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estimates from microwave (MW) and infrared (IR) sensors. One of the most popular multisatellite products, the TRMM Multisatellite Precipitation Analysis–real time (TMPA-RT) algorithm, combines multiple independent precipitation estimates from the TRMM Microwave Imager (TMI; Kummerow et al. 1998 ; McCollum and Ferraro 2003 ), Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E; Shibata et al. 2003 ; Turk and Miller 2005 ; McCollum and Ferraro 2003 ), Special Sensor Microwave
estimates from microwave (MW) and infrared (IR) sensors. One of the most popular multisatellite products, the TRMM Multisatellite Precipitation Analysis–real time (TMPA-RT) algorithm, combines multiple independent precipitation estimates from the TRMM Microwave Imager (TMI; Kummerow et al. 1998 ; McCollum and Ferraro 2003 ), Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E; Shibata et al. 2003 ; Turk and Miller 2005 ; McCollum and Ferraro 2003 ), Special Sensor Microwave
applied in several studies in the greater area of northern Italy ( Norbiato et al. 2008 , 2009a ). A summary of the modeling framework is provided below, while for a detailed description of the modeling structure, the interested reader is referred to Norbiato et al. (2008) . Snow accumulation and melting is calculated using a distribution function approach based on a combined radiation index degree-day concept ( Cazorzi and Dalla Fontana 1996 ). Potential evapotranspiration is estimated with the
applied in several studies in the greater area of northern Italy ( Norbiato et al. 2008 , 2009a ). A summary of the modeling framework is provided below, while for a detailed description of the modeling structure, the interested reader is referred to Norbiato et al. (2008) . Snow accumulation and melting is calculated using a distribution function approach based on a combined radiation index degree-day concept ( Cazorzi and Dalla Fontana 1996 ). Potential evapotranspiration is estimated with the
. 2009 ) database, which is composed of collocated TRMM Precipitation Radar (PR) 13.8-GHz attenuation-corrected radar reflectivity from the TRMM 2A25 product ( Iguchi et al. 2000 ), Visible and Infrared Scanner (VIRS) 12- μ m infrared (IR) brightness temperature (Tb IR ) from the TRMM 1B01 product, and TRMM Microwave Imager (TMI) 85.5-GHz dual-polarization microwave brightness temperature (Tb 85 ) from the TRMM 1B11 product. The PR has a shorter wavelength than the TMI 85.5-GHz channels so that
. 2009 ) database, which is composed of collocated TRMM Precipitation Radar (PR) 13.8-GHz attenuation-corrected radar reflectivity from the TRMM 2A25 product ( Iguchi et al. 2000 ), Visible and Infrared Scanner (VIRS) 12- μ m infrared (IR) brightness temperature (Tb IR ) from the TRMM 1B01 product, and TRMM Microwave Imager (TMI) 85.5-GHz dual-polarization microwave brightness temperature (Tb 85 ) from the TRMM 1B11 product. The PR has a shorter wavelength than the TMI 85.5-GHz channels so that
infrared (IR) images from low-Earth-orbiting (LEO) or geostationary (GEO) satellites provide regular observations of clouds from which estimates of precipitation may be generated. However, although precipitation originates from clouds, not all clouds produce precipitation. More importantly, the relationship between the cloud-top properties and the precipitation reaching the surface is indirect. Passive microwave (PM) radiometers allow a more direct measure of precipitation to be made since these
infrared (IR) images from low-Earth-orbiting (LEO) or geostationary (GEO) satellites provide regular observations of clouds from which estimates of precipitation may be generated. However, although precipitation originates from clouds, not all clouds produce precipitation. More importantly, the relationship between the cloud-top properties and the precipitation reaching the surface is indirect. Passive microwave (PM) radiometers allow a more direct measure of precipitation to be made since these
