Toward a Remote Sensing System Architecture for Operational Wildfire Prevention Using Lightning Suppression

Past field experiments have demonstrated multiple cloud seeding techniques for modifying the electrical characteristics of developing thunderstorms with the purpose of reducing or eliminating lightning strikes. One motivation for these weather modification research programs was the prospect of preventing wildfires in inaccessible locations or particularly hazardous conditions by temporarily suppressing a prolific ignition source: lightning. It has been nearly 50 years since the last large-scale field effort in lightning suppression, and the ensuing five decades of technological innovation hold the promise of supporting this novel hazard mitigation approach. This study outlines observational and forecasting requirements, as well as an associated remote sensing architecture, that would support an operational wildfire prevention program based on lightning suppression by chaff seeding clouds. Two capabilities enabled by remote sensing observations are highlighted: (1) identifying potential regions of extreme wildfire behavior based on wildland fuels, topography, and weather, and (2) predicting regions where dry lightning strikes are probable. In combination, the proposed nowcasting system would predict the most likely areas of lightning-initiated wildfire danger. Dependent on land management strategies, surrounding infrastructure, firefighting capacity, and risk to human wellbeing, this information could be used to deploy lightning suppression technology to reduce or temporarily prevent wildfire ignitions in these high-risk situations.