The research, led by Fatemeh Salehipour Bavarsad of the Czech Technical University in Prague together with colleagues at Shahrood University of Technology and Osaka Metropolitan University, tackles this blind spot head-on. The team developed high-resolution, site-specific urban weather datasets that explicitly account for the urban heat island effect, the well-documented phenomenon in which cities run several degrees warmer than their rural surroundings because asphalt, concrete and building mass absorb and re-emit heat while vegetation and moisture are scarce. Rather than treating the city as a passive backdrop, the researchers coupled statistically downscaled future climate projections with a physics-based urban canopy model known as the Urban Weather Generator, or UWG, to produce multiple urbanized future weather files tailored to a specific urban site.

The Urban Weather Generator works by taking an upstream rural weather signal and transforming it through a physically grounded representation of the urban fabric. It accounts for how much of the site is covered by buildings, how tall those buildings are, how closely they are packed, the thermal properties of their walls and roofs, and the heat released by human activity and traffic. As solar radiation heats horizontal surfaces during the day and those surfaces release stored energy at night, the model computes the resulting air temperature differences between the rural reference and the urban site, hour by hour. This means the output is not a generic city correction but a weather file that reflects the actual three-dimensional geometry and material composition of the neighborhood surrounding a given building.

To disentangle the many forces at play, the team designed a structured three-scenario framework. The first scenario isolates regional climate change, asking how a future atmosphere alone alters building behavior. The second adds the urban heat island effect on top of that changed climate, capturing the extra thermal burden that urbanization imposes. The third goes further and incorporates the surrounding urban morphology, meaning the actual arrangement of neighboring buildings and their radiative and shading interactions with the building under study. By comparing results across these scenarios, the researchers could attribute changes in building performance to each driver separately, and, crucially, observe how the drivers interact with one another in ways that simple additive assumptions miss.

The test case is a representative mid-rise office building in Osaka, Japan, a metropolis that combines a hot, humid summer climate with intense urban density, making it an ideal laboratory for studying the collision between global warming and urban heat. The team simulated the building’s energy use and indoor thermal conditions under conventional weather files and under their new urbanized future weather files, tracking metrics that include cooling energy demand, indoor overheating degree, indoor overcooling degree, indoor discomfort degree and thermal autonomy, a measure of how much of the year a building maintains comfort without active systems. The contrast between the datasets was stark and, in places, counterintuitive.

The headline finding is that conventional weather datasets systematically underestimate indoor thermal discomfort in dense urban settings. Because the reference data comes from cooler rural or airport locations, simulations driven by such files paint an optimistic picture of future comfort, understating both the frequency and the intensity of overheating episodes. For a building designer, that optimism is dangerous. It can lead to undersized cooling systems, insufficient attention to shading and facade design, and a false sense of thermal resilience that evaporates during the first serious heat wave. As climate change pushes regional temperatures upward, the penalty for ignoring the urban heat island grows larger, because the extra urban warming compounds the baseline shift rather than merely adding to it.

Yet the study also delivers a more nuanced and arguably more surprising message: urban form is not simply an enemy of thermal comfort. When the researchers included the surrounding three-dimensional urban morphology in their weather generation, they found compensating effects. Neighboring buildings shade one another from direct solar radiation, and surfaces exchange longwave radiation in ways that can moderate conditions at the facade. A building in a tight urban canyon may suffer from the heat island’s warmer air, but it also receives less sun on its walls and windows than an isolated building in an open field. These interactions are nonlinear, meaning their combined effect cannot be predicted by summing individual contributions, and they can materially alter both energy use and indoor thermal conditions depending on the specific geometry of the site.

This nonlinearity is precisely why the researchers argue that urban microclimate must be treated as an integral part of building performance simulation rather than an optional refinement. The interplay between regional warming, urban heat island intensity and urban geometry produces outcomes that no single-factor analysis can anticipate. A design decision that looks prudent under a rural weather file, such as a generous window-to-wall ratio to capture daylight, may perform very differently when the same glazing faces a heat-soaked urban canyon. Conversely, dense urban form that raises local air temperatures may simultaneously deliver shading benefits that reduce cooling loads. Capturing these trade-offs requires weather data that carries the fingerprint of the actual urban environment, which is exactly what the new framework produces.

The practical implications extend well beyond Osaka. Building performance simulation underpins energy codes, green building certification, HVAC system sizing and climate adaptation planning worldwide, and all of these applications currently inherit the rural bias of standard weather files. The framework proposed by the Bavarsad team offers a workflow that practitioners can follow: take future climate projections, downscale them statistically, pass them through an urban canopy model parameterized with local morphology, and feed the resulting urbanized weather files into standard building simulation tools. The approach is deliberately compatible with existing simulation practice, using formats and tools already familiar to the industry, which lowers the barrier to adoption. It also supports climate-responsive urban design, because by varying morphological parameters, planners can test how different configurations of street width, building height and density shape both neighborhood climate and building performance before anything is built.

The broader stakes are considerable. Heat is already the deadliest weather-related hazard in many regions, and the buildings people occupy are the first line of defense between urban populations and dangerous temperatures. As the Intergovernmental Panel on Climate Change has emphasized, even modest levels of global warming translate into substantial increases in extreme heat exposure, and cities concentrate that exposure. Studies of temperature-related mortality under Paris Agreement scenarios have shown that the difference between warming targets is measured in lives, and indoor conditions during heat waves are a critical part of that equation. A simulation methodology that understates urban heat therefore does not just mispredict energy bills; it risks misinforming the very decisions that determine whether buildings shelter people or endanger them during the extreme events of the coming decades.

What makes this study resonate beyond its technical contribution is the clarity of its central lesson: the city itself is a climate machine, and pretending otherwise corrupts every downstream calculation. The researchers demonstrate that accurate representation of urban microclimate, particularly the combined effects of the urban heat island and urban geometry, is essential for reliable assessment of building performance and thermal resilience under future climate conditions. Their three-scenario framework gives the field a reusable template for separating and recombining the effects of global climate change, urban warming and urban form, and their Osaka case study shows concretely how much conventional methods miss. As cities race to retrofit existing stock and design new districts capable of withstanding a hotter century, tools like the Urban Weather Generator, coupled with downscaled climate futures, offer a way to stop designing for a countryside that the building will never experience, and start designing for the city as it truly is, and as it is becoming.

Subject of Research: Integrating urban heat island effects and urban morphology into future weather files for building performance simulation

Article Title: Integrating urban heat island effects into future weather data for building performance simulation

Article References: Bavarsad, F. S., Mohajerani, M., Tywoniak, J., & Yuan, J. (2026). Integrating urban heat island effects into future weather data for building performance simulation. Theoretical and Applied Climatology, 157(10), Article 630. https://doi.org/10.1007/s00704-026-06571-7

Image Credits: AI Generated

DOI: 10.1007/s00704-026-06571-7

Keywords: urban heat island, building performance simulation, Typical Meteorological Year, Urban Weather Generator, climate downscaling, urban morphology, overheating risk, thermal comfort, Osaka, future climate scenarios, energy demand, urban microclimate