Cheng Wei

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  • Article
    Observational needs supporting marine ecosystems modeling and forecasting: from the global ocean to regional and coastal systems
    (Frontiers Media, 2019-10-15) Capotondi, Antonietta ; Jacox, Michael ; Bowler, Chris ; Kavanaugh, Maria T. ; Lehodey, Patrick ; Barrie, Daniel ; Brodie, Stephanie ; Chaffron, Samuel ; Cheng, Wei ; Dias, Daniela F. ; Eveillard, Damien ; Guidi, Lionel ; Iudicone, Daniele ; Lovenduski, Nicole S. ; Nye, Janet A. ; Ortiz, Ivonne ; Pirhalla, Douglas ; Pozo Buil, Mercedes ; Saba, Vincent S. ; Sheridan, Scott ; Siedlecki, Samantha A. ; Subramanian, Aneesh C. ; de Vargas, Colomban ; Di Lorenzo, Emanuele ; Doney, Scott C. ; Hermann, Albert J. ; Joyce, Terrence M. ; Merrifield, Mark ; Miller, Arthur J. ; Not, Fabrice ; Pesant, Stephane
    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.
  • Article
    Seasonal-to-interannual prediction of North American coastal marine ecosystems: forecast methods, mechanisms of predictability, and priority developments
    (Elsevier, 2020-02-20) Jacox, Michael ; Alexander, Michael A. ; Siedlecki, Samantha A. ; Chen, Ke ; Kwon, Young-Oh ; Brodie, Stephanie ; Ortiz, Ivonne ; Tommasi, Desiree ; Widlansky, Matthew J. ; Barrie, Daniel ; Capotondi, Antonietta ; Cheng, Wei ; Di Lorenzo, Emanuele ; Edwards, Christopher ; Fiechter, Jerome ; Fratantoni, Paula S. ; Hazen, Elliott L. ; Hermann, Albert J. ; Kumar, Arun ; Miller, Arthur J. ; Pirhalla, Douglas ; Pozo Buil, Mercedes ; Ray, Sulagna ; Sheridan, Scott ; Subramanian, Aneesh C. ; Thompson, Philip ; Thorne, Lesley ; Annamalai, Hariharasubramanian ; Aydin, Kerim ; Bograd, Steven ; Griffis, Roger B. ; Kearney, Kelly ; Kim, Hyemi ; Mariotti, Annarita ; Merrifield, Mark ; Rykaczewski, Ryan R.
    Marine ecosystem forecasting is an area of active research and rapid development. Promise has been shown for skillful prediction of physical, biogeochemical, and ecological variables on a range of timescales, suggesting potential for forecasts to aid in the management of living marine resources and coastal communities. However, the mechanisms underlying forecast skill in marine ecosystems are often poorly understood, and many forecasts, especially for biological variables, rely on empirical statistical relationships developed from historical observations. Here, we review statistical and dynamical marine ecosystem forecasting methods and highlight examples of their application along U.S. coastlines for seasonal-to-interannual (1–24 month) prediction of properties ranging from coastal sea level to marine top predator distributions. We then describe known mechanisms governing marine ecosystem predictability and how they have been used in forecasts to date. These mechanisms include physical atmospheric and oceanic processes, biogeochemical and ecological responses to physical forcing, and intrinsic characteristics of species themselves. In reviewing the state of the knowledge on forecasting techniques and mechanisms underlying marine ecosystem predictability, we aim to facilitate forecast development and uptake by (i) identifying methods and processes that can be exploited for development of skillful regional forecasts, (ii) informing priorities for forecast development and verification, and (iii) improving understanding of conditional forecast skill (i.e., a priori knowledge of whether a forecast is likely to be skillful). While we focus primarily on coastal marine ecosystems surrounding North America (and the U.S. in particular), we detail forecast methods, physical and biological mechanisms, and priority developments that are globally relevant.