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A stochastic framework for modeling the population dynamics of convective clouds

Hagos, S., Feng, Z., Plant, R. S., Houze Jr, R. A. and Xiao, H. (2018) A stochastic framework for modeling the population dynamics of convective clouds. Journal of Advances in Modeling Earth Systems, 10 (2). pp. 448-465. ISSN 1942-2466

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To link to this item DOI: 10.1002/2017MS001214

Abstract/Summary

A stochastic prognostic framework for modeling the population dynamics of convective clouds and representing them in climate models is proposed. The framework follows the non-equilibrium statistical mechanical approach to constructing a master equation for representing the evolution of the number of convective cells of a specific size and their associated cloud-base mass flux, given a large-scale forcing. In this framework, referred to as STOchastic framework for Modeling Population dynamics of convective clouds (STOMP), the evolution of convective cell size is predicted from three key characteristics of convective cells: (i) the probability of growth, (ii) the probability of decay, and (iii) the cloud-base mass flux. STOMP models are constructed and evaluated against CPOL radar observations at Darwin and convection permitting model (CPM) simulations. Multiple models are constructed under various assumptions regarding these three key parameters and the realisms of these models are evaluated. It is shown that in a model where convective plumes prefer to aggregate spatially and the cloud-base mass flux is a non-linear function of convective cell area, then the mass flux manifests a recharge-discharge behavior under steady forcing. Such a model also produces observed behavior of convective cell populations and CPM simulated cloud-base mass flux variability under diurnally varying forcing. In addition to its use in developing understanding of convection processes and the controls on convective cell size distributions, this modeling framework is also designed to be capable of serving as a non-equilibrium closure formulations for spectral mass flux parameterizations.

Item Type:Article
Refereed:Yes
Divisions:Faculty of Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:75248
Publisher:American Geophysical Union

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