88th Annual Meeting (20-24 January 2008)

Tuesday, 22 January 2008: 4:45 PM
Flash rate, electrical, microphysical, and dynamical relationships across a simulated storm spectrum
222 (Ernest N. Morial Convention Center)
Ariel E. Cohen, NOAA/NWSFO, Jackson, MS; and E. R. Mansell
Poster PDF (890.9 kB)
Many studies have suggested relationships between intracloud and cloud-to-ground flash rates and microphyiscal variables both from an observational perspective and for specific storm intensity and morphology. These relationships provide a necessary component to lightning forecasting, especially when combined with improved and more comprehensive radar data. This study provides an analysis of the relationships between flash rates and several microphysical quantities across a wide spectrum of simulated storms. Some of these quantities include electric field, graupel volume, updraft mass flux, rain mass, ice crystal mass flux, updraft volume, maximum updraft, and cloud ice mass. Eleven unique storms were simulated using the Collaborative Model for Multiscale Atmospheric Simulation (COMMAS) to maximize the temporal and spatial resolution of the analysis. Modifications to surface moisture and bulk shear depth and magnitude yielded a wide range of storm intensity and morphology, from weak, unicell storms, to strong squall lines and supercells. Each case was run with two different noninductive graupel-ice charge separation schemes, for a total of 22 simulations. Results show that the relationships between total flash rate and rain mass, ice crystal mass flux, and graupel volume are significant, while the relationships are weak for electric field and maximum updraft. In cases where convection remained isolated (i.e., one cell in the model domain for most of the 120 minutes), the correlations between detrended total flash rate and graupel volume were also found to be significant. Additionally, by translating flash rate time series backwards in time, the correlation coefficients between flash rates and some of the microphysical variables were found to increase. Understanding these relationships can provide the foundation for future work in predicting flash rates across a wide range of storms based on observational information, including radar data.

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