Improvement of Rain/No-Rain Classification Methods for Microwave Radiometer Observations over the Ocean Using a 37GHz Emission Signature(2. Global Satellite Mapping of Precipitation (GSMaP) Project,<Special Issue>Precipitation Measurements from Space)

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The rain/no-rain classification (RNC) for the Tropical Rainfall Measuring Mission (TRMM) Imager (TMI) fails in detecting shallow rain observed by the TRMM Precipitation Radar (PR). In this study, the RNC method is revised to use the 37-GHz emission more efficiently to identify shallow rain and is applied to the TMI observation. The results are then evaluated against the RNC made by the PR observation, considered as the "truth." The revised RNC method (GSMaP2) is compared with the original RNC method (GSMaP1) and the Goddard profiling algorithm (GPROF). GSMaP2 performs well for shallow rain behind cold fronts in the extratropics, where GSMaP1 and GPROF fail, using the 37-GHz emission signature. Through a whole year, a global comparison shows that GSMaP2 performs better than GSMaP1 and GPROF over mid-latitudes. However, GSMaP2 fails in detecting shallow isolated rain over sub-tropical oceans owing to a globally constant value for the vertically integrated cloud liquid water path (LWP) assumed in the forward calculation. Therefore, we parameterize the LWP as a function of storm height from the PR observation over the region where shallow isolated rain is predominant. GSMaP3, in which the parameterization of the LWP is applied to GSMaP2, improves detection of shallow isolated rain over sub-tropical oceans.
2009-03-31