A statistical scheme to forecast the daily lightning threat over southern Africa using the Unified Model

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dc.contributor.author Gijben, Morne
dc.contributor.author Dyson, Liesl L.
dc.contributor.author Loots, Mattheus Theodor
dc.date.accessioned 2017-06-28T13:32:14Z
dc.date.issued 2017-09 en
dc.description.abstract 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. en_ZA
dc.description.department Geography, Geoinformatics and Meteorology en
dc.description.embargo 2018-09-15
dc.description.uri http://www.elsevier.com/locate/atmos en
dc.identifier.citation Gijben, M., Dyson, L.L. & Loots, M.T. 2017, 'A statistical scheme to forecast the daily lightning threat over southern Africa using the Unified Model', Atmospheric Research, vol. 194, pp. 78-88. en
dc.identifier.issn 1873-2895 (online) en
dc.identifier.issn 0169-8095 (print) en
dc.identifier.other 10.1016/j.atmosres.2017.04.022 en
dc.identifier.uri http://hdl.handle.net/2263/61163
dc.language.iso English en
dc.publisher Elsevier en
dc.rights © 2017 Elsevier B.V. All rights reserved. Notice : this is the author's version of a work that was accepted for publication in Atmospheric Research. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. A definitive version was subsequently published in Atmospheric Research, vol. 194, pp. 78-88, 2017. doi : 10.1016/j.atmosres.2017.04.022. en
dc.subject Lightning en
dc.subject Numerical weather prediction en
dc.subject Rare-event logistic regression en
dc.subject Clouds en
dc.subject Forecasting en
dc.subject Lightning en
dc.subject Regression analysis en
dc.subject Cloud-to-ground lightning en
dc.subject Lightning detection en
dc.subject Logistic regression analysis en
dc.subject Numerical weather prediction en
dc.subject Numerical weather prediction models en
dc.subject Statistical approach en
dc.subject Statistical scheme en
dc.subject Weather forecasting en
dc.subject Numerical model en
dc.subject Prediction en
dc.subject Statistical analysis en
dc.subject Weather forecasting en
dc.subject South Africa (SA) en
dc.title A statistical scheme to forecast the daily lightning threat over southern Africa using the Unified Model en_ZA
dc.type Postprint Article en


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