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

dc.contributor.authorGijben, Morne
dc.contributor.authorDyson, Liesl L.
dc.contributor.authorLoots, Mattheus Theodor
dc.date.accessioned2017-06-28T13:32:14Z
dc.date.issued2017-09en
dc.description.abstractCloud-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.departmentGeography, Geoinformatics and Meteorologyen
dc.description.embargo2018-09-15
dc.description.urihttp://www.elsevier.com/locate/atmosen
dc.identifier.citationGijben, 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.issn1873-2895 (online)en
dc.identifier.issn0169-8095 (print)en
dc.identifier.other10.1016/j.atmosres.2017.04.022en
dc.identifier.urihttp://hdl.handle.net/2263/61163
dc.language.isoEnglishen
dc.publisherElsevieren
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.subjectLightningen
dc.subjectNumerical weather predictionen
dc.subjectRare-event logistic regressionen
dc.subjectCloudsen
dc.subjectForecastingen
dc.subjectLightningen
dc.subjectRegression analysisen
dc.subjectCloud-to-ground lightningen
dc.subjectLightning detectionen
dc.subjectLogistic regression analysisen
dc.subjectNumerical weather predictionen
dc.subjectNumerical weather prediction modelsen
dc.subjectStatistical approachen
dc.subjectStatistical schemeen
dc.subjectWeather forecastingen
dc.subjectNumerical modelen
dc.subjectPredictionen
dc.subjectStatistical analysisen
dc.subjectWeather forecastingen
dc.subjectSouth Africa (SA)en
dc.titleA statistical scheme to forecast the daily lightning threat over southern Africa using the Unified Modelen_ZA
dc.typePostprint Articleen

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