Uncertainty of atmospheric microwave absorption model: impact on ground-based radiometer simulations and retrievals

Cimini, Domenico; Rosenkranz, Philip W.; Tretyakov, Mikhail Y.; Koshelev, Maksim A.; Romano, Filomena

doi:https://doi.org/10.5194/acp-18-15231-2018

Articles | Volume 18, issue 20

https://doi.org/10.5194/acp-18-15231-2018

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

https://doi.org/10.5194/acp-18-15231-2018

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

Articles | Volume 18, issue 20

Research article

|

23 Oct 2018

Research article |

| 23 Oct 2018

Uncertainty of atmospheric microwave absorption model: impact on ground-based radiometer simulations and retrievals

Domenico Cimini, Philip W. Rosenkranz, Mikhail Y. Tretyakov, Maksim A. Koshelev, and Filomena Romano

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Final revised paper (published on 23 Oct 2018)
Supplement to the final revised paper
Preprint (discussion started on 11 Jul 2018)
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Interactive discussion

Status: closed

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

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RC1: 'acp-2018-536 comments', Anonymous Referee #1, 07 Aug 2018
- AC1: 'Reply to RC1', Domenico Cimini, 12 Sep 2018
RC2: 'Cite paper on vapor continuum', Anonymous Referee #2, 08 Aug 2018
- AC2: 'Reply to RC2', Domenico Cimini, 12 Sep 2018
SC1: 'Important work quantifying the impact of spectroscopic uncertainties on each other', Emma Turner, 30 Aug 2018
- AC3: 'Reply to SC1', Domenico Cimini, 12 Sep 2018
RC3: 'Review of Cimini et al. [2018]', Vivienne Payne, 03 Sep 2018
- AC4: 'Reply to RC3', Domenico Cimini, 12 Sep 2018

Peer-review completion

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

AR by Domenico Cimini on behalf of the Authors (12 Sep 2018) Author's response Manuscript

ED: Publish as is (28 Sep 2018) by Jui-Yuan Christine Chiu

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Short summary

The paper presents a general approach to quantify the uncertainty related to atmospheric absorption models. These models describe how the atmosphere interacts with radiation, and they have general implications for atmospheric sciences. The presented approach contributes to a better understanding of the total uncertainty affecting atmospheric radiative properties, thus reducing the chances of systematic errors when observations are exploited for weather forecast or climate trend derivations.