SATELLITE REMOTE SENSING FOR CLOUDS AND PRECIPITATIONS

Satellite remote sensing is very useful for the monitoring and characterization of cloudy areas and for the monitoring of precipitation events. In particular, satellite monitoring of extreme precipitation events is particularly attractive for real-time operational purposes. The detection and classification of cloudy areas is important for monitoring convective and stratiform clouds to which heavy and moderate rain are respectively associated. In this paper, two techniques - developed at the National Research Council of Italy Institute of Methodologies for Environmental Analysis (CNR-IMAA) - are reviewed. These were developed for the recognition of convective clouds as well as the monitoring of extreme precipitation events: the Precipitation Evolving Technique (PET) and the Rain Class Evaluation from Infrared and Visible observations (RainCEIV). PET uses Infrared (IR) channels from the Meteosat Second Generation-Spinning Enhanced Visible and Infrared Imager (MSG-SEVIRI) coupled with Rain Rate (RR) obtained from Passive-Microwave-based algorithm to provide near real time RR maps. RainCEIV uses Visible (VIS) and IR observations from MSG-SEVIRI to determine near real-time cloud classification and rain class evaluation. RainCEIV classifies SEVIRI pixels as non-rainy, light-to-moderate rain, or heavy-to-very heavy rain. In addition, two cloud classification schemes developed at CNR-IMAA, namely MACSP (Cloud Mask Coupling of statistical and Physical Methods) and C_MACSP (Classification Cloud Mask Coupling of Statistical and Physical Methods), are also described.