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Comprehensive Evaluations of Mesoscale Convective Systems Simulated in Convection-permitting WRF Model during the MC3E Field Experiment

Presentation Date
Tuesday, December 11, 2018 at 1:40pm
Walter E Washington Convention Center Hall A-C (Poster Hall)



Mesoscale convective systems (MCSs) are an important component of our hydrologic cycle as they produce prolific rainfall in the tropics and mid-latitudes. Recent advancements in high-resolution modeling show promise in representing MCSs in regional climate simulations. However, how well do these models represent the complex interactions between convective dynamics and microphysics in MCSs remain unknown. In this study, we take advantage of observations collected during the Midlatitude Continental Convective Cloud (MC3E) experiment to evaluate multi-scale aspects of MCSs in convection-permitting WRF model. We conducted three sets of month-long simulations with Morrison and P3 (1-ice and 2-ice categories) microphysics, respectively, at 1.8 km grid-spacing over the Southern Great Plains. MCSs in observations and simulations were tracked using a newly developed FLEXTRKR algorithm. About 15-20 MCSs were identified in the simulations, consistent with observations. All three simulations underestimate observed monthly total precipitation which are primarily from MCSs, suggesting the biases might be caused by large-scale forcings rather than microphysics. All simulated MCSs overestimate convective area and precipitation amount but underestimate stratiform rain area and precipitation. Simulated MCS convective updraft intensities are comparable with radar retrievals for moderate depths of convective cores, but are too strong for deep cores. The two P3 simulations have smaller mean ice mass aloft but more frequent heavy convective rain rate at the surface than the simulation with Morrison, agreeing better with observations (Figure 1). Simulated stratiform area ice mass in the upper troposphere are generally larger than radar retrievals, but the P3 2-ice category has relatively smaller bias. We will also use polarimetric radar 3-D rain water retrieval to further evaluate the vertical evolution of rainfall to explain differences in simulated surface precipitation.