Cloud Classification by Machine Learning for Geostationary Radiation Imager-Reference-Cited by-同舟云学术

Cloud Classification by Machine Learning for Geostationary Radiation Imager

Published:2024 Issue: Volume:62 Page:1-14
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Guo Bin¹^ORCID,Zhang Feng¹^ORCID,Li Wenwen¹^ORCID,Zhao Zhijun²

Affiliation:

1. Department of Atmospheric and Oceanic Sciences, CMA-FDU Joint Laboratory of Marine Meteorology, Institutes of Atmospheric Sciences, Fudan University, Shanghai, China

2. Key Laboratory for Information Science of Electromagnetic Waves, Ministry of Education, Fudan University, Shanghai, China

Funder

National Natural Science Foundation of China

China Postdoctoral Science Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/36/10354519/10400516.pdf?arnumber=10400516

Reference52 articles.

1. Precipitation, Convective Clouds, and Their Connections With Tropical Cyclone Intensity and Intensity Change

2. Aerosol-cloud-precipitation effects over Germany as simulated by a convective-scale numerical weather prediction model

3. Consequences of poor representation of Arctic sea-ice albedo and cloud-radiation interactions in the CMIP5 model ensemble

4. The role of cloud phase in Earth's radiation budget

5. A Near-Global Climatology of Single-Layer and Overlapped Clouds and Their Optical Properties Retrieved from Terra/MODIS Data Using a New Algorithm

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