Improving the Physical Basis for Updraft Dynamics in Deep Convection Parameterizations

Abstract

This article presents a new deep convective parameterization that determines cloud characteristics based on a specified cloud size distribution. The vertical profiles of cloud properties are determined by analytic equations, which formulate entrainment with an inverse relationship to cloud width. In line with recent studies of large eddy simulations (LES), cloud widths are assumed to be constant with height and vertical mass flux (M) characteristics of the clouds are therefore regulated by the vertical velocity profile. The parameterization is configured to work with existing cloud baseMclosure formulations, with the closure predicting the total cloud area rather than the cloud baseMdirectly. Analytic formula are also used to connect the vertical wind shear magnitude to the cloud size distribution, wherein larger shear magnitudes result in more numerous large updrafts than weaker shear magnitudes, which is in line with recent research results. The parameterization is compared against 10 deep convective LES with varying thermodynamic and vertical wind shear profiles. Results show dramatic improvements in the prediction of normalizedM, detrainment, and the properties of detrained air over the existing Zhang and McFarlane (1995) scheme. In particular, the new model is able to correctly portray the transition from a bottom‐heavyMprofile in weakly sheared environments, to a top‐heavyMprofile in strongly sheared environments.

Document Details

Document Type
Pub Defense Publication
Publication Date
Feb 01, 2021
Source ID
10.1029/2020ms002282

Entities

People

  • Guang J. Zhang
  • Hugh Morrison
  • John M. Peters
  • Scott W. Powell

Organizations

  • National Center for Atmospheric Research
  • National Science Foundation
  • Naval Postgraduate School
  • United States Department of Energy
  • University of California, San Diego

Tags

Fields of Study

  • Environmental science

Readers

  • Aerosol Science/Aerosol Physics
  • Atmospheric Science / Meteorology, specifically Wind Wave Turbulence.
  • Ocean-Atmosphere Mesoscale Modeling, Data Assimilation, and Flux Boundary Layers