Satellite retrieval of aerosol combined with assimilated forecast

Yoshida, Mayumi; Yumimoto, Keiya; Nagao, Takashi M.; Tanaka, Taichu Y.; Kikuchi, Maki; Murakami, Hiroshi

doi:https://doi.org/10.5194/acp-21-1797-2021

Articles | Volume 21, issue 3

https://doi.org/10.5194/acp-21-1797-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/acp-21-1797-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 21, issue 3

Research article

|

10 Feb 2021

Research article |

| 10 Feb 2021

Satellite retrieval of aerosol combined with assimilated forecast

Mayumi Yoshida, Keiya Yumimoto, Takashi M. Nagao, Taichu Y. Tanaka, Maki Kikuchi, and Hiroshi Murakami

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Final revised paper (published on 10 Feb 2021)
Preprint (discussion started on 27 May 2020)

Interactive discussion

Status: closed

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

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- Supplement

RC1: 'Reviewer 1', Alexander Kokhanovsky, 02 Jun 2020
RC2: 'Review of “Retrieval of Aerosol Combined with Assimilated Forecast”', Anonymous Referee #3, 01 Sep 2020
AC1: 'Response to reviewers', Mayumi Yoshida, 15 Nov 2020

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

AR by Mayumi Yoshida on behalf of the Authors (16 Nov 2020) Author's response Manuscript

ED: Referee Nomination & Report Request started (23 Nov 2020) by Stelios Kazadzis

RR by Anonymous Referee #3 (03 Dec 2020)

ED: Publish as is (04 Dec 2020) by Stelios Kazadzis

Short summary

We developed a new aerosol satellite retrieval algorithm combining a numerical aerosol forecast. This is the first study that utilizes the assimilated model forecast of aerosol as an a priori estimate of the retrieval. Aerosol retrievals were improved by effectively incorporating both model and satellite information. By using the assimilated forecast as an a priori estimate, information from previous observations can be propagated to future retrievals, thus leading to better retrieval accuracy.