A point process analysis of cloud-to-ground lightning strikes in urban and rural Oklahoma areas
KAUST DepartmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Online Publication Date2018-10-10
Print Publication Date2019-02
Permanent link to this recordhttp://hdl.handle.net/10754/630034
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AbstractLightning is a natural event that can cause severe human and financial losses. This work introduces a probability risk assessment of the occurrence of the cloud-to-ground (CG) lightning in urban and rural areas of Oklahoma. CG lightning, although not the most common type, is the most damaging. Previous studies have reported that urban areas experience an increase in the frequency of CG lightning events, during warm months. This increase poses serious threats to urban industries and electronic systems. Lightning strikes are point process in nature, although this quality has not been exploited in previous studies. We utilize a probability model for the spatiotemporal point process of CG lightning to estimate the risk of a CG lightning strike for a particular location and time. The data are discretized into small spatiotemporal cells (voxels), and then, we fit a generalized additive model with a complementary log–log link function using the location and the day of occurrence of the strike as explanatories. On the basis of this model, we compared the urban and rural monthly fitted rates of CG lightning strikes. We found that the rate in the rural area is smaller than the rate in the Tulsa metropolitan area during the warm months; however, it is larger than the rate in the Oklahoma metropolitan area during May and June.
CitationHernandez-Magallanes I, Genton MG (2018) A point process analysis of cloud-to-ground lightning strikes in urban and rural Oklahoma areas. Environmetrics: e2535. Available: http://dx.doi.org/10.1002/env.2535.
SponsorsThe authors thank the Reviewers for the valuable comments provided; Professors Richard Orville, Shaima L. Nasiri, and Courtney Schumacher for their input in the preliminary stage of this work; and Ron Holle at Vaisala Inc. for providing the lightning data. The research described here was supported by King Abdullah University of Science and Technology.