Technical note: Applicability of physics-based and machine-learning-based algorithms of a geostationary satellite in retrieving the diurnal cycle of cloud base height

Two groups of retrieval algorithms, physics based and machine learning (ML) based, each consisting of two independent approaches, have been developed to retrieve cloud base height (CBH) and its diurnal cycle from Himawari-8 geostationary satellite observations. Validations have been conducted using...

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Bibliographic Details
Published in:	Atmospheric chemistry and physics Vol. 24; no. 24; pp. 14239 - 14256
Main Authors:	Wang, Mengyuan, Min, Min, Li, Jun, Lin, Han, Liang, Yongen, Chen, Binlong, Yao, Zhigang, Xu, Na, Zhang, Miao
Format:	Journal Article
Language:	English
Published:	Katlenburg-Lindau Copernicus GmbH 20.12.2024 Copernicus Publications
Subjects:	Algorithms Artificial satellites Aviation CALIPSO (Pathfinder satellite) Climate change Clouds Comparative analysis Correlation coefficient Correlation coefficients Datasets Diurnal cycle Diurnal variations Geostationary satellites Ground-based observation Height Learning algorithms Lidar Machine learning Meteorological satellites Physics Radar Remote sensing Satellite observation Satellites Synchronous satellites Training Weather forecasting
ISSN:	1680-7324, 1680-7316, 1680-7324
Online Access:	Get full text
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