Extended Abstract (2.3M)4.3
A physically-based parameter for lightning prediction and its calibration in ensemble forecasts
David R. Bright, NOAA/NWS/NCEP/Storm Prediction Center, Norman, OK; and R. E. Jewell, M. S. Wandishin, and S. J. Weiss
The Storm Prediction Center (SPC) issues forecasts over the contiguous United States related to hazardous convective weather including thunderstorms, severe thunderstorms, tornadoes, and elements critical to fire weather such as dry lightning. A physically-based parameter known as the Cloud Physics Thunder Parameter (CPTP) is described that aids in the prediction of lightning. The CPTP uses an observed or model forecast sounding to determine if charge separation is likely to occur. To ensure updraft potential coincides within the favorable temperature range for charge separation, the lifting condensation level must be > -10 C, the equilibrium level temperature < -20 C, and CAPE in the 0 to -20 C layer must be > 100 J/kg. The CPTP is normalized such that values greater than unity indicate the vertical profile supports lightning production given a convective updraft. The CPTP is found to have a very good probability of detection, but suffers from a rather high false alarm ratio due to its insensitivity to the likelihood of convection (e.g., convective inhibition is not accounted for nor is model convective precipitation considered).
The NCEP short-range ensemble forecast (SREF) is used to provide information about the likelihood of convection. When the CPTP is calculated using SREF output, a probabilistic forecast of lightning potential is produced. These forecasts are combined with the probability of precipitation from the SREF to yield a probabilistic forecast of lightning. Cloud-to-ground lightning strike data from the NLDN are then used to calibrate the combined aforementioned probabilities. This technique calibrates itself in short-order, yielding very skillful and reliable forecasts of thunderstorms which serve as guidance to SPC forecasters. A similar parameter and calibration process is used for the prediction of dry lightning.
The lightning prediction parameters, combined probability calibration technique, and verification results are presented. The results appear very promising and should be readily extendable to other products or ensemble systems, and perhaps even more sophisticated diagnostics.
Session 4, Lightning prediction, safety, and protection
Monday, 10 January 2005, 4:00 PM-5:15 PM
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