Advances on Rain Rate Retrieval from Satellite Platforms using Artificial Neural Networks

In the last two decades, great advances have been related with the development of rain rate retrieval algorithms using artificial neural networks, in order to exploit satellite data capabilities. The enhancement of computing processing capacity available from modern computers has impulsed a long number of researches aimed to generate more accurate and faster algorithms. This work deals with how the implementation of new trends in artificial neural networks and the spectral resolution improvement of spaceborne sensors have influenced in the design of retrieval algorithms to estimate rain rate from satellites using artificial neural networks. Recent results have shown an important increasing in accuracy and technical feasibility of implementation, however, the feasibility to use artificial neural networks to estimate rain rate in real time, using remote sensing techniques, is a research issue yet.