Cloud-Resolving Model Intercomparison of a MC3E Squall Line Case: Part I – Convective Updrafts

 

Authors

Jiwen Fan — Pacific Northwest National Laboratory
Bin Han — Pacific Northwest National Laboratory
Adam Varble — Pacific Northwest National Laboratory
Hugh Clifton Morrison — University Corporation for Atmospheric Research
Kirk North — McGill University
Pavlos Kollias — Stony Brook University
Baojun Chen — Nanjing University
Xiquan Dong — University of Arizona
Scott Giangrande — Brookhaven National Laboratory
Alexander Khain — The Hebrew University of Jerusalem
Yun Lin — Texas A&M University
Edward Mansell — NOAA/National Severe Storms Lab
Jason Milbrandt — Meteorological Research Division, Environment Canada
Ronald Stenz — University of North Dakota
Gregory Thompson — National Center for Atmospheric Research (NCAR)
Yuan Wang — Jet Propulsion Laboratory/California Institute of Technology

Category

Convective clouds, including aerosol interactions

Description

A constrained model intercomparison study of a mid-latitude mesoscale squall line is performed using the Weather Research & Forecasting (WRF) model at 1-km horizontal grid spacing with eight cloud microphysics schemes to understand specific processes that lead to the large spread of simulated cloud and precipitation at cloud-resolving scales. The focus of this poster is convective updrafts. Various observational data are employed to evaluate the baseline simulations. All simulations tend to produce a wider convective area than observed, but a much narrower stratiform area, with most bulk schemes overpredicting radar reflectivity (Ze). The magnitudes of the virtual potential temperature drop, pressure rise, and the peak wind speed associated with the passage of the gust front are significantly smaller than the observations, suggesting simulated cool pools are weaker. Simulations also overestimate the vertical velocity and Ze in updrafts as compared with observational retrievals. The modeled updraft velocity and precipitation have a significant spread across the eight schemes even in this strongly dynamically driven system. The spread in updraft velocity is attributed to the joint effects of the low-level perturbation pressure gradient determined by cold-pool intensity and buoyancy. Updraft velocity variability between schemes is mainly controlled by differences in ice-related parameterizations mainly on riming, drop freezing, and deposition, whereas precipitation variability increases in no-ice simulations because of scheme differences in collision-coalescence parameterizations.