Extreme heat waves in urban areas are much more likely than previously thought, according to a new modeling approach developed by researchers such as Lei Zhao, Assistant Professor at the University of Illinois Urbana-Champaign Civil and Environmental Engineering (CEE) and Alumnus Zhonghua Zheng (MS 16, PhD .) was developed 20). Her work with co-author Keith W. Oleson of the National Center for Atmospheric Research, “Large model Structure Uncertainty in Global Projections of Urban Heatwaves,” is featured in the journal. released Nature communication.

Urban heat waves (UHW) can be devastating; a 1995 heat wave in Chicago claimed more than 1,000 deaths. Last year’s heat wave on the west coast led to forest fires. Global warming is expected to increase the incidence and severity of UHWs, but when cities fully understand their risk, they can better prepare with predictions and warnings, safety warnings, and improved access to health facilities like cold centers and hospitals. Longer-term strategies include adaptation practices that help cities adapt to the warmer temperatures caused by climate change – such as highly reflective roofs and sidewalks and green infrastructure – and mitigation practices that help reduce carbon emissions – such as renewable energies.

However, in recent years, the increase in record breaking UHWs has raised concerns that the computer models used to predict them are flawed, leading to a systematic underestimation of their frequency and severity. Without accurate models, cities can dramatically misjudge their risk and prepare accordingly, putting their citizens at greater risk when the world heats up.

Zhao’s team has developed a model that closes two major gaps in urban climate modeling. First, most traditional climate models virtually completely ignore cities. Urban areas make up only 2-3 percent of the earth’s land area, so their impact on global models is negligible, but more than half of the world’s population lives in urban areas, so their impact is significant. The team’s new modeling approach addresses this by providing city-specific climate signals.

Second, due to this lack of urban representation in modern climate models, there were no global multi-model projections for the urban climate. The multi-model projections are crucial to characterize the robustness and uncertainty of the projections, which is very important for the assessment of the climate-related risks, for example the probability of climate extremes. The new model offers global multi-model projections of the local urban climate.

The paper also highlights four high stakes regions – the Great Lakes region, southern Europe, central India, and northern China – and notes that cities in these areas had dramatically lower risk probabilities using a single-model approach than using the researchers’ multi-model. model approach. For example, the researchers found that only with traditional models in the Great Lakes region was an extreme heat event expected only once in 10,000 years; with the researchers’ new modeling technique, such events could be expected every four years.

“This work underscores the critical importance of multi-model projections to accurately estimate the likelihood of extreme events that will occur in the future under climate change,” said Zhao.


Funding for this work was provided by a start-up grant from CEE in Illinois. Support for high-performance computing was provided by the National Center for Atmospheric Research, which was funded by the National Science Foundation.


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