The Coastal Ocean Prediction Systems Program : understanding and managing our coastal ocean - Volume I: Strategic Summary
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The Coastal Ocean Prediction Systems Program : understanding and managing our coastal ocean - Volume I: Strategic Summary

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    COPS Planning Workshop (1989)
  • Description:
    The proposed COPS (Coastal Ocean Prediction Systems) program is concerned with combining numerical models with observations (through data assimilation) to improve our predictive knowledge of the coastal ocean. It is oriented toward applied research and development and depends upon the continued pursuit of basic research in programs like CoOP (Coastal Ocean Processes); i,e., to a significant degree it is involved with "technology transfer" from basic knowledge to operational and management applications. (Here, the term 'prediction' is used in the broad sense to include modeling systems for simulations, hindcasts, nowcasts, and forecasts. Consequently, there is a special emphasis on data-assimilation schemes which benefit from real-time observing systems. Also, here, the term 'coastal ocean' means the entire EEZ plus estuaries and the Great Lakes.) This predictive knowledge is intended to address a variety of societal problems: (1) ship routing, (2) trajectories for search and rescue operations, (3) oil spill trajectory simulations, (4) pollution assessments, (5) fisheries management guidance, (6) simulation of the coastal ocean's response to climate variability, (7) calculation of sediment transport, (8) calculation of forces on structures, and so forth. The initial concern is with physical models and observations in order to provide a capability for the estimation of physical forces and transports in the coastal ocean. For all these applications, there are common needs for physical field estimates: waves, tides, currents, temperature, and salinity, including mixed layers, thermoclines, fronts, jets, etc. However, the intent is to work with biologists, chemists, and geologists in developing integrated multidisciplinary prediction systems as it becomes feasible to do so. From another perspective, by combining observations with models through data assimilation, a modern approach to monitoring is provided through whole-field estimation. These same predictive models can be use J for process-oriented research.
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