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Abstract Hurricanes significantly harm homeowners through physical damage and long-term financial strain due to rising insurance costs, property value loss, and repair expenses. This paper focuses on the interrelated decisions of the government mitigation funding of residential acquisitions and retrofit subsidies and of price restrictions on the insurance market in eastern North Carolina to determine the financial effects on stakeholders. The introduction of these policy interventions have impacts that propagate through the system due to risk adjustments, homeowner take-up behaviour, and insurer profit-maximising behaviour. This study uses an integrated game theoretic model to demonstrate that there are cost-effective government spending levels that reduce residential loss from hurricane damage. When insurance prices are capped at preintervention levels, the number of households and their distribution of losses, which has been altered through mitigation, leads to increased insurer insolvency. When insurance prices are allowed to adjust after mitigation, some homeowners find insurance is no longer affordable. This highlights the tradeoff between ensuring insurer stability and expanding homeowner insurance accessibility. 

Body size declines are a common response to warming via both plasticity and evolution, but variable size responses have been observed for terrestrial ectotherms. We investigate how temperature-dependent development and growth rates in ectothermic organisms induce variation in size responses. Leveraging long-term data for six montane grasshopper species spanning 1,768–3 901 m, we detect size shifts since ~1960 that depend on elevation and species’ seasonal timing. Size shifts have been concentrated at low elevations, with the early emerging species (those that overwinter as juveniles) increasing in size, while later season species are becoming smaller. Interannual temperature variation accounts for the size shifts. The earliest season species may be able to take advantage of warmer conditions accelerating growth during early spring development, whereas warm temperatures may adversely impact later season species via mechanisms such as increased rates of energy use or thermal stress. Grasshoppers tend to capitalize on warm conditions by both getting bigger and reaching adulthood earlier. Our analysis further reinforces the need to move beyond expectations of universal responses to climate change to consider how environmental exposure and sensitivity vary across elevations and life histories. 

Abstract Avoiding floodplain development is critical for limiting flood damage, yet there is little empirical evidence of how local governments effectively avoid floodplain development. We conduct a mixed-methods study to explain how local floodplain management influences floodplain development in New Jersey, a state with high development pressure and flood risk. We find that 85% of towns developed relatively little in the floodplain from 2001 to 2019, and they achieved this with commonplace land use management tools and modest levels of local government capacity. One hundred twenty-six New Jersey towns put none of their new housing in the floodplain 2001–2019. Our findings run counter to common reports of rampant floodplain development requiring legal innovation and capacity-building campaigns and suggest alternative approaches for promoting floodplain avoidance. We find multiple paths to floodplain avoidance, weak support for previously identified drivers, and strong evidence that the keys to avoidance include having a few high-quality tools that are well-implemented, requiring consistency, coordination, and commitment of local officials. The multiple paths and importance of maximum, rather than average, quality might explain the mixed evidence in prior research connecting floodplain management actions and development outcomes. A lack of attention to towns that limit floodplain development impedes our ability to learn from and disseminate their successes. Contrary to our expectations, we show that floodplain avoidance can be and is achieved through routine municipal practices. Our findings underscore the importance of sustained commitment to development management as a core tool for limiting flood risk. 

Wind fragility curves for roof sheathing were developed for single-family building models to investigate the effects of roof shape and roof pitch on the wind performance of roof sheathing. For gable roofs, it was found that more complex roof shapes are more likely to suffer roof sheathing damage when subjected to high winds. The probability of no roof sheathing failure can be up to 36% higher for a simple gable roof than for a complex gable roof. For hip roofs with different configurations, variation in roof shape has minimal effect on roof sheathing fragility. Roof pitch effects were also evaluated for 10 pitch angles, ranging from 14° to 45°. Results suggest that for roof pitches smaller than 27°, the effects of this angle are more substantial on the performance of gable roofs than on hip roofs. For gable roofs, the probability of no roof sheathing failure can be up to 23% higher for a 23° roof pitch than that for an 18° roof pitch. Furthermore, the inclusion of complex roof shapes in a regional hurricane loss model for New Hanover County, North Carolina, accounted for a 44% increase in estimated annual expected losses from roof sheathing damages compared to a scenario in which all roofs are assumed to have rectangular roof shapes. Therefore, to avoid an underestimation of roof damages due to high-wind impact, the inclusion of complex roof geometries in hurricane loss modeling is strongly recommended. 

Abstract. Regional hurricane risk is often assessed assuming a static housing inventory, yet a region's housing inventory changes continually. Failing to include changes in the built environment in hurricane risk modeling can substantially underestimate expected losses. This study uses publicly available data and a long short-term memory (LSTM) neural network model to forecast the annual number of housing units for each of 1000 individual counties in the southeastern United States over the next 20 years. When evaluated using testing data, the estimated number of housing units was almost always (97.3 % of the time), no more than 1 percentage point different than the observed number, predictive errors that are acceptable for most practical purposes. Comparisons suggest the LSTM outperforms the autoregressive integrated moving average (ARIMA) and simpler linear trend models. The housing unit projections can help facilitate a quantification of changes in future expected losses and other impacts caused by hurricanes. For example, this study finds that if a hurricane with characteristics similar to Hurricane Harvey were to impact southeastern Texas in 20 years, the residential property and flood losses would be nearly USD 4 billion (38 %) greater due to the expected increase of 1.3 million new housing units (41 %) in the region.