Articles | Volume 12, issue 7
https://doi.org/10.5194/amt-12-3629-2019
https://doi.org/10.5194/amt-12-3629-2019
Research article
 | 
04 Jul 2019
Research article |  | 04 Jul 2019

Correlated observation error models for assimilating all-sky infrared radiances

Alan J. Geer

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Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Alan Geer on behalf of the Authors (31 May 2019)  Author's response    Manuscript
ED: Publish subject to technical corrections (12 Jun 2019) by Isaac Moradi
AR by Alan Geer on behalf of the Authors (17 Jun 2019)  Author's response    Manuscript
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Short summary
Using more satellite data in cloudy areas helps improve weather forecasts, but all-sky assimilation is still tricky, particularly for infrared data. To allow the use of hyperspectral infrared sounder radiances in all-sky conditions, an error model is developed that, in the presence of cloud, broadens the correlations between channels and increases error variances. After fixing problems of gravity wave and bias amplification, the results of all-sky assimilation trials were promising.