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To mitigate the devastating impacts of hurricanes on people’s lives, communities, and societal infrastructures, disaster management would benefit considerably from a detailed understanding of evacuation, including the socio-demographics of the populations that evacuate, or remain, down to disaggregated geographic levels such as local neighborhoods. A detailed household evacuation prediction model for local neighborhoods requires both a robust household evacuation decision model and individual household data for small geographic units. This paper utilizes a recently pub- lished statistical meta-analysis for the first requirement and then conducts a rigorous population synthesis procedure for the second. Our model produces predicted non-evacuation rates for all US Census block groups for the Tampa-St. Petersburg-Clearwater Metropolitan Statistical Area for a Hurricane Irma-like storm along with their socio-demographic and hurricane impact risk profiles. Our model predictions indicate that non- evacuation rates are likely to vary considerably, even across neighboring block groups, driven by the variability in evacuation risk profiles. Our results also demonstrate how different predictors may come to the fore in influencing non-evacuation in different block groups, and that predictors which may have an outsize impact on individual household evacuation decisions, such as Race, are not necessarily associated with the greatest differentials in non-evacuation rates when we aggregate households to block group level and above. Our research is intended to provide a framework for the design of hurricane evacuation prediction tools that could be used in disaster management. 

The origin of electrical activity accompanying volcanic ash plumes is an area of heightened interest in volcanology. However, it is unclear how intense an eruption needs to be to produce lightning flashes as opposed to “vent discharges,” which represent the smallest scale of electrical activity. This study targets 97 carefully monitored plumes <3 km high from Sakurajima volcano in Japan, from June 1 to 7, 2015. We use multiparametric measurements from sensors including a nine‐station lightning mapping array and an infrared camera to characterize plume ascent. Findings demonstrate that the impulsive, high velocity plumes (>55 m/s) were most likely to create vent discharges, whereas lightning flashes occurred in plumes with high volume flux. We identified conditions where volcanic lightning occurred without detectable vent discharges, highlighting their independent source mechanisms. Our results imply that plume dynamics govern the charging for volcanic lightning, while the characteristics of the source explosion control vent discharges.