Skip to main content
U.S. flag

An official website of the United States government

Publication Date
1 January 2023

Deep Convection in the Southern Great Plains (SGP)

Print / PDF
Powerpoint Slide

Very high-resolution simulations with the Weather Research and Forecasting (WRF) model are performed and subject to uniquely detailed fidelity assessment. Although this simulation exhibits fidelity for the marginal probabilities of wind speed, rainfall rates, and hail occurrence, the joint probabilities of these properties and the maximum size of hail are, as yet, not sufficient to characterize potential damage to key renewable energy industries.


Extremely heavy rain and hail during convective events are challenging to simulate but represent important atmospheric hazards including to the renewable energy industry. Understanding the degree to which convection-permitting simulations represent these phenomena is critical to informing needed improvements and contingent risk assessments.


The Southern Great Plains (SGP) exhibits a relatively high frequency of periods with extremely high rainfall rates (RR) and hail. Seven months of 2017 are simulated using the Weather Research and Forecasting (WRF) model applied at convection-permitting resolution (grid spacing of 1.3 km) with the Mibrandt-Yau microphysics scheme. Simulation fidelity is evaluated, particularly during intense convective events, using data from National Weather Service stations, dual-polarization RADAR, gridded data sets and observations at the DoE Atmospheric Radiation Measurement site. The spatial gradients and temporal variability of precipitation and the cumulative density functions for both rainfall rates and wind speeds exhibit fidelity. Odds ratios >1 indicate WRF is also skillful in simulating high composite reflectivity (cREF, used as a measure of widespread convection) and RR > 5 mmhr-1 over the domain. Detailed analyses of the ten days with the highest spatial coverage of cREF >30 dBZ show spatially similar reflectivity fields and high RR in both RADAR data and WRF simulations. However, during periods of high reflectivity, WRF exhibits a positive bias in terms of very high RR (> 25 mmhr-1) and hail occurrence, and during the summer and transition months, maximum hail size is underestimated. For some renewable energy applications, fidelity is required with respect to the joint probabilities of wind speed and RR and/or hail. While partial fidelity is achieved for the marginal probabilities, performance during events of critical importance to these energy applications is currently not sufficient. Further research into optimal WRF configurations in support of potential damage quantification for these applications is warranted.

Point of Contact
Sara C Pryor
Cornell University
Funding Program Area(s)
Additional Resources: