PHYSICALLY-BASED SATELLITE RETRIEVAL OF PRECIPITATION USING A 3D PASSIVE MICROWAVE RADIATIVE-TRANSFER MODEL

A precipitation retrieval algorithm based on the application of a 3D r adiative transfer model to a hybrid physical-stochastic 3D cloud model is described. The cloud model uses a statistical rainfall clustering scheme to generate 3D cloud structures while ensuring that the stochas tically generated quantities remain physically plausible. The radiativ e transfer model is applied to the cloud structures to simulate satell ite remotely sensed upwelling microwave brightness temperatures T-B's. Regression-derived relationships between model T-B's and surface rain fall rates for Special Sensor Microwave/Imager (SSM/I) frequencies are used as the foundation of the retrieval algorithm, which is valid ove r oceans. A case study calibrates the retrieval algorithm to the Europ ean Centre for Medium-Range Weather Forecasts (ECMWF) numerical weathe r prediction model and applies the algorithm to SSM/I data obtained du ring the Tropical Ocean Global Atmosphere Coupled Ocean-Atmosphere Res ponse Experiment. Comparisons between the satellite-derived precipitat ion amounts and radar-derived amounts, at a spatial resolution of appr oximately 55 km, give correlations of about 0.7 for instantaneous rain rates and 0.634 for monthly accumulations. Although the satellite-der ived totals are reasonably well correlated with the radar totals, they also appear to contain a relatively large positive bias, which may in part be due to the ECMWF tuning. However, optical rain gauge measurem ents are larger than both the satellite- and radar-derived amounts, ca sting uncertainty into the level of bias of the satellite algorithm. F inally, an important aspect of 3D radiative transfer in precipitating systems is illustrated by demonstrating that satellite viewing angle e ffects realized in the simulation framework also appear to be present in empirical relations between SSM/ITB's and radar-derived surface rai nfall rates.