Abstract
ABSTRACTLightning risk indexes identifying the potential number of dangerous lightning events (NDLE) and ground sensitivity to lightning in residential sub-districts in the Beijing metropolitan area have been estimated on a 5 m resolution grid for the first time. The gridded cloud-to-ground (CG) lightning strike density was used in the NDLE calculation, on account of the multiple contacts formed by CG events with multiple lightning flashes. Meanwhile, in the NDLE estimates, the critical CG strike densities derived from the lightning location system data were corrected for network detection efficiency (DE). The case study for a residential sub-district indicates that the site-specific sensitivity to lightning, which is determined by the terrain factors related to lightning attachment and the lightning rod effects induced by nearby structures, differs greatly among types of underlying ground areas. The discrepancy in the NDLE, which is the numerical product of sensitivity and CG strike density, is dominated by the sensitivity to the relatively stationary CG strike density at the residential sub-district scale. Conclusively, the visualization of lightning risk sensitivity and NDLE differences in parts of a residential sub-district at a high spatial resolution makes this model useful in risk reduction and risk control for lightning risk management.
Highlights
The frequent occurrences of lightning disaster events cause large numbers of casualties and substantial damage losses, such that lightning is considered one of the most dangerous natural hazards (Curran et al 2000; Holle et al 2005; Zhang et al 2011) and the second most fatal meteorological phenomenon (Ashley and Gilson 2009)
Before being used in number of dangerous lightning events (NDLE) estimates, the CG strike densities derived from lightning location system (LLS) data should be corrected for detection efficiency (DE)
The correction of CG strike density makes it better qualified for risk assessment, the LLS data should be made more reliable through network upgrades, which can improve the DE and location accuracy (Rudlosky and Fuelberg 2010)
Summary
The frequent occurrences of lightning disaster events cause large numbers of casualties and substantial damage losses, such that lightning is considered one of the most dangerous natural hazards (Curran et al 2000; Holle et al 2005; Zhang et al 2011) and the second most fatal meteorological phenomenon (Ashley and Gilson 2009). Approaches will be employed in pattern recognition of topographical features, locating earthen structures and determining their lightning collection areas, downscaling grids of cloud-to-ground (CG) strike densities, among others These processes can be accomplished with the support of GIS technology using high-resolution map data. The approach is to derive lightning parameters (e.g. CG flash/strike density and CG flash multiplicity) from observational data, e.g. climatological data (Changnon 1985; Gabriel and Changnon 1989), remote sensing lightning imagery (Christian et al 2003) and lightning location system (LLS) data (Changnon 1993; Schulz et al 2005; Biagi et al 2007; Cummins and Murphy 2009) These lightning parameters fundamentally reflect regional lightning activity relevant to lightning disaster occurrence (Schulz et al 2005; M€akel€a et al 2010). This site-specific lightning risk is critical to public safety and infrastructure planning (Stallins and Rose 2008)
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