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Sea Ice Mapping Method For Seawinds, David G. Long, Hyrum S. Anderson
Sea Ice Mapping Method For Seawinds, David G. Long, Hyrum S. Anderson
Faculty Publications
A sea ice mapping algorithm for SeaWinds is developed that incorporates statistical and spatial a priori information in a modified maximum a posteriori (MAP) framework. Spatial a priori data are incorporated in the loss terms of a Bayes risk formulation. Conditional distributions and priors for sea ice and ocean statistics are represented as empirical histograms that are forced to conform to a set of expected histograms via principal component filtering. Tuning parameters for the algorithm allow adjustments in the algorithm's performance. Results of the algorithm exhibit high correlation with the Remund-Long sea ice mapping algorithm for SeaWinds and the Special …