Urban land patterns can moderate population exposures to climate extremes over the 21st century

The study investigates whether and how urban land patterns can moderate, rather than amplify, future population exposures to climate extremes under concurrent climate change and urbanization. Motivated by projections of increased frequency and intensity of extreme weather and continued urban growth, the authors examine the relative and combined effects of climate change, population change, and urban land expansion on exposures to hot days, cold days, heavy rainfalls, and severe thunderstorm environments (STEs) across the continental U.S. at the end of the 21st century. The research emphasizes three aspects: (i) explicitly accounting for urban land change, often overlooked yet capable of altering regional climate; (ii) analyzing continental-scale spatial patterns by urban development densities, climate regions, and 109 sizeable urban centers; and (iii) extending exposure assessments beyond temperature to include precipitation and convective environments. The goal is to understand spatial exposure patterns and identify opportunities to embed long-term climate resilience in urban and regional land-use designs.

Prior work often assumes that urbanization increases exposure to climate extremes, focusing largely on temperature-related risks and individual cities. Urban heat island effects are known to modify local climate extremes, and urban areas can influence precipitation and convective environments. However, many regional climate projections omit explicit urban land change despite substantial anticipated expansion. Spatial population projections commonly rely on gravity models, yielding stable relative spatial distributions over long horizons. The literature’s focus on total urban land amounts and city-scale temperature effects leaves gaps regarding the influence of spatial urban land patterns on continental-scale exposure to a broader set of extremes and how these patterns might reduce exposures.

The analysis uses high-resolution regional climate projections and spatial socioeconomic datasets to quantify exposure as the product of event frequency and population. Climate simulations were produced with the Weather Research and Forecasting (WRF) model at 25-km resolution for the continental U.S., summarizing the beginning of century (BOC: 1980–2005) and end of century (EOC: 2075–2100). Two EOC climate states were considered: (1) climate change under RCP 8.5, and (2) RCP 8.5 plus SSP5 land-use change impacts. Urban land projections derive from the CLUBS-SELECT data-driven framework, which models spatial urban development using 15 datasets and captures changes in urbanization styles, local variations, and the emergence of new centers. Population grids (1-km downscaled to 25-km) represent 2005 and 2090 conditions. Climate extremes were defined per 25-km grid: hot day (daily Tmax ≥ 35 °C), cold day (daily mean temperature ≤ 0 °C), heavy rainfall (hourly precipitation ≥ BOC 5-year return level for that grid), and STE day (daily CAPE × 0–6 km wind shear > 20,000 m3 s−3). Exposure counts (ECs) were computed by multiplying average frequency of each extreme by population for BOC and EOC. Scenarios combined climate, land use, and population to isolate effects: historical (BOC climate, land use, population), climate (EOC climate only), climate+pop (EOC climate and population, fixed land use), and climate+pop+landUse (EOC climate, population, and land use). Effects were quantified using robust ratio-based metrics: climate effect = ECclimate/EChistorical, land-use effect = ECclimate+pop+landUse/ECclimate+pop, population effect = ECclimate+pop/ECclimate. Ratio metrics were validated against helper scenarios (climate+landUse; pop) and shown to consistently separate multiplicative effects. Spatial aggregations examined exposure patterns by urban development density (not developed <20% urban, low-density 20–50%, mid-to-high-density >50%), U.S. National Climate Assessment climate regions, and 109 sizeable urban centers constructed by buffering UN-identified cities >300,000 population with size-dependent circular buffers to represent fixed regional land systems around urban areas. Additional analysis contrasted total precipitation versus heavy rainfall responses to isolate changes in precipitation intensity distribution.

