A VERIFICATION STUDY OVER EUROPE OF AMSU-A/MHS AND SSMIS PASSIVE MICROWAVE PRECIPITATION RETRIEVALS

Within the EUMETSAT H-SAF program (Satellite Application Facility on Support to Operational Hydrology and Water Management, http://hsaf.meteoam.it) we have developed two different passive microwave precipitation retrieval algorithms, one based on a physically-based Bayesian approach for conically scanning radiometers (i.e., SSMIS), and the other one based on Neural Network approach for cross-track scanning radiometers (i.e., AMSU-A/MHS). The two algorithms are based on the same physical foundation, i.e., same cloud-radiation model simulations to be used as a priori information in the Bayesian solver and as training dataset in the neural network approach. They also use similar procedures for screening of non-precipitating pixels, identification of frozen background surface, presence of snowfall, and determination of a pixel based quality index of the surface precipitation retrievals. These procedures are calibrated according to the different characteristics (i.e., viewing angle, horizontal resolution, channel frequencies) of the cross-track and conically scanning radiometers used. The two algorithms use dynamical/meteorological/environmental variables as ancillary information to characterize the observed event, and mitigate the ambiguity of the cloud microphysical structures (and rainfall rates at the ground) associated to any given set of measured multichannel brightness temperatures. A verification study of the latest versions of the two algorithms has been carried out within the H-SAF program, where the rainfall estimates are compared against radar observations and rain gauge network measurements for several precipitation events in Europe, characterized by different environmental, meteorological, dynamical conditions, and by different precipitation regimes. We will present the main results of this study, discussing strengths and potentials of the two algorithms in relation to the different characteristics of the observed events. In addition the consistency of the retrievals from close in time overpasses of the cross-track and conically scanning radiometers for the same event will be discussed. Consistency, besides accuracy of the retrievals, is necessary in order to be able to fully exploit all current of future cross-track and conically scanning radiometer overpasses for monitoring precipitation, and to be able to use them in conjunction with IR GEO observations in blending/morphing resolution enhancing techniques for nowcasting and/or hydrological applications.