Effects of coupling a stochastic convective parameterization with the Zhang–McFarlane scheme on precipitation simulation in the DOE E3SMv1.0 atmosphere model

Wang, Yong; Zhang, Guang J.; Xie, Shaocheng; Lin, Wuyin; Craig, George C.; Tang, Qi; Ma, Hsi-Yen

doi:https://doi.org/10.5194/gmd-14-1575-2021

Articles | Volume 14, issue 3

https://doi.org/10.5194/gmd-14-1575-2021

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

https://doi.org/10.5194/gmd-14-1575-2021

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

Articles | Volume 14, issue 3

Development and technical paper

|

18 Mar 2021

Development and technical paper |

| 18 Mar 2021

Effects of coupling a stochastic convective parameterization with the Zhang–McFarlane scheme on precipitation simulation in the DOE E3SMv1.0 atmosphere model

Yong Wang, Guang J. Zhang, Shaocheng Xie, Wuyin Lin, George C. Craig, Qi Tang, and Hsi-Yen Ma

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Final revised paper (published on 18 Mar 2021)
Preprint (discussion started on 29 Sep 2020)

Interactive discussion

Status: closed

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

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- Supplement

RC1: 'Anonymous review', Anonymous Referee #1, 30 Oct 2020
- AC2: 'Reply on RC1', Yong Wang, 28 Jan 2021
- AC1: 'Reply on RC2', Yong Wang, 28 Jan 2021
RC2: 'Review of ''Effects of Coupling a Stochastic Convective Parameterization with Zhang-McFarlane Scheme on Precipitation Simulation in the DOE E3SMv1 Atmosphere Model" by Wang et al.', Anonymous Referee #2, 06 Nov 2020
- AC1: 'Reply on RC2', Yong Wang, 28 Jan 2021
- AC2: 'Reply on RC1', Yong Wang, 28 Jan 2021

Peer-review completion

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

AR by Yong Wang on behalf of the Authors (05 Feb 2021) Author's response Author's tracked changes Manuscript

ED: Publish subject to technical corrections (13 Feb 2021) by Richard Neale

AR by Yong Wang on behalf of the Authors (16 Feb 2021) Manuscript

Short summary

A stochastic deep convection parameterization is implemented into the US Department of Energy Energy Exascale Earth System Model Atmosphere Model version 1 (EAMv1). Compared to the default model, the well-known problem of too much light rain and too little heavy rain is largely alleviated over the tropics with the stochastic scheme. Results from this study provide important insights into the model performance of EAMv1 when stochasticity is included in the deep convective parameterization.