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

Chandramouli, Krishnamoorthy; Wang, Xuguang; Johnson, Aaron; Otkin, Jason

doi:10.1029/2021ms002711

i

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

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2022
By Chandramouli, Krishnamoorthy ; Wang, Xuguang ; Johnson, Aaron ; ...

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Journal Title:

Journal of Advances in Modeling Earth Systems
Personal Author:

Chandramouli, Krishnamoorthy ; Wang, Xuguang ; Johnson, Aaron ; Otkin, Jason
NOAA Program & Office:

CIMSS (Cooperative Institute for Meteorological Satellite Studies)
Description:

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 radar reflectivity as the anchoring observation for ABI all sky radiance assimilation. The online and offline nonlinear bias correction methods are compared and evaluated for a case of rapidly developing supercells over Oklahoma and Texas. The analysis and background of the online bias correction perform better than the offline approach during the suppression of spurious clouds and the establishment of non-precipitating and precipitating regions when the
Keywords:

Environmental Chemistry General Earth And Planetary Sciences Global And Planetary Change General Earth And Planetary Sciences Global And Planetary Change General Earth And Planetary Sciences Global And Planetary Change
Source:

Journal of Advances in Modeling Earth Systems, 14(3)
DOI:

https://doi.org/10.1029/2021ms002711
ISSN:

1942-2466 ; 1942-2466
Format:

PDF
Publisher:

American Geophysical Union (AGU)
Document Type:

Journal Article
Funding:

Grant no. NA16OAR4320115
License:

https://creativecommons.org/licenses/by/4.0/
Rights Information:

CC BY
Compliance:

Library
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urn:sha256:9e746880b14356a108fcd80d7463f8cd2d409e7829d899eb61e6c610278d2b30
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https://repository.library.noaa.gov/view/noaa/52794/noaa_52794_DS1.pdf
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[PDF - 8.37 MB ]

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