The characteristics of lightning risk and zoning in Beijing simulated by a risk assessment model

Abstract

Abstract. In this study, the cloud-to-ground (CG) lightning flash/stroke density was derived from the lightning location finder (LLF) data recorded between 2007 and 2011. The vulnerability of land surfaces was then assessed from the classification of the study areas into buildings, outdoor areas under the building canopy and open-field areas, which makes it convenient to deduce the location factor and confirm the protective capability. Subsequently, the potential number of dangerous lightning events at a location could be estimated from the product of the CG stroke density and the location's vulnerability. Although the human beings and all their material properties are identically exposed to lightning, the lightning casualty risk and property loss risk was assessed respectively due to their vulnerability discrepancy. Our analysis of the CG flash density in Beijing revealed that the valley of JuMaHe to the southwest, the ChangPing–ShunYi zone downwind of the Beijing metropolis, and the mountainous PingGu–MiYun zone near the coast are the most active lightning areas, with densities greater than 1.5 flashes km−2 year−1. Moreover, the mountainous northeastern, northern, and northwestern rural areas are relatively more vulnerable to lightning because the high-elevation terrain attracts lightning and there is little protection. In contrast, lightning incidents by induced lightning are most likely to occur in densely populated urban areas, and the property damage caused by lightning here is more extensive than that in suburban and rural areas. However, casualty incidents caused by direct lightning strokes seldom occur in urban areas. On the other hand, the simulation based on the lightning risk assessment model (LRAM) demonstrates that the casualty risk is higher in rural areas, whereas the property loss risk is higher in urban areas, and this conclusion is also supported by the historical casualty and damage reports.