CDRD and PNPR passive microwave precipitation retrieval algorithms: extension to the MSG full disk area

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 is the Cloud Dynamics Radiation Database algorithm (CDRD), based on a physically-based Bayesian approach for conically scanning radiometers (i.e., DMSP SSMIS); the other one is the Passive microwave Neural network Precipitation Retrieval (PNPR) algorithm for cross-track scanning radiometers (i.e., NOAA and MetOp-A/B AMSU-A/MHS). The algorithms originally created for Europe and the Mediterranean basin have been recently extended to Africa and Southern Atlantic for application to the MSG full disk area. 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 nonprecipitating pixels, identification of frozen background surface, detection of snowfall, and determination of a pixel based quality index of the surface precipitation retrievals. Operational precipitation products based on CDRD and PNPR covering the MSG full disk area will be soon made available within H-SAF. In this paper the methodology used to create a cloud-radiation database representative of the area of interest is described, as well as the changes made in the precipitation retrieval algorithms to account for the extended database. The results of a verification study over the African continent using as ground truth the TRMM Precipitation Radar will be shown. Future development of the algorithms for the full exploitation of the NASA/JAXA Global Precipitation Measuring mission (GPM) is also presented.