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One measurement modality for rainfall is a fixed location rain gauge.However, extreme rainfall, flooding, and other climate extremes often occur atlarger spatial scales and affect more than one location in a community. Forexample, in 2017 Hurricane Harvey impacted all of Houston and the surroundingregion causing widespread flooding. Flood risk modeling requires understandingof rainfall for hydrologic regions, which may contain one or more rain gauges.Further, policy changes to address the risks and damages of natural hazardssuch as severe flooding are usually made at the community/neighborhood level orhigher geo-spatial scale. Therefore, spatial-temporal methods which convertresults from one spatial scale to another are especially useful in applicationsfor evolving environmental extremes. We develop a point-to-area random effects(PARE) modeling strategy for understanding spatial-temporal extreme values atthe areal level, when the core information are time series at point locationsdistributed over the region.

Spatial-Temporal Extreme Modeling for Point-to-Area Random Effects (PARE)