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.

中文翻译：

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基于极地轨道和地球静止卫星数据的云量和降水监测

摘要

考虑使用来自卫星多通道扫描辐射计的可见光和红外数据对云层和降水参数进行业务自动分类的现代方法和技术。本文分析了基于机器学习和人工神经网络的阈值分类技术和算法，以及通过与地面气象观测和独立卫星估计进行比较获得的卫星产品验证结果。阐述了云三叶和降水监测进一步发展和应用的问题和展望。