Estimating the Impacts of Increasing Temperatures and the Efficacy of Climate Adaptation Strategies in Urban Microclimates with Deep Learning

Journal Article · Tue Sep 16 04:00:00 EDT 2025 · Urban Climate

DOI:https://doi.org/10.1016/j.uclim.2025.102603· OSTI ID:2703312

Buster, Grant ^[1]; Cox, Jordan ^[1]; Benton, Brandon ^[1]; King, Ryan ^[1]

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1. National Renewable Energy Lab., Golden, CO (United States)

As urbanization and climate change progress, understanding and addressing urban heat becomes a priority for climate adaptation efforts. High temperatures concentrated in the urban core can drive increased risk of heat-related death and illness as well as increased energy demand for cooling. However, modeling the urban microclimate is an ongoing field of research typically burdened by an imprecise description of the built environment, incomplete observational records, significant computational cost, and a lack of high-resolution estimates of the impacts of increasing temperatures. Here, we present computationally efficient machine learning methods that can improve the accuracy of urban temperature estimates when compared to historical reanalysis data. These models are applied to a neighborhood in Los Angeles, and we compare the energy benefits of heat mitigation strategies to the impacts of climate change. We find that cooling demand is likely to increase substantially through midcentury, but engineered high-albedo surfaces could lessen this increase by more than 50 %. The corresponding increase in winter gas heating offsets the summer cooling benefit in the current climate, but total annual energy use from combined heating and cooling with electric heat pumps benefits from the engineered heat mitigation strategies under both current and future climates.

• Research Organization: National Renewable Energy Laboratory (NREL), Golden, CO (United States)
• Sponsoring Organization: USDOE National Renewable Energy Laboratory (NREL), Laboratory Directed Research and Development (LDRD) Program
• DOE Contract Number: AC36-08GO28308
• OSTI ID: 2703312
• Report Number(s): NREL/JA-6A20-91294
• Journal Information: Urban Climate, Journal Name: Urban Climate Vol. 64
• Country of Publication: United States
• Language: English

Related Subjects

54 ENVIRONMENTAL SCIENCES
97 MATHEMATICS AND COMPUTING
climate adaptation
climate change
heat mitigation
machine learning
urban heat island