modeling and forecasting: from the global ocean to regional and coastal systems

© The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Capotondi, A., Jacox, M., Bowler, C., Kavanaugh, M., Lehodey, P., Barrie, D., Brodie, S., Chaffron, S., Cheng, W., Dias, D. F., Eveillard, D., Guidi, L., Iudicone, D., Lovenduski, N. S., Nye, J. A., Ortiz, I., Pirhalla, D., Buil, M. P., Saba, V., Sheridan, S., Siedlecki, S., Subramanian, A., de Vargas, C., Di Lorenzo, E., Doney, S. C., Hermann, A. J., Joyce, T., Merrifield, M., Miller, A. J., Not, F., & Pesant, S. Observational needs supporting marine ecosystems modeling and forecasting: from the global ocean to regional and coastal systems. Frontiers in Marine Science, 6, (2019): 623, doi:10.3389/fmars.2019.00623.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.This study was supported by the NOAA’s Climate Program Office’s Modeling, Analysis, Predictions, and Projections (MAPP) Program through grants NA17OAR4310106, NA17OAR4310104, NA17OAR4310108, NA17OAR4310109, NA17OAR4310110, NA17OAR4310111, NA17OAR4310112, and NA17OAR4310113. This manuscript is a product of the NOAA/MAPP Marine Prediction Task Force. The Tara Oceans consortium acknowledges support from the CNRS Research Federation FR2022 Global Ocean Systems Ecology and Evolution, and OCEANOMICS (grant agreement ‘Investissement d’Avenir’ ANR-11-BTBR-0008). This is article number 95 of the Tara Oceans consortium. MK and SD acknowledge support from NASA grant NNX14AP62A “National Marine Sanctuaries as Sentinel Sites for a Demonstration Marine Biodiversity Observation Network (MBON)” funded under the National Ocean Partnership Program (NOPP RFP NOAA-NOS-IOOS-2014-2003803 in partnership between NOAA, BOEM, and NASA), and the NOAA Integrated Ocean Observing System (IOOS) Program Office. WC, IO, and AH acknowledge partial support from the Joint Institute for the Study of the Atmosphere and Ocean (JISAO) under NOAA Cooperative Agreement NA15OAR4320063, Contribution No. 2019-1029. This study received support from the European H2020 International Cooperation project MESOPP (Mesopelagic Southern Ocean Prey and Predators), grant agreement no. 692173