- Over the 21st century in the scenarios examined, U.S. mean temperature increases by 4.4 °C, national population is 2.3× BOC, and total urban land is 4.2× BOC. Resulting national EOC exposure multipliers relative to BOC are: hot days 13.6×, cold days 1.1×, heavy rainfalls 7.5×, and STEs 2.5×. - Urban land expansion has limited impact on national total exposure counts but strongly redistributes who experiences extremes: BOC exposures are mostly non-urban (~65–75%), whereas EOC exposures are primarily urban (~50–75%). - Per-capita exposure to hot days increases from 7 days/person/year (BOC) to 32 (EOC, climate only) and to 41 (EOC with climate+urbanization). At EOC, per-capita hot-day exposure varies by development density: non-urban 29 vs. mid-to-high density 53 days/person/year. - Urban land expansion can decrease exposures in certain contexts (e.g., mid-to-high-density developments for heavy rainfalls), potentially via physical mechanisms (e.g., UHI-induced changes in convective inhibition) and/or population-land-use spatial dynamics (e.g., non-residential dense cores). - Climate effects dominate total exposure changes, strongest for hot days, then heavy rainfalls, weaker for cold days, and weakest for STEs, with modest increase in climate effect from low to high development densities. - Population effects are consistently ~2.3 across categories, reflecting stationarity from gravity-model-based spatial population projections; thus, population largely sets exposure magnitude, while climate and land use shape spatial patterns. - Regional shifts: For hot days, the Southeast surpasses the Southwest to become most heat-exposed; Southern Great Plains catch up; Northeast and Midwest see substantial increases. Heavy rainfall exposures increase markedly in most regions except the Great Plains. Urban land effects vary in sign and magnitude across regions and are not tied to climate effect magnitude. - Comparative regional exposure: Southeast becomes most exposed for three of four extremes; Northeast and Midwest rank high (Midwest highest for cold days); Southwest is stressed by heat and heavy rain; Southern Great Plains primarily heat; Northwest and Northern Great Plains least exposed due to both climatic and urban processes. - Across 109 sizeable urban centers, urban land effects can either increase or decrease exposures and can offset climate-driven increases. Urban land effects show little to no correlation with total urban land amount or its change, indicating spatial patterns and land-cover conversions are key determinants. Examples where land changes reduce hot-day exposure include Savannah (GA), Los Angeles (CA), Boise (ID), Seattle (WA), San Francisco (CA), Salt Lake City (UT), and Virginia Beach (VA) with land-effect ratios from 0.92 to 0.48. - Precipitation totals (annual and summer) change little (~1.1×), while heavy rainfall exposures increase more than threefold, implying a shift toward a greater fraction of precipitation occurring as heavy events.

The findings demonstrate that urban land patterns can moderate, not just amplify, population exposures to climate extremes, addressing the core question of whether urbanization can play a mitigating role. While climate change determines the spatial distribution of extremes and population sets overall exposure magnitude, urban land primarily shapes how and where individuals experience extremes. The decoupling between urban land effect magnitude and total urban land quantity underscores the importance of spatial configuration and land-cover transitions. City-level analyses show that tailored urban land patterns can reduce exposures even where climate change increases them, suggesting actionable levers for design and planning. The results also warn against relying on stationary spatial population projections for long-term spatial exposure analysis, highlighting a need for improved models. Overall, embedding long-term climate resilience into urban and regional land-use patterns can substantially influence individual experiences of future extremes, even though such designs cannot eliminate climate hazards.

This work provides continental-scale evidence that spatial patterns of urban land can moderate population exposures to multiple climate extremes and are more influential than total urban land quantity for shaping experiences. It quantifies dominant climate-driven increases in exposure while revealing opportunities for mitigation through urban pattern design. The study advocates for integrating long-term, adaptive urban and regional land-use planning to enhance climate resilience. Future research should identify and test urban land patterns and mechanisms that most effectively reduce exposures, develop forward-looking, robust socioeconomic spatial models, and create computational sandboxes to evaluate alternative design pathways and policies across diverse future scenarios.

Key limitations include: (1) reliance on a single regional climate model configuration and forcing scenario (WRF under RCP 8.5 with SSP5 land-use change), leaving structural and scenario uncertainties underexplored; and (2) limitations of long-term spatial population projections based on gravity models, which impose stationary spatial distributions that may mask potential shifts. Enhanced multi-model ensembles and improved long-term, large-scale spatiotemporal socioeconomic models are needed to refine estimates and better capture interactions among climate, population, and urban land patterns.