Global Positioning System (GPS) Precipitable Water in Forecasting Lightning at Spaceport Canaveral

Abstract

This paper evaluates the use of precipitable water (PW) from the global positioning system (GPS) in lightning prediction. Additional independent verification of an earlier model is performed. This earlier model used binary logistic regression with the following four predictor variables optimally selected from a candidate list of 23 candidate predictors: the current precipitable water value for a given time of the day, the change in GPS PW over the past 9 h, the K index, and the electric field mill value. The K index was used as a measure of atmospheric stability, which, of the traditional stability measures, has been shown to work best in the area and season under study. This earlier model was not optimized for any specific forecast interval, but showed promise for 6- and 1.5-h forecasts. Two new models were developed and verified. These new models were optimized for two operationally significant forecast intervals. The first model was optimized for the 0.5-h lightning advisories issued by the U.S. Air Force?s 45th Weather Squadron. An additional 1.5 h was allowed for sensor dwell, communication, calculation, analysis, and advisory decision by the forecaster. Therefore, the 0.5-h advisory model became a 2-h forecast model for lightning within the 45th Weather Squadron advisory areas. The second model was optimized for major ground processing operations supported by the 45th Weather Squadron, which can require lightning forecasts with a lead time of up to 7.5 h. Using the same 1.5-h lag as in the other new model, this became a 9-h forecast model for lightning within 37 km (20 n mi) of the 45th Weather Squadron advisory areas. The two new models were built using binary logistic regression and a list of 26 candidate predictor variables: the current GPS PW value, the K index, and 24 candidate variables of the change in GPS PW levels over 0.5-h increments up to 12 h. The new 2-h model found the following four predictors to be statistically significant, listed in decreasing order of contribution to the forecast: the 0.5-h change in GPS PW, the 7.5-h change in GPS PW, the current GPS PW value, and the K index. The new 9-h forecast model found the following five independent variables to be statistically significant, listed in decreasing order of contribution to the forecast: the current GPS PW value, the 8.5-h change in GPS PW, the 3.5-h change in GPS PW, the 12-h change in GPS PW, and the K index. In both models, the GPS PW parameters had better correlation to the lightning forecast than did the K index, a widely used thunderstorm index. Possible future improvements to this study are discussed.