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

Di Tomaso, Enza; Schutgens, Nick A. J.; Jorba, Oriol; Pérez García-Pando, Carlos

doi:https://doi.org/10.5194/gmd-10-1107-2017

Articles | Volume 10, issue 3

https://doi.org/10.5194/gmd-10-1107-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

https://doi.org/10.5194/gmd-10-1107-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 10, issue 3

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, Nick A. J. Schutgens, Oriol Jorba, and Carlos Pérez García-Pando

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Final revised paper (published on 10 Mar 2017)
Preprint (discussion started on 21 Sep 2016)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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- Supplement

RC1: 'Review for Assimilation of MODIS Dark Target and Deep Blue Observations in the dust aerosol component of NMMB/BSC-CTM version 1.0', Anonymous Referee #1, 21 Oct 2016
- AC1: 'Response to the Anonymous Reviewer #1', Enza Di Tomaso, 10 Feb 2017
RC2: 'Review of Assimilation of MODIS Dark Target and Deep Blue Observations in the dust aerosol component of NMMB/BSC-CTM version 1.0 by Tomaso et al.', Anonymous Referee #2, 06 Nov 2016
- AC2: 'Response to the Anonymous Reviewer #2', Enza Di Tomaso, 10 Feb 2017

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

AR by Enza Di Tomaso on behalf of the Authors (23 Feb 2017)

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.