Thermal, water, and land cover factors led to contrasting urban and rural vegetation resilience to extreme hot months.

With continuing global warming and urbanization, it is increasingly important to understand the resilience of urban vegetation to extreme high temperatures, but few studies have examined urban vegetation at large scale or both concurrent and delayed responses. In this study, we performed an urban-rural comparison using the Enhanced Vegetation Index and months that exceed the historical 90th percentile in mean temperature (referred to as "hot months") across 85 major cities in the contiguous United States. We found that hot months initially enhanced vegetation greenness but could cause a decline afterwards, especially for persistent (≥4 months) and intense (≥+2 °C) episodes in summer. The urban responses were more positive than rural in the western United States or in winter, but more negative during spring-autumn in the eastern United States. The east-west difference can be attributed to the higher optimal growth temperatures and lower water stress levels of the western urban vegetation than the rural. The urban responses also had smaller magnitudes than the rural responses, especially in deciduous forest biomes, and least in evergreen forest biomes. Within each biome, analysis at 1 km pixel level showed that impervious fraction and vegetation cover, local urban heat island intensity, and water stress were the key drivers of urban-rural differences. These findings advance our understanding of how prolonged exposure to warm extremes, particularly within urban environments, affects vegetation greenness and vitality. Urban planners and ecosystem managers should prioritize the long and intense events and the key drivers in fostering urban vegetation resilience to heat waves.

Exploring the Spatial Patterning of Sociodemographic Disparities in Extreme Heat Exposure at Multiple Scales Across the Conterminous United States.

Climate change has led to an increase in heat-related morbidity and mortality. The impact of heat on health is unequally distributed amongst different socioeconomic and demographic groups. We use high-resolution daily air temperature-based heat wave intensity (HWI) and neighborhood-scale sociodemographic information from the conterminous United States to evaluate the spatial patterning of extreme heat exposure disparities. Assuming differences in spatial patterns at national, regional, and local scales; we assess disparities in heat exposure across race, housing characteristics, and poverty level. Our findings indicate small differences in HWI based on these factors at the national level, with the magnitude and direction of the differences varying by region. The starkest differences are present over the Northeast and Midwest, where primarily Black neighborhoods are exposed to higher HWI than predominantly White areas. At the local level, we find the largest difference by socioeconomic status. We also find that residents of nontraditional housing are more vulnerable to heat exposure. Previous studies have either evaluated such disparities for specific cities and/or used a satellite-based land surface temperature, which, although correlated with air temperature, does not provide the true measure of heat exposure. This study is the first of its kind to incorporate high-resolution gridded air temperature-based heat exposure in the evaluation of sociodemographic disparities at a national scale. The analysis suggests the unequal distribution of heat wave intensities across communities-with higher heat exposures characterizing areas with high proportions of minorities, low socioeconomic status, and homes in need of retrofitting to combat climate change.

Continental United States climate projections based on thermodynamic modification of historical weather.

Regional climate models can be used to examine how past weather events might unfold under different climate conditions by simulating analogue versions of those events with modified thermodynamic conditions (i.e., warming signals). Here, we apply this approach by dynamically downscaling a 40-year sequence of past weather from 1980-2019 driven by atmospheric re-analysis, and then repeating this 40-year sequence a total of 8 times using a range of time-evolving thermodynamic warming signals that follow 4 80-year future warming trajectories from 2020-2099. Warming signals follow two emission scenarios (SSP585 and SSP245) and are derived from two groups of global climate models based on whether they exhibit relatively high or low climate sensitivity. The resulting dataset, which contains 25 hourly and over 200 3-hourly variables at 12 km spatial resolution, can be used to examine a plausible range of future climate conditions in direct reference to previously observed weather and enables a systematic exploration of the ways in which thermodynamic change influences the characteristics of historical extreme events.

Drought and immunity determine the intensity of West Nile virus epidemics and climate change impacts.

The effect of global climate change on infectious disease remains hotly debated because multiple extrinsic and intrinsic drivers interact to influence transmission dynamics in nonlinear ways. The dominant drivers of widespread pathogens, like West Nile virus, can be challenging to identify due to regional variability in vector and host ecology, with past studies producing disparate findings. Here, we used analyses at national and state scales to examine a suite of climatic and intrinsic drivers of continental-scale West Nile virus epidemics, including an empirically derived mechanistic relationship between temperature and transmission potential that accounts for spatial variability in vectors. We found that drought was the primary climatic driver of increased West Nile virus epidemics, rather than within-season or winter temperatures, or precipitation independently. Local-scale data from one region suggested drought increased epidemics via changes in mosquito infection prevalence rather than mosquito abundance. In addition, human acquired immunity following regional epidemics limited subsequent transmission in many states. We show that over the next 30 years, increased drought severity from climate change could triple West Nile virus cases, but only in regions with low human immunity. These results illustrate how changes in drought severity can alter the transmission dynamics of vector-borne diseases.