A sparse reconstruction method for the estimation of multi-resolution emission fields via atmospheric inversion

Ray, J.; Lee, J.; Yadav, V.; Lefantzi, S.; Michalak, A. M.; van Bloemen Waanders, B.

doi:https://doi.org/10.5194/gmd-8-1259-2015

Articles | Volume 8, issue 4

https://doi.org/10.5194/gmd-8-1259-2015

© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

https://doi.org/10.5194/gmd-8-1259-2015

© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 8, issue 4

Development and technical paper

|

29 Apr 2015

Development and technical paper |

| 29 Apr 2015

A sparse reconstruction method for the estimation of multi-resolution emission fields via atmospheric inversion

J. Ray, J. Lee, V. Yadav, S. Lefantzi, A. M. Michalak, and B. van Bloemen Waanders

Download

Final revised paper (published on 29 Apr 2015)
Preprint (discussion started on 20 Aug 2014)

Interactive discussion

Status: closed

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

- Printer-friendly version

- Supplement

RC C2000: 'Review of Ray et al. 2014', Anonymous Referee #1, 16 Oct 2014
- AC C3046: 'Response to Reviewer No. 1', Jaideep Ray, 22 Jan 2015
RC C2133: 'Comments', Anonymous Referee #2, 25 Oct 2014
- AC C3047: 'Response to Reviewer No. 2', Jaideep Ray, 22 Jan 2015
RC C2353: 'Referee Comment', Anonymous Referee #3, 21 Nov 2014
- AC C3048: 'Response to Reviewer No. 3', Jaideep Ray, 22 Jan 2015

Peer-review completion

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

AR by Jaideep Ray on behalf of the Authors (07 Mar 2015) Author's response Manuscript

ED: Publish subject to technical corrections (07 Apr 2015) by Andrea Stenke

AR by Jaideep Ray on behalf of the Authors (07 Apr 2015) Manuscript

Short summary

The paper presents a statistical method (shrinkage) that can be used to estimate rough emission fields, e.g., fossil fuel CO2 emissions, from measurements of concentrations. This method is demonstrated in a test case where the emissions are modeled using wavelets. We find that the method can eliminate unnecessary complexity from the wavelet model, ensures non-negativity of the emissions, is computationally efficient and is, by construction, insensitive to prior guesses of the total emission.