The Advanced Infra-Red WAter Vapour Estimator (AIRWAVE) version 2: algorithm evolution, dataset description and performance improvements

Castelli, Elisa; Papandrea, Enzo; Di Roma, Alessio; Dinelli, Bianca Maria; Casadio, Stefano; Bojkov, Bojan

doi:https://doi.org/10.5194/amt-12-371-2019

Articles | Volume 12, issue 1

https://doi.org/10.5194/amt-12-371-2019

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

https://doi.org/10.5194/amt-12-371-2019

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

Articles | Volume 12, issue 1

Research article

|

18 Jan 2019

Research article |

| 18 Jan 2019

The Advanced Infra-Red WAter Vapour Estimator (AIRWAVE) version 2: algorithm evolution, dataset description and performance improvements

Elisa Castelli, Enzo Papandrea, Alessio Di Roma, Bianca Maria Dinelli, Stefano Casadio, and Bojan Bojkov

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Final revised paper (published on 18 Jan 2019)
Preprint (discussion started on 20 Jun 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 "The Advanced Infra-RedWAter Vapour Estimator (AIRWAVE) version 2: algorithm evolution, dataset description and performance improvements"', Anonymous Referee #1, 27 Jul 2018
- AC1: 'Replies to Referee #1', Elisa Castelli, 10 Oct 2018
RC2: 'Interactive comment on “The Advanced Infra-Red Water Vapour Estimator (AIRWAVE) version 2: algorithm evolution, dataset description and performance improvements” by Castelli et al., 2018', Anonymous Referee #2, 31 Jul 2018
- AC2: 'Replies to Referee #2', Elisa Castelli, 10 Oct 2018

Peer-review completion

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

AR by Elisa Castelli on behalf of the Authors (11 Oct 2018) Author's response Manuscript

ED: Referee Nomination & Report Request started (12 Oct 2018) by Helen Worden

RR by Anonymous Referee #2 (01 Nov 2018)

Suggestions for revision or reasons for rejection

Dear Authors,

I would like to thank you very much for addressing all my comments and questions in my previous review. Your first version of the manuscript already included a lot of works. But the overall high amount of precise answers and solid clarifications satisfy my raised comments. In particular, I very much appreciate the efforts of having added the Figure 1, merged the Panels of Figure 2, added the discussion of Airwaves 1 vs. 2 + Table 2, the clarification of the equations in Sect. 2.2, and all the quantitative numbers that allow to better understand the quality and sensitivity of your retrievals (overall and per error source).

I recommend the publication in AMT. I have a few remaining minor requests:
- Perhaps it should be directly obvious, but I don't directly see the transition from Eq 12 to Eq 13. Could you please explicit it? Furthermore, what is the meaning of "pseudo-column"? A column integrated along the average light path (by opposition of vertical atmospheric layers?
- I somehow feel your abstract (and conclusion) underestimates a little bit the impact of your study. I don't think AIRWAVES "only" improves thanks to a higher performance. The improvements are also: a better algorithm implementation by explicitly taking into account the geometry and latitude dependence for each pixel retrieval (a post-correction may create some strange spatial artefacts, hard to quantify in terms of performances), and a better uncertainty estimation of your overall retrievals with a large sensitivity analyses to various parameters. This last one is, for someone like me, important as it may better recommend me to use this dataset (and its overall error bar) for future applications. You may want to stress that. You also (now) made a direct comparison with previous Airwaves v1.
- I found your Figure 0 in your reply informative. Why not adding it in your new manuscript?

Congratulations again for your work!

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ED: Publish subject to minor revisions (review by editor) (01 Nov 2018) by Helen Worden

AR by Elisa Castelli on behalf of the Authors (16 Nov 2018) Author's response Manuscript

ED: Publish as is (25 Nov 2018) by Helen Worden

AR by Elisa Castelli on behalf of the Authors (03 Dec 2018)

Short summary

The total column water vapour (TCWV) is a key atmospheric variable. The AIRWAVE (Advanced Infra-Red WAter Vapour Estimator) v1 algorithm was developed to retrieve TCWV from satellite measurements. Comparisons with independent TCWV show good agreement with an overall bias of 0.72 kg m⁻² due to the polar and coastal regions. Here, we describe the AIRWAVEv2 dataset, which shows significant improvements with a global bias of 0.02 kg m⁻². This dataset was used to produce a climatology from 1991 to 2012.