GSTDTAP  > 地球科学
DOI10.1016/j.atmosres.2017.04.022
A statistical scheme to forecast the daily lightning threat over southern Africa using the Unified Model
Gijben, Morne1,2; Dyson, Liesl L.2; Loots, Mattheus T.3
2017-09-15
发表期刊ATMOSPHERIC RESEARCH
ISSN0169-8095
EISSN1873-2895
出版年2017
卷号194
文章类型Article
语种英语
国家South Africa
英文摘要

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.


英文关键词Lightning Forecasting Rare-event logistic regression Numerical weather prediction
领域地球科学
收录类别SCI-E
WOS记录号WOS:000405043700006
WOS关键词EVENT LOGISTIC-REGRESSION ; ELECTRICAL CIRCUIT ; PRECIPITABLE WATER ; PREDICTION ; CLIMATOLOGY ; WEATHER ; FLORIDA ; TEMPERATURE ; INDICATOR ; RAINFALL
WOS类目Meteorology & Atmospheric Sciences
WOS研究方向Meteorology & Atmospheric Sciences
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文献类型期刊论文
条目标识符http://119.78.100.173/C666/handle/2XK7JSWQ/38107
专题地球科学
作者单位1.South African Weather Serv, 442 Rigel Ave South,Erasmusrand 0181, ZA-0001 Pretoria, South Africa;
2.Univ Pretoria, Dept Geog Geoinformat & Meteorol, CNR, Lynnwood Rd & Roper St,Hatfield 0002, ZA-0028 Pretoria, South Africa;
3.Univ Pretoria, CNR, Dept Stat, Lynnwood Rd & Roper St,Hatfield 0002, ZA-0028 Pretoria, South Africa
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GB/T 7714
Gijben, Morne,Dyson, Liesl L.,Loots, Mattheus T.. A statistical scheme to forecast the daily lightning threat over southern Africa using the Unified Model[J]. ATMOSPHERIC RESEARCH,2017,194.
APA Gijben, Morne,Dyson, Liesl L.,&Loots, Mattheus T..(2017).A statistical scheme to forecast the daily lightning threat over southern Africa using the Unified Model.ATMOSPHERIC RESEARCH,194.
MLA Gijben, Morne,et al."A statistical scheme to forecast the daily lightning threat over southern Africa using the Unified Model".ATMOSPHERIC RESEARCH 194(2017).
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