Nonlinear Bias Correction of the FY-4A AGRI Infrared Radiance Data Based on the Random Forest

Nonlinear Bias Correction of the FY-4A AGRI Infrared Radiance Data Based on the Random Forest

Bias correction is a key prerequisite for radiance data assimilation. Directly assimilating the radiance observations generally involves large systematic biases affecting the numerical prediction accuracy. In this study, a nonlinear bias correction scheme with Random Forest (RF) technology is firstl...

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Bibliographic Details
Main Authors: Xuewei Zhang, Dongmei Xu, Xin Li, Feifei Shen
Format: Article
Language:English
Published: MDPI AG 2023-03-01
Series:Remote Sensing
Subjects:
FY-4A AGRI
bias correction
data assimilation
nonlinear method
Online Access:https://www.mdpi.com/2072-4292/15/7/1809

Internet

https://www.mdpi.com/2072-4292/15/7/1809

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