Abstract

In crisis situations, military operating units require a rapid evaluation of the local meteorological and oceanographic (METOC) conditions affecting their missions. An important role of military oceanography (MILOC) is thus to provide a timely METOC characterization of denied littoral areas [1]. Environmental sampling procedures in MILOC must be easily relocatable, discreet, and secure. Until recently, marine sampling technologies meeting these requirements were scarce. Remote sensing is the technology mostly used by navies to assess environmental conditions in restricted areas [2]. Very-near-shore bathymetry, sea state, surface currents, ocean color, and sea surface temperature (SST) are among the pieces of environmental information that can be obtained by means of remote sensors. Although valuable, this information is not sufficient to fully assess the three-dimensional (3-D) variability of the environment. Numerical approaches that simulate the ocean dynamics may provide additional information on the environmental conditions. In the coastal regions, numerical ocean models of different spatiotemporal resolutions are generally nested to downscale METOC information to the region of interest [3]. Numerical procedures used to feed back dynamical information between the models with different resolutions inevitably introduce errors in this nesting process. In addition, at present, the uncertainties in physical parameterizations, forcing, and model initialization limit the accuracy of model forecasts.

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