496 
5 - CONCLUSIONS 
Microwave signature of precipitation as given by a space-borne multi-frequency radiometer has been shown 
and discussed. Pre-processing of brightness temperature data are needed when applying retrieval algorithms 
to satellite brightness temperature images. In particular, deconvolution of the low-frequency images and 
preliminary identification of rainfall areas can improve the precipitation retrieval accuracy. The use of a 
simulated cloud-radiation dataset leads to a proper modeling framework for statistical retrieval of 
precipitation. The maximum likelihood estimation algorithm is able to assimilate the information deduced 
from the simulated dataset in an effective and efficient way. The potentiality of the proposed retrieval 
algorithm has been shown and a preliminary comparison with rain-gauge measurements has given 
encouraging results. 
Acknowledgments: The authors are grateful to dr. A. Mugnai for his collaboration and for providing us SSM/I 
and rain-gauge data; this work has been partially supported by Italian Space Agency (ASI), by Ministry of 
University and Research (MURST), and by European Economic Community (EEC). 
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