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Lightning data provide a valuable tool for examining interactions between multi-scale weather phenomena. Weather events are determined by complex atmospheric interactions at various spatial and temporal scales. Long-term climatologies facilitate discussion of average meteorological conditions and can help isolate the relative influence of multi-scale systems (e.g., synoptic scale, mesoscale, etc.) on local weather patterns. Lightning datasets allow the development of large-scale, long-term climatologies. These lightning climatologies then are compared with additional atmospheric observations (e.g., numerical models and radar) to examine the regional, seasonal, and storm-scale variability of thunderstorm characteristics. The National Lightning Detection Network (NLDN) underwent a major upgrade during 2002–2003 that increased its sensitivity and improved its performance. Therefore, this study applies the same methodology to pre- and post-upgrade NLDN datasets to allow direct quantitative comparisons between them and thereby examine the influence of the recent upgrade on regional distributions of cloud-to-ground (CG) lightning characteristics. Although seasonal variability must be understood to better define apparent relationships between storm properties and lightning production, seasonal differences are best described on the regional scale. Therefore, this study also examines Florida's seasonal, regional, and storm-scale CG variability during 2004–09. Since lightning data are recorded instantaneously and typically reported every minute, they also provide valuable information on storm-scale development and evolution. Automated procedures are developed to create grids of lightning and radar parameters, cluster individual storm features, and data mine the lightning and radar attributes of many individual storms. These procedures facilitate detailed analysis of relationships between lightning and radar-derived parameters in many individual storms in the Mid-Atlantic Region during 2007–09. A major goal of this research is to combine information about the near-storm environment, radar-defined storm structure, and both intra-cloud (IC) and CG lightning characteristics to better quantify relationships between storm structure, lightning production, and storm severity.