Abstract

Abstract Rainfall data from the Denver, Colorado, Urban Drainage and Flood Control District Automated Local Evaluation in Real Time (ALERT) network were used to identify heavy rainfall alarms for the period 1999–2003. Twenty-nine heavy rainfall-rate alarms were identified. Cloud-to-ground (CG) lightning flash data from the National Lightning Detection Network (NLDN) were analyzed for the 90 min prior to each heavy rainfall alarm. Spatial patterns from NLDN data were extracted using a point-polygon topology developed with basic Geographic Information System procedures. The information extracted from the polygons was used to calculated summary statistics for rainfall rates, CG flash rates, and CG flash duration. Heavy rainfall episodes were divided into two groups based on latitude, longitude, and elevation. Heavy rainfall episodes in the higher elevations of the study area produced an average of 29 mm of rainfall per episode and 1095 CG flashes in the 90 min prior to the rainfall-rate alarm. Only five polygons, all closely proximal to the alarm sites, produced significant CG flash rates prior to the rainfall alarms, and areas with CG flash durations greater than 25 min were clustered near the rainfall-rate alarm sites. In the second group (the lower elevation stations) the mean event produced a total of 33 mm of rainfall and 1182 CG flashes during the 90 min prior to the rainfall alarm. Four polygons saw consistent CG flash rates in the 90 min prior to the heavy rainfall alarms and CG flash duration was at its greatest in areas just west of the ALERT stations.

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