Data assimilation of volcanic aerosol observations using FALL3D+PDAF

Mingari, Leonardo; Folch, Arnau; Prata, Andrew T.; Pardini, Federica; Macedonio, Giovanni; Costa, Antonio

doi:https://doi.org/10.5194/acp-22-1773-2022

Articles | Volume 22, issue 3

https://doi.org/10.5194/acp-22-1773-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue:

Satellite observations, in situ measurements and model simulations...

https://doi.org/10.5194/acp-22-1773-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 22, issue 3

Research article

|

07 Feb 2022

Research article |

| 07 Feb 2022

Data assimilation of volcanic aerosol observations using FALL3D+PDAF

Leonardo Mingari, Arnau Folch, Andrew T. Prata, Federica Pardini, Giovanni Macedonio, and Antonio Costa

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Final revised paper (published on 07 Feb 2022)
Supplement to the final revised paper
Preprint (discussion started on 21 Sep 2021)
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Interactive discussion

Status: closed

RC1: 'Comment on acp-2021-747', Anonymous Referee #1, 05 Oct 2021

Please see attachment.

Citation: https://doi.org/10.5194/acp-2021-747-RC1
RC2: 'Comment on acp-2021-747', Anonymous Referee #2, 07 Oct 2021

The comment was uploaded in the form of a supplement: https://acp.copernicus.org/preprints/acp-2021-747/acp-2021-747-RC2-supplement.pdf

Citation: https://doi.org/10.5194/acp-2021-747-RC2
AC1: 'Comment on acp-2021-747', Leonardo Mingari, 23 Nov 2021

The comment was uploaded in the form of a supplement: https://acp.copernicus.org/preprints/acp-2021-747/acp-2021-747-AC1-supplement.pdf

Citation: https://doi.org/10.5194/acp-2021-747-AC1

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload

AR by Leonardo Mingari on behalf of the Authors (23 Nov 2021) Author's response Author's tracked changes Manuscript

ED: Publish subject to technical corrections (29 Nov 2021) by Farahnaz Khosrawi

AR by Leonardo Mingari on behalf of the Authors (01 Dec 2021) Author's response Manuscript

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Short summary

We present a new implementation of an ensemble-based data assimilation method to improve forecasting of volcanic aerosols. This system can be efficiently integrated into operational workflows by exploiting high-performance computing resources. We found a dramatic improvement of forecast quality when satellite retrievals are continuously assimilated. Management of volcanic risk and reduction of aviation impacts can strongly benefit from this research.