A Stochastic Framework for Modeling the Population Dynamics of Convective Clouds. (20th February 2018)

• Record Type: Journal Article
• Authors: Hagos, Samson; Feng, Zhe; Plant, Robert S.; Houze, Robert A.; Xiao, Heng
• Is Part Of: Journal of advances in modeling earth systems. Volume 10:Number 2(2018)
• Page Start: 448
• Page End: 465
• Publication Date: 2018-02-20
• Subjects: stochastic -- nonequilibrium -- parameterization -- population dynamics -- convection; Geological modeling -- Periodicals; Climatology -- Periodicals; Geochemical modeling -- Periodicals; 551.5011
• DOI: 10.1002/2017MS001214
• Languages: English
• ISSNs: 1942-2466

Abstract

Abstract: A stochastic prognostic framework for modeling the population dynamics of convective clouds and representing them in climate models is proposed. The framework follows the nonequilibrium 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 nonlinear function of convective cell area, 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 serve as a nonequilibrium closure formulations for spectral mass flux parameterizations. Plain Language Summary: A new approach to modeling the evolution of the size spectrum of populations of convective clouds is proposed. This nonequilibrium, probabilistic modeling framework is designed to provide (i) understanding of cloud‐cloud and cloud‐environment interactions and (ii) enable representation of these interactions in cumulus parameterizations. Key Points: A new nonequilibrium, stochastic framework for predicting the evolution of size spectrum of clouds and associated mass fluxes is developed In this framework, models are defined by the probabilities of growth and decay of clouds and the dependence of mass flux on clouds size The importance of aggregation and nonlinearity of relationship between cell size and mass flux in cloud population dynamics is highlighted