Comparisons of Wyoming Cloud Radar observations to simulations of precipitation generating cells in winter cyclones

A thorough understanding of the mechanisms that modulate the development, maintenance, structure, and kinematics of cloud-top precipitation generating cells is elusive, yet critical to understanding heavy snowfall in winter cyclones. These cells were consistently observed in the warm-frontal and comma-head regions of Midwestern winter cyclones sampled during the 2009-2010 Profiling of Winter Storms (PLOWS) field campaign. Observations from Wyoming Cloud Radar (WCR) aboard the NSF/NCAR C-130, paired with thermodynamic analyses, indicate that the generating cells had bases above stable frontal layers and tops at the tropopause. Observed generating cell dimensions from the WCR dataset were ~0.75 – 1.5 km wide and ~1.5 – 2.0 km deep, with maximum updrafts and adjacent downdrafts of approximately +/- 3 m s-1.

This paper serves as a pairing of Wyoming Cloud Radar (WCR) observations and idealized Weather Research and Forecasting (WRF) simulations aimed at assessing the role of cloud-top radiative cooling and sublimational cooling on the dynamics of generating cells. Simulations with very small horizontal grid spacing (~50 m) are required due to the small spatial scale of the generating cells. The resolution of both the WRF simulations and WCR observations (~30 m resolution) are unprecedented for winter cyclones, and thus these complementary datasets allow investigations on the interplay of cooling and dynamics. In this paper the simulated bulk characteristics of generating cells in the context of the PLOWS WCR observations are discussed. Specific comparisons will include Contoured Frequency by Altitude Displays (CFADs) of simulated vertical velocity to CFADs of WCR radial velocity corrected for particle fall speed, and Fourier analyses of vertical velocities at the generating cell level to determine cell spacing. Comparisons of bulk characteristics of the generating cells observed by the WCR and output by WRF are particularly useful as an indication of how well the simulations represent what occurred in nature, and thus the utility of the simulations for hypothesis testing.