Cloud-to-ground lightning data from the Southern Africa Lightning Detection Network and numerical weather prediction model parameters from the Unified Model are used to develop a lightning threat index (LTI) for South Africa. The aim is to predict lightning for austral summer days (September to February) by means of a statistical approach. The austral summer months are divided into spring and summer seasons and analysed separately. Stepwise logistic regression techniques are used to select the most appropriate model parameters to predict lightning. These parameters are then utilized in a rare-event logistic regression analysis to produce equations for the LTI that predicts the probability of the occurrence of lightning. Results show that LTI forecasts have a high sensitivity and specificity for spring and summer. The LTI is less reliable during spring, since it over-forecasts the occurrence of lightning. However, during summer, the LTI forecast is reliable, only slightly over-forecasting lightning activity. The LTI produces sharp forecasts during spring and summer. These results show that the LTI will be useful early in the morning in areas where lightning can be expected during the day.
Positive lightning flashes are known to be more intense and cause more damage than negative flashes, although positive flashes only occur about 10% of the time. This study expounds on cloud microphysical aspects of ...
Blumenthal, Ryan; West, Nicholas J.; Jandrell, Ian R.(Lippencott, Williams & Wilkens, 2012-09)
Five mechanisms have been described in the literature regarding lightning injury
mechanisms. A sixth mechanism is proposed in this article, namely, lightning
barotrauma. A simple laboratory experiment was conducted using ...
Poolman, Eugene Rene(University of Pretoria, 2015)
The development of the Severe Weather Impact Forecasting System (SWIFS) for flash flood
hazards in South Africa is described in this thesis. Impact forecasting addresses the need to
move from forecasting weather conditions ...