An Integrated 0-1 hour First-Flash Lightning Nowcasting and Lightning Amount Algorithm

Lightning is one of the most dangerous weather-related phenomena, especially as many jobs and activities occur outdoors, presenting risk from a lightning strike. Cloud-to-ground (CG) lightning represents a considerable safety threat to people in numerous outdoor activities—from airfields, stadium events, beaches, golf courses, as well as mariners, and emergency personnel. Holle et al. (2005) show that 90% of lightning deaths occurred outdoors, while 10% occurred indoors despite the perception of safety when inside buildings. Curran et al. (2000) found that nearly half of fatalities due to weather were related to convective weather in the 1992-1994 timeframe, with lightning causing a large component of the fatalities, in addition to tornadoes and flash flooding. In the aviation industry, CG lightning represents a considerable hazard to baggage-handlers, aircraft refuelers, food caterers, and emergency personnel, who all become exposed to the risk of being struck within short time periods while convective storm clouds develop. Airport safety protocols require that ramp operations be modified or discontinued when lightning is in the vicinity (typically 16 km), which becomes very costly and disruptive to flight operations. Therefore, much focus has been paid to nowcasting the first-time initiation and extent of lightning, both of CG and of any lightning (e.g, in-cloud, cloud-to-cloud).

Numerous studies have been conducted on the nowcasting of convective initiation through the use of geostationary satellite data (Walker et al. 2012, Mecikalski et al. 2015). Taking a step further, other studies have a shown that including data from the 3.9 µm channel available on the GOES instruments allows for the prediction of the onset of lightning (LI) over the next 0-1 hour (Harris et al. 2010; Iskendarian et al. 2012). Following these studies, a lightning initiation algorithm has been developed using GOES satellite interest fields to focus forecasters on areas where future lightning flashes are expected. Using a storm motion derived from the profile of RAP model winds to determine direction, a polygon is created for a cloud object if it exceeds a certain threshold of LI indicators. The algorithm ingests Multi-Radar/Multi-Sensor (MRMS) reflectivity at the -10°C isotherm to highlight polygons that have radar reflectivities ≥ 40 dBZ. The overall product also makes use of the Lightning Forecast Algorithm available within the operational High Resolution Rapid Refresh (HRRR) model. Using a blend of model forecasts of lightning amounts and flash densities, polygons from the GOES LI algorithm can be overlaid these forecasts to give forecasters an idea of approximately how much lightning is expected if the storms develop.

The lightning alert tool has been developed in concert with National Weather Service (NWS) forecasters to meet their needs for real-time, accurate first-flash LI and timing, as well as anticipated lightning trends and amounts, so to provide key situational awareness and decision support information. The NASA Short-term Prediction Research and Transition (SPoRT) Center has provided important logistical and collaborative support and training, involving interactions with the NWS and broader user community.