DARLA: Data Assimilation and Remote Sensing for Littoral Applications
University of Washington Seattle United States
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Our long-term goal was to use remote sensing observations to constrain a data assimilation model of wave and circulation dynamics in an area characterized by a river mouth or tidal inlet and surrounding beaches. As a result of this activity, we have improved environmental parameter estimation via remote sensing fusion, determined the success of using remote sensing data to drive DA models, and produced a dynamically consistent representation of the wave, circulation, and bathymetry fields in complex environments.
- Physical and Dynamic Oceanography
- Active and Passive Radar Detection and Equipment