The microphysics of clouds over the Antarctic Peninsula – Part 2: modelling aspects within Polar WRF

Listowski, Constantino; Lachlan-Cope, Tom

doi:https://doi.org/10.5194/acp-17-10195-2017

Articles | Volume 17, issue 17

https://doi.org/10.5194/acp-17-10195-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

https://doi.org/10.5194/acp-17-10195-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 17, issue 17

Research article

|

31 Aug 2017

Research article |

| 31 Aug 2017

The microphysics of clouds over the Antarctic Peninsula – Part 2: modelling aspects within Polar WRF

Constantino Listowski and Tom Lachlan-Cope

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Final revised paper (published on 31 Aug 2017)
Preprint (discussion started on 19 Jan 2017)

Interactive discussion

Status: closed

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

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- Supplement

RC1: 'Comment on acp-2016-1135', Anonymous Referee #1, 21 Feb 2017
RC2: 'Review', Anonymous Referee #2, 24 Feb 2017
AC1: 'response to reviewers', Constantino Listowski, 20 Jun 2017

Peer-review completion

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

AR by Constantino Listowski on behalf of the Authors (20 Jun 2017) Author's response Manuscript

ED: Referee Nomination & Report Request started (03 Jul 2017) by Martina Krämer

RR by Anonymous Referee #2 (05 Jul 2017)

RR by Anonymous Referee #1 (08 Jul 2017)

ED: Publish as is (12 Jul 2017) by Martina Krämer

AR by Constantino Listowski on behalf of the Authors (14 Jul 2017)

Short summary

Modelling Antarctic tropospheric clouds remains challenging because of the lack of observations in this remote place. We use aircraft in situ observations to assess the performances of simulations over the Antarctic Peninsula within the Polar Weather Research and Forecasting model. The cloud scheme used by the operational forecast model AMPS performs the least well. Ice microphysics is key for correctly modelling the supercooled liquid phase and hence for lowering the surface radiative biases.