Articles | Volume 10, issue 10
Geosci. Model Dev., 10, 3695–3713, 2017
https://doi.org/10.5194/gmd-10-3695-2017
Geosci. Model Dev., 10, 3695–3713, 2017
https://doi.org/10.5194/gmd-10-3695-2017

Methods for assessment of models 10 Oct 2017

Methods for assessment of models | 10 Oct 2017

Atmospheric inverse modeling via sparse reconstruction

Nils Hase et al.

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Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Nils Hase on behalf of the Authors (24 May 2017)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (08 Jun 2017) by Michael Long
RR by Anonymous Referee #1 (19 Jul 2017)
ED: Publish subject to minor revisions (Editor review) (31 Jul 2017) by Michael Long
AR by Nils Hase on behalf of the Authors (24 Aug 2017)  Author's response    Manuscript
ED: Publish as is (06 Sep 2017) by Michael Long
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Short summary
Inverse modeling uses atmospheric measurements to estimate emissions of greenhouse gases, which are key to understand the climate system. However, the measurement information alone is typically insufficient to provide reasonable emission estimates. Additional information is required. This article applies modern mathematical inversion techniques to formulate such additional knowledge. It is a prime example of how such tools can improve the quality of estimates compared to commonly used methods.