Abstract
Modern methods and technologies for operational automatic classification of cloud cover and precipitation parameters using visible and infrared data from satellite multi-channel scanning radiometers are considered. The paper analyzes threshold classification techniques and algorithms based on machine learning and artificial neural networks and the results of validation of satellite products obtained from the comparison with ground-based meteorological observations and independent satellite estimates. Problems and prospects of further development and application of cloud clover and precipitation monitoring are formulated.
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