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Issues in stochastic ocean modeling

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The general theory of stochastic differential equations is presented in this chapter, including the theoretical background on how measured statistics from time series can be used to develop a stochastic parameterization. The general rules of stochastic calculus, including the important and often overlooked differences between Ito and Stratonovich calculus, are mentioned, and references are provided in which more detail may be found. We discuss how Stratonovich calculus is usually appropriate for fluid systems, whereas Ito calculus is often appropriate for data assimilation. We also discuss some common numerical pitfalls awaiting the unwary modeler, and warn against unsophisticated random number generators. Finally, we offer a selection of examples showing the importance of the variability of unresolved scales in an ocean model and, by citation, a variety of methods that have been employed.
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Keywords: . STOCHASTIC MODELING; AIR-SEA INTERACTION; CENTRAL LIMIT THEOREM; ENSEMBLE FORECASTING; MULTISCALE INTERACTIONS; NUMERICAL MODELING; OCEAN DYNAMICS; OCEAN PREDICTIONS; PARAMETERIZATION; PREDICTABILITY

Document Type: Research Article

Publication date: November 1, 2017

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  • The Journal of Marine Research, one of the oldest journals in American marine science, publishes peer-reviewed research articles covering a broad array of topics in physical, biological and chemical oceanography. Articles that deal with processes, as well as those that report significant observations, are welcome. Biological studies involving coupling between ecological and physical processes are preferred over those that report systematics. The editors strive always to serve authors and readers in the academic oceanographic community by publishing papers vital to the marine research in the long and rich tradition of the Sears Foundation for Marine Research. We welcome you to the Journal of Marine Research.
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