Retrieving Rain rates from space borne microwave sensors using U-nets.
Authors: 
Nicolas Viltard, Pierre Lepetit, Cecile Mallet, Laurent Barthès, Audrey MartiniAuthors Info & Claims
Pages 30 - 36
Abstract
Despite a lot of progress over the last decades, rain retrieval from spaceborne measurement has been a challenge since the first launch of a passive microwave radiometers on one of the NOAA Defense Meteorological satellites in the 70s. Deep-learning and convolutional U-Nets might be able to offer a breakthrough on the topic because they do take into account the topology of both the rain field and the measured brightness temperatures. The present paper offers the very first results on the application of such artificial neural networks on the rain retrieval problem.
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- Retrieving Rain rates from space borne microwave sensors using U-nets.
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Published In
September 2020
138 pages
ISBN:9781450388481
DOI:10.1145/3429309
Copyright © 2020 ACM.
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Published: 11 January 2021
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CI2020
CI2020: 10th International Conference on Climate Informatics
September 22 - 25, 2020
virtual, United Kingdom
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