Fengyun-3D/MERSI-II Cloud Thermodynamic Phase Determination Using a Machine-Learning Approach

Fengyun-3D/MERSI-II Cloud Thermodynamic Phase Determination Using a Machine-Learning Approach

Global cloud thermodynamic phase (CP) is normally derived from polar-orbiting satellite imaging data with high spatial resolution. However, constraining conditions and empirical thresholds used in the MODIS (Moderate Resolution Imaging Spectroradiometer) CP algorithm are closely associated with spec...

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Bibliographic Details
Main Authors: Dexin Zhao, Lin Zhu, Hongfu Sun, Jun Li, Weishi Wang
Format: Article
Language:English
Published: MDPI AG 2021-06-01
Series:Remote Sensing
Subjects:
FY-3D/MERSI-II
MODIS
cloud thermodynamic phase
machine learning
Online Access:https://www.mdpi.com/2072-4292/13/12/2251

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