Online Nonlinear Bias Correction in Ensemble Kalman Filter to Assimilate GOES‐R All‐Sky Radiances for the Analysis and Prediction of Rapidly Developing Supercells

Online Nonlinear Bias Correction in Ensemble Kalman Filter to Assimilate GOES‐R All‐Sky Radiances for the Analysis and Prediction of Rapidly Developing Supercells

Abstract The present study introduces the online non‐linear bias correction for the assimilation of all‐sky GOES‐16 Advanced Baseline Imager (ABI) channel 9 (6.9 μm) radiances in a rapidly cycled EnKF for convective scale data assimilation (DA). This study is the first to explore the use of the rada...

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Bibliographic Details
Main Authors: Krishnamoorthy Chandramouli, Xuguang Wang, Aaron Johnson, Jason Otkin
Format: Article
Language:English
Published: American Geophysical Union (AGU) 2022-03-01
Series:Journal of Advances in Modeling Earth Systems
Subjects:
bias correction
all‐sky radiances
GOES‐R
EnKF
RADAR
Online Access:https://doi.org/10.1029/2021MS002711

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