Introducing hydrometeor orientation into all-sky microwave and submillimeter assimilation

Barlakas, Vasileios; Geer, Alan J.; Eriksson, Patrick

doi:https://doi.org/10.5194/amt-14-3427-2021

Articles | Volume 14, issue 5

https://doi.org/10.5194/amt-14-3427-2021

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

https://doi.org/10.5194/amt-14-3427-2021

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

Articles | Volume 14, issue 5

Research article

| Highlight paper

|

12 May 2021

Research article | Highlight paper |

| 12 May 2021

Introducing hydrometeor orientation into all-sky microwave and submillimeter assimilation

Vasileios Barlakas, Alan J. Geer, and Patrick Eriksson

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Final revised paper (published on 12 May 2021)
Preprint (discussion started on 20 Nov 2020)

Interactive discussion

Status: closed

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

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- Supplement

RC1: 'Manuscript Review', Anonymous Referee #1, 22 Dec 2020
- AC1: 'Reply on RC1', Vasileios Barlakas, 11 Feb 2021
RC2: 'Review for Barlakas et al.', Anonymous Referee #2, 25 Dec 2020
- AC2: 'Reply on RC2', Vasileios Barlakas, 11 Feb 2021

Peer-review completion

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

AR by Vasileios Barlakas on behalf of the Authors (11 Feb 2021) Author's response Manuscript

ED: Referee Nomination & Report Request started (17 Feb 2021) by S. Joseph Munchak

RR by Anonymous Referee #2 (22 Feb 2021)

RR by Anonymous Referee #3 (01 Mar 2021)

Suggestions for revision or reasons for rejection

Review comments on “Introducing hydrometeor orientation into all-sky microwave/sub-millimeter assimilation”, Barlakas et al.

This study presents a simple approach to estimate the hydrometeor orientation in the RTTOV forward operator and tested on ECMWF IFS. This work is important to the community because the misrepresentation of hydrometeor orientation could lead to large discrepancies in simulating brightness temperatures at microwave with radiative transfer models. This manuscript is well written and well designed, but I do have several questions and concerns related to the modeling setup and assumptions.

L82 – The “cloud overlap scheme” has been mentioned several times in the text, and is considered as a fast approximation of sub-grid variability. I understand that the scheme is introduced by Geer et al. (2009), but I think authors need to give a brief description of this method in the text.

L87–88 – What is the difference between “convective snow” and “large scale snow”? Can large scale snow be considered as stratiform snow? The convective snow is assumed to be graupel, how the density of graupel is defined in the simulations?

L100-102 – “In case the retrieval fails, the TELSEM is employed.” What do you mean by "retrieval fails"? Please specify it. A short explanation of Karbou et al. (2010) and the TELSEM is needed.

L107-108 – The search of the “optimal” microphysical setup was based on SSMIS. Could you please specify what do you mean by that? In this study, observations from three sensors are used. Is the optimization suitable for the other two sensors?

L118-119 – It claims that “The PSD introduced by Field et al. (2007) is a good physical representation for snow and further employed to represent graupel.” Could you please provide references? Snow and graupel dominate different cloud regimes (stratiform vs convective), could you please explain why Field et al. (2007) is a good for both cases?

L125 – Could you please give references to which observations are you referring to?

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ED: Publish subject to minor revisions (review by editor) (08 Mar 2021) by S. Joseph Munchak

AR by Vasileios Barlakas on behalf of the Authors (15 Mar 2021) Author's response Manuscript

ED: Publish as is (31 Mar 2021) by S. Joseph Munchak

AR by Vasileios Barlakas on behalf of the Authors (06 Apr 2021)

Short summary

Oriented nonspherical ice particles induce polarization that is ignored when cloud-sensitive satellite observations are used in numerical weather prediction systems. We present a simple approach for approximating particle orientation, requiring minor adaption of software and no additional calculation burden. With this approach, the system realistically simulates the observed polarization patterns, increasing the physical consistency between instruments with different polarizations.