AbstractIn this work a methodology for inferring water cloud macro and microphysical properties from nighttime MODIS imagery is developed. This method is based on the inversion of a theoretical radiative transfer model that simulates the radiances detected in each of the sensor infrared bands. To accomplish this inversion, an operational technique based on Artificial Neural Networks (ANNs) is proposed, whose main characteristic is the ability to retrieve cloud properties much faster than conventional methods. Furthermore, a detailed study of input data is performed to avoid different sources of errors that appear in several MODIS infrared channels. Finally, results of applying the proposed method are compared with in-situ measurements carried out during the DYCOMS-II field experiment.
Nighttime cloud properties retrieval using MODIS and artificial neural networks
Advances in Space Research ; 43 , 5 ; 852-858
2008-06-18
7 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Nighttime cloud properties retrieval using MODIS and artificial neural networks
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