Presenter: Guang Zhang

Title: Coupling Stochastic Convection Parameterization with ZM in E3SM

Abstract:Like many Global Climate Models and Earth System Models, E3SM has a problem of “too much drizzle and too little heavy rain”. A likely cause of this is that convection occurs too often. We recently introduced a stochastic deep convection parameterization into E3SMv1 and coupled it with the Zhang-McFarlane (ZM) deep convection scheme. The simulated PDF of rainfall intensity is greatly improved, with the “too much drizzle and too little heavy rain” problem alleviated. The reduction of light rain frequency is entirely from convection whereas the increase in heavy rain comes from both convection and grid-scale precipitation. Both the intraseasonal and synoptic-scale variances are also increased. The climatological means of variables of interest remain about the same as the default E3SMv1, which means no extensive model tuning is needed if/when adopted into E3SMv2.

Date

23 Apr 2020

Time

PT: 8:30 am
ET: 11:30 am

Call Info

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Attendees

Presentaiton

Time	Title	Presenter	Presentation	Recording	Notes
30 min	Coupling Stochastic Convection Parameterization with ZM in E3SM	Guang Zhang	E3SM-all-hands-Stochastic Convection.pptx	MP4 Movie (on the E3SM YouTube Channel)

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