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


Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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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.