Abstract
This comprehensive analysis of convective environments associated with thunderstorms affecting portions of central and southern Arizona during the North American monsoon focuses on both observed soundings and mesoanalysis parameters relative to lightning flash counts and severe-thunderstorm reports. Analysis of observed sounding data from Phoenix and Tucson, Arizona, highlights several moisture and instability parameters exhibiting moderate correlations with 24-h, domain-total lightning and severe thunderstorm counts, with accompanying plots of the precipitable water, surface-based lifted index, and 0–3-km layer mixing ratio highlighting the relationship to the domain-total lightning count. Statistical techniques, including stepwise, multiple linear regression and logistic regression, are applied to sounding and gridded mesoanalysis data to predict the domain-total lightning count and individual gridbox 3-h-long lightning probability, respectively. Applications of these forecast models to an independent dataset from 2013 suggest some utility in probabilistic lightning forecasts from the regression analyses. Implementation of this technique into an operational forecast setting to supplement short-term lightning forecast guidance is discussed and demonstrated. Severe-thunderstorm-report predictive models are found to be less skillful, which may partially be due to substantial population biases noted in storm reports over central and southern Arizona.
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