Information content analysis: the potential for methane isotopologue retrieval from GOSAT-2

Malina, Edward; Yoshida, Yukio; Matsunaga, Tsuneo; Muller, Jan-Peter

doi:https://doi.org/10.5194/amt-11-1159-2018

Articles | Volume 11, issue 2

https://doi.org/10.5194/amt-11-1159-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/amt-11-1159-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 11, issue 2

Research article

|

28 Feb 2018

Research article |

| 28 Feb 2018

Information content analysis: the potential for methane isotopologue retrieval from GOSAT-2

Edward Malina, Yukio Yoshida, Tsuneo Matsunaga, and Jan-Peter Muller

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Final revised paper (published on 28 Feb 2018)
Preprint (discussion started on 15 Aug 2017)

Interactive discussion

Status: closed

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

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- Supplement

RC1: 'Referee Comment', Haili Hu, 07 Sep 2017
- AC1: 'Response to Review comment 1', Edward Malina, 20 Dec 2017
RC2: 'referee report', Anonymous Referee #2, 10 Nov 2017
- AC2: 'Response to Review comment 2', Edward Malina, 20 Dec 2017

Peer-review completion

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

AR by Edward Malina on behalf of the Authors (20 Dec 2017) Author's response Manuscript

ED: Publish subject to minor revisions (review by editor) (28 Dec 2017) by Piet Stammes

AR by Edward Malina on behalf of the Authors (29 Dec 2017) Author's response Manuscript

ED: Publish as is (22 Jan 2018) by Piet Stammes

AR by Edward Malina on behalf of the Authors (25 Jan 2018)

Short summary

We present an assessment of the predicted information content and retrieval errors for ¹³CH₄ retrieval from the planned GOSAT-2 satellite, assuming a wide range of land surface conditions. Retrieval of this quantity may allow for estimation of methane source types (e.g. biological or non-biological) based on the δ¹³C metric. We conclude that GOSAT-2 can be used for this purpose (to an accuracy of 10 ‰) assuming sufficient spatial (regional) and temporal (at least monthly) averaging.