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

Download

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

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

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

Download

Article (4803 KB)
Full-text XML

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.