Articles written in Journal of Earth System Science
Volume 121 Issue 2 April 2012 pp 355-371
A prediction model based on the perfect prognosis method was developed to predict the probability of lightning and probable time of its occurrence over the south-east Indian region. In the perfect prognosis method, statistical relationships are established using past observed data. For real time applications, the predictors are derived from a numerical weather prediction model. In the present study, we have developed the statistical model based on Binary Logistic Regression technique. For developing the statistical model, 115 cases of lightning that occurred over the south-east Indian region during the period 2006–2009 were considered. The probability of lightning (yes or no) occurring during the 12-hour period 0900–2100 UTC over the region was considered as the predictand. The thermodynamic and dynamic variables derived from the NCEP Final Analysis were used as the predictors. A three-stage strategy based on Spearman Rank Correlation, Cumulative Probability Distribution and Principal Component Analysis was used to objectively select the model predictors from a pool of 61 potential predictors considered for the analysis. The final list of six predictors used in the model consists of the parameters representing atmospheric instability, total moisture content in the atmosphere, low level moisture convergence and lower tropospheric temperature advection. For the independent verifications, the probabilistic model was tested for 92 days during the months of May, June and August 2010. The six predictors were derived from the 24-h predictions using a high resolution Weather Research and Forecasting model initialized with 00 UTC conditions. During the independent period, the probabilistic model showed a probability of detection of 77% with a false alarm rate of 35%. The Brier Skill Score during the independent period was 0.233, suggesting that the prediction scheme is skillful in predicting the lightning probability over the south-east region with a reasonable accuracy.
Volume 132, 2023
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