A Lagrangian approach towards extracting signals of urban CO2 emissions from satellite observations of atmospheric column CO2 (XCO2): X-Stochastic Time-Inverted Lagrangian Transport model (“X-STILT v1”)

Wu, Dien; Lin, John C.; Fasoli, Benjamin; Oda, Tomohiro; Ye, Xinxin; Lauvaux, Thomas; Yang, Emily G.; Kort, Eric A.

doi:https://doi.org/10.5194/gmd-11-4843-2018

Articles | Volume 11, issue 12

https://doi.org/10.5194/gmd-11-4843-2018

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

https://doi.org/10.5194/gmd-11-4843-2018

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

Articles | Volume 11, issue 12

Development and technical paper

|

04 Dec 2018

Development and technical paper |

| 04 Dec 2018

A Lagrangian approach towards extracting signals of urban CO₂ emissions from satellite observations of atmospheric column CO₂ (XCO₂): X-Stochastic Time-Inverted Lagrangian Transport model (“X-STILT v1”)

Dien Wu, John C. Lin, Benjamin Fasoli, Tomohiro Oda, Xinxin Ye, Thomas Lauvaux, Emily G. Yang, and Eric A. Kort

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Final revised paper (published on 04 Dec 2018)
Supplement to the final revised paper
Preprint (discussion started on 14 Jun 2018)

Interactive discussion

Status: closed

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

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- Supplement

SC1: 'Code Availability', Lutz Gross, 06 Jul 2018
- AC3: 'Model code version', Dien Wu, 22 Sep 2018
RC1: 'Review of Wu et al.', Anonymous Referee #1, 16 Jul 2018
- AC1: 'Response to Reviewer 1', Dien Wu, 22 Sep 2018
RC2: 'Review comments on "A Lagrangian Approach Towards Extracting Signals of Urban CO2 Emissions from Satellite Observations of Atmospheric Column CO2 (XCO2)"', Anonymous Referee #2, 24 Aug 2018
- AC2: 'Response to Reviewer 2', Dien Wu, 22 Sep 2018

Peer-review completion

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

AR by Dien Wu on behalf of the Authors (22 Sep 2018) Author's response Manuscript

ED: Referee Nomination & Report Request started (25 Sep 2018) by Christoph Knote

RR by Anonymous Referee #2 (16 Oct 2018)

ED: Publish as is (22 Oct 2018) by Christoph Knote

AR by Dien Wu on behalf of the Authors (01 Nov 2018) Author's response Manuscript

Short summary

Urban CO₂ enhancement signals can be derived using satellite column CO₂ concentrations and atmospheric transport models. However, uncertainties due to model configurations, atmospheric transport, and defined background values can potentially impact the derived urban signals. In this paper, we present a modified Lagrangian model framework that extracts urban CO₂ signals from satellite observations and determines potential error impacts.