A method for random uncertainties validation and probing the natural variability with application to TROPOMI on board Sentinel-5P total ozone measurements

Sofieva, Viktoria F.; Lee, Hei Shing; Tamminen, Johanna; Lerot, Christophe; Romahn, Fabian; Loyola, Diego G.

doi:https://doi.org/10.5194/amt-14-2993-2021

Articles | Volume 14, issue 4

https://doi.org/10.5194/amt-14-2993-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue:

Towards Unified Error Reporting (TUNER)

https://doi.org/10.5194/amt-14-2993-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 14, issue 4

Research article

|

22 Apr 2021

Research article |

| 22 Apr 2021

A method for random uncertainties validation and probing the natural variability with application to TROPOMI on board Sentinel-5P total ozone measurements

Viktoria F. Sofieva, Hei Shing Lee, Johanna Tamminen, Christophe Lerot, Fabian Romahn, and Diego G. Loyola

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Final revised paper (published on 22 Apr 2021)
Preprint (discussion started on 28 Oct 2020)

Interactive discussion

Status: closed

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

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- Supplement

RC1: 'Review Comments', Anonymous Referee #1, 18 Dec 2020
- AC1: 'Reply on RC1', Viktoria Sofieva, 02 Feb 2021
RC2: 'Review', Anonymous Referee #2, 04 Jan 2021
- AC2: 'Reply on RC2', Viktoria Sofieva, 02 Feb 2021

Peer-review completion

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

AR by Viktoria Sofieva on behalf of the Authors (04 Feb 2021) Author's response Author's tracked changes Manuscript

ED: Publish as is (09 Mar 2021) by Doug Degenstein

Short summary

Our paper discusses the structure function method, which allows validation of random uncertainties in the data and, at the same time, probing of the small-scale natural variability. We applied this method to the clear-sky total ozone measurements by TROPOMI Sentinel-5P satellite instrument and found that the TROPOMI random error estimation is adequate. The discussed method is a powerful tool, which can be used in various applications.