Model-Generated Predictions of Dry Lightning Risk—Initial Results

Lightning-caused wildfires continue to be a major problem in the western United States. Many of these fires ignite when little or no rainfall reaches the surface. In previous studies we demonstrated the ability to discriminate between “dry” and “wet” convective days using indicators of upper-air moisture and stability. We have applied this methodology using output variables from the Penn State/NCAR mesoscale model (MM5) to develop a predictive scheme for estimating the risk of “dry” lightning. In so doing we have taken advantage of the quasi-terrain-following vertical coordinate system of the MM5 to mitigate the negative effects of widely varying terrain elevations within the model domain. Predictions of the risk of “dry” lightning were generated from real-time MM5 forecasts for the summer of 2004. Eighty-eight large lightning-caused fires were ignited in the model domain during that period. Of those, 35 percent occurred where the probability of dry lightning was predicted to be equal to or greater than 90, and 80 percent of the fires occurred where the probability was 50 percent or greater. Results for the summer of 2005 will also be presented.