Articles | Volume 10, issue 3
Geosci. Model Dev., 10, 1107–1129, 2017
https://doi.org/10.5194/gmd-10-1107-2017
Geosci. Model Dev., 10, 1107–1129, 2017
https://doi.org/10.5194/gmd-10-1107-2017

Development and technical paper 10 Mar 2017

Development and technical paper | 10 Mar 2017

Assimilation of MODIS Dark Target and Deep Blue observations in the dust aerosol component of NMMB-MONARCH version 1.0

Enza Di Tomaso et al.

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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 Enza Di Tomaso on behalf of the Authors (10 Feb 2017)  Author's response    Manuscript
ED: Publish as is (17 Feb 2017) by Axel Lauer
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Short summary
A data assimilation capability has been built for a chemical weather prediction system, with a focus on mineral dust. Before this work, dust was produced uniquely from model estimated emissions. As emissions are recognized as a major factor limiting the accuracy of dust modelling, satellite observations have been used to improve the description of the atmospheric dust load, with a significant impact on dust forecast from assimilating observations particularly relevant for dust applications.