A scanning strategy optimized for signal-to-noise ratio for the Geostationary Carbon Cycle Observatory (GeoCarb) instrument

Nivitanont, Jeffrey; Crowell, Sean M. R.; Moore III, Berrien

doi:https://doi.org/10.5194/amt-12-3317-2019

Articles | Volume 12, issue 6

https://doi.org/10.5194/amt-12-3317-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/amt-12-3317-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 12, issue 6

Research article

|

21 Jun 2019

Research article |

| 21 Jun 2019

A scanning strategy optimized for signal-to-noise ratio for the Geostationary Carbon Cycle Observatory (GeoCarb) instrument

Jeffrey Nivitanont, Sean M. R. Crowell, and Berrien Moore III

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Final revised paper (published on 21 Jun 2019)
Preprint (discussion started on 09 Nov 2018)

Interactive discussion

Status: closed

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

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- Supplement

RC1: 'Review of amt-2018-359 "An SNR-Optimized Scanning Strategy for Geostationary Carbon Cycle Observatory (GeoCarb) Instrument"', Anonymous Referee #1, 17 Dec 2018
- AC1: 'Response to Referee Comments 1', Jeffrey Nivitanont, 26 Apr 2019
RC2: 'Reviewer's comments', Anonymous Referee #2, 13 Feb 2019
- AC2: 'Response to Referee Comments 2', Jeffrey Nivitanont, 27 Apr 2019

Peer-review completion

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

AR by Jeffrey Nivitanont on behalf of the Authors (27 Apr 2019) Author's response Manuscript

ED: Publish subject to technical corrections (15 May 2019) by Alyn Lambert

AR by Jeffrey Nivitanont on behalf of the Authors (17 May 2019) Author's response Manuscript

Short summary

A scanning strategy is proposed for the upcoming GeoCarb instrument that minimizes predicted retrieval errors of CO₂ by optimizing signal-to-noise ratio with respect to air mass factor and solar zenith angle. The strategy is generated using a modified greedy algorithm that optimizes over these stationary processes while also considering operational constraints. This method increases the number of soundings with predicted CO₂ retrieval error less than 2 ppm by 18–41 %.