The Influence of FY-4A High-Frequency LST Data on Data Assimilation in a Climate Model

The Influence of FY-4A High-Frequency LST Data on Data Assimilation in a Climate Model

Based on the Beijing Climate Center’s land surface model BCC_AVIM2.0, an ensemble Kalman filter (EnKF) algorithm is developed to assimilate the land surface temperature (LST) product of the first satellite of Fengyun-4 series meteorological satellites of China to study the influence of LST data with...

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Bibliographic Details
Main Authors: Suping Nie, Xiaolong Jia, Weitao Deng, Yixiong Lu, Dongyan He, Liang Zhao, Weihua Cao, Xueliang Deng
Format: Article
Language:English
Published: MDPI AG 2022-12-01
Series:Remote Sensing
Subjects:
FY-4A satellite
LST data
high-frequency observations
data assimilation
climate model
Online Access:https://www.mdpi.com/2072-4292/15/1/59

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