Clustering of Satellite Sounding Radiances to Enhance Mesoscale Meteorological Retrievals

Abstract

Clustering is used to enhance mesoscale meteorological detail in retrievals produced from satellite sounding measurements. By placing sounding fields-of-view (FOVs) into groups of similar measurements, mesoscale details are reinforced, compared to arbitrary grouping of FOVs into a fixed block size. Clustering takes advantage of similarity among the measurements to avoid smearing gradient information. A case study is presented showing the advantage of clustering as applied to the satellite sounding problem.