Rain rate estimation from a synergetic use of SSM/I, AVHRR and meso-scale numerical model data

Summary In this paper a retrieval technique for estimating rainfall rates is introduced. The novel feature of this technique is the combination of two satellite radiometers — the Special Sensor Microwave/Imager (SSM/I) and the Advanced Very High-Resolution Radiometer (AVHRR) — with mesoscale weather prediction model data. This offers an adjustment of the model atmospheres to reality which is necessary for calculating brightness temperatures that can be compared with microwave satellite measurements.In sensitivity studies it was found that the estimation of precipitation is determined to a high degree by the particle size distribution of rain and snow, especially by the size distribution of solid hydrometeors. These studies also reveal the influence of the knowledge of the correct cloud coverage inside a SSM/I pixel and the importance of using a realistic temperature profile instead of using standard atmospheres.The retrieval technique is based on radiative transfer calculations using the model of Kummerow et al. (1989). The algorithm consists of two parts: First Guess (FG) brightness temperatures for the SSM/I frequencies are generated as a function of the cloud top height and the cloud coverage, derived from AVHRR data and predictions from a meso-scale model. The rainfall rate of different types of clouds containing raindrops, ice particles and coexisting ice and water hydrometeors is then calculated as a function of the cloud top height. As an example, a strong convective rain event over the western part of Europe and over the Alps is taken to evaluate the performance of this technique. Good agreement with radar data from the German Weather Service was achieved. Compared to statistical rainfall algorithms, the current algorithm shows a better performance of detecting rainfall areas.With 12 Figures