Assimilation of HF Radar-Derived Radials and Total Currents in the Monterey Bay Area
NAVAL RESEARCH LAB STENNIS SPACE CENTER MS OCEANOGRAPHY DIV
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Impact of HF radar surface-current assimilation on ocean circulation model predictions in the Monterey Bay area is studied and evaluated during the time frame of the Autonomous Ocean Sampling Network AOSN-II experiment August-September 2003. In the first instance, a previously described method for assimilation of surface current data is applied to 33-h low-pass-filtered data and a non-tidal version of the circulation model. It is demonstrated that assimilation of surface velocity data improves the surface and subsurface correlation of model currents with moored current observations. These results from the AOSN-II period illustrate that surface-current assimilation is beneficial even in cases for which very high-resolution 3 km atmospheric forcing is utilized. The assimilation approach is also tested with hourly, unfiltered, CODAR-type HF radar-derived surface currents configuration that includes tidal forcing. It is shown, that assimilation of unfiltered with tides surface- current observations into the model with tides improves the sub-tidal model predictions to the level comparable with the assimilation of filtered data into the non-tidal model, which is respect to options for designing real-time nowcast and forecast systems. Finally, one approach is extended and evaluated for the direct assimilation of HF radar-derived radial velocity components. The model runs that included assimilation of radials from at least two HF radar sites show better correlations with observations than the non-assimilative run, especially those runs that from the Santa Cruz site. Directions of radials for that site coincide with the directions southward flow during upwelling events and the northward flow during relaxation assimilation of radial currents extends the range of influence of the data into regions covered by only one HF radar site.
- Physical and Dynamic Oceanography
- Active and Passive Radar Detection and Equipment