LS-APC v1.0: a tuning-free method for the linear inverse problem and its application to source-term determination

Tichý, Ondřej; Šmídl, Václav; Hofman, Radek; Stohl, Andreas

doi:https://doi.org/10.5194/gmd-9-4297-2016

Articles | Volume 9, issue 11

https://doi.org/10.5194/gmd-9-4297-2016

© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

https://doi.org/10.5194/gmd-9-4297-2016

© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 9, issue 11

Development and technical paper

|

25 Nov 2016

Development and technical paper |

| 25 Nov 2016

LS-APC v1.0: a tuning-free method for the linear inverse problem and its application to source-term determination

Ondřej Tichý, Václav Šmídl, Radek Hofman, and Andreas Stohl

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Final revised paper (published on 25 Nov 2016)
Supplement to the final revised paper
Preprint (discussion started on 17 Mar 2016)
Supplement to the preprint

Interactive discussion

Status: closed

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

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- Supplement

SC1: 'Executive Editor Comment to "A tuning-free method for the linear inverse problem and its application to source term determination"', Astrid Kerkweg, 30 Mar 2016
- AC1: 'Response to comment by A. Kerkweg', Ondřej Tichý, 09 Sep 2016
RC1: 'Review of "A tuning-free method for the linear inverse problem and its application to source term determination"', Anonymous Referee #1, 29 Jul 2016
- AC2: 'Response to Reviewer #1', Ondřej Tichý, 09 Sep 2016
RC2: 'Referee comment', Anonymous Referee #2, 14 Aug 2016
- AC3: 'Response to Reviewer #2', Ondřej Tichý, 09 Sep 2016
AC4: 'Modifications to the manuscript', Ondřej Tichý, 09 Sep 2016

Peer-review completion

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

AR by Ondřej Tichý on behalf of the Authors (09 Sep 2016)

ED: Referee Nomination & Report Request started (16 Sep 2016) by Adrian Sandu

RR by Anonymous Referee #1 (04 Oct 2016)

ED: Publish subject to technical corrections (01 Nov 2016) by Adrian Sandu

AR by Ondřej Tichý on behalf of the Authors (08 Nov 2016) Author's response Manuscript

Short summary

Estimation of pollutant releases into the atmosphere is an important problem in the environmental sciences. We formulate a probabilistic model, where a full Bayesian estimation allows estimation of all tuning parameters from the measurements. The proposed algorithm is tested and compared with the state-of-the-art method on data from the European Tracer Experiment (ETEX), where advantages of the new method are demonstrated.