Sensitivity of Simulated Deep Convection to a Stochastic Ice Microphysics Framework

Journal of Advances in Modeling Earth Systems

Greg McFarquhar¹  Wei Wu¹  Adam Varble²  McKenna W. Stanford²  Jason Milbrandt³  Judith Berner⁴  Hugh Morrison⁴ 

[1] Cooperative Institute for Mesoscale Meteorological Studies Norman OK USA;Department of Atmospheric Sciences University of Utah Salt Lake City UT USA;Meteorological Research Division Environment and Climate Change Canada Dorval Quebec Canada;National Center for Atmospheric Research Boulder CO USA;

关键词: ice microphysics;    mesoscale convective systems;    stochastic physics;    parameterization development;    model‐observation comparison;    cloud radiative forcing;   

DOI  :  10.1029/2019MS001730

来源: DOAJ

【 摘 要 】

Abstract Ice microphysics parameterizations in models must make major simplifications relative to observations, typically employing empirical relationships to represent average functional properties of particles. However, previous studies have established that ice particle properties vary even in similar cloud types and thermodynamic environments, and it remains unclear how this so‐called “natural variability” impacts simulated deep convection. This uncertainty is addressed by implementing a stochastic framework into the Predicted Particle Properties microphysics scheme in the Weather Research and Forecasting model. The approach stochastically varies the coefficients of the mass‐size (m‐D) relationship (m=aDb) for unrimed and partially rimed ice. Using guidance from aircraft in situ measurements obtained during the Midlatitude Continental Convective Clouds Experiment (MC3E), the scheme samples from distributions of the prefactor (a) and the exponent (b) of the m‐D relationship. Simulations of two MC3E deep convective cases indicate that the stochastic m‐D scheme produces considerable variability of anvil cirrus cloud optical depth (τ) distributions, even for the same ice water path (IWP). Thus, the stochastic scheme produces variable cloud radiative forcing that is independent of IWP. This τ‐IWP relationship variability is nonexistent using the deterministic m‐D ensemble. Additional sensitivity tests are performed in which the fallspeed‐size relationship (V=cDd) is stochastically varied, resulting in variable precipitation amounts and rain rate distributions. Results are presented in the context of satellite and precipitation observations and include comparison with other ensemble configurations using perturbed initial and lateral boundary conditions and small‐amplitude noise added to the potential temperature field.

【 授权许可】

Unknown