To explore this idea, University of Delaware researcher Jing Gao, assistant professor in the College of Earth, Ocean and Environment and a resident faculty member in the Data Science Institute, and colleague Melissa Bukovsky, associate professor in the Haub School of Environment and Natural Resources at the University of Wyoming, investigated how changes in urban land and population will affect future populations’ exposures to weather extremes under climate conditions at the end of the 21st century. 

The researchers looked at urban areas across the continental United States, including cities large and small, with various development densities and in different climate regions. They used a data-driven model developed by Gao to predict how urban areas across the country will grow by 2100, based on development trends observed over the past 40 years. The research team considered how these urban land changes might affect weather extremes like heat waves, cold waves, heavy rainfalls and severe thunderstorms. They then analyzed how many people would be exposed to these extremes under different climate and urban development conditions at the end of the century.

The research team’s simulations showed that at the end of the 21st century, how a city is laid out or organized spatially, often called an urban land pattern, has the potential to reduce population exposures to future weather extremes, even for heat waves under very high urban expansion rates. Further, how the urban landscape is designed — meaning how buildings are clustered or dispersed and how they fit into the surrounding environment — seem to matter more than simply the size of a city. This is true even while climate change is increasing population exposures.

These findings apply to all cities, from large metropolitan areas like New York City to smaller towns in more rural contexts, such as Newark, Delaware.

“Regardless of the size of a city, well planned urban land patterns can reduce population exposures to weather extremes,” Gao said. “In other words, cities large and small can reduce their risks caused by weather extremes by better arranging their land developments.” 

These findings differ from current common perceptions. For example, existing literature in this area has almost exclusively focused on limiting the amount of urban land development, Gao said.

In contrast, the new findings from this research encourage researchers and practitioners from a wide range of related fields to reconsider how cities are designed and built so that they can be in harmony with their regional natural surroundings and more resilient to potential climate risks over the long run. 

Gao likened the effects of climate change and urban land patterns on extreme weather risks to the effects of a person’s diet and activity level on their risk for health problems. Properly designed urban land patterns, she said, are like physical exercises that work to counteract poor dietary choices, contributing to a reduced risk for disease, while helping a person become more fit in general.

“Carefully designed urban land patterns cannot completely erase increased population exposures to weather extremes resulting from climate change, but it can generate a meaningful reduction of the increase in risks,” Gao said. 

And the cost to start is small, Gao said. No extravagant measure, such as leveling and rebuilding a large area at once, is required. 

“Instead, when building new and renovating existing parts of a city, we should adjust our mindset to consider how the new development and renovation will change the way the city as a whole situates in its natural surroundings, and how the city and its surrounds can be one integrated human-environment system at large scales over the long run,” Gao said. “The key is to start adjusting how we think about development now.”

Next steps in the work

The researchers are working to identify specific characteristics about the spatial arrangement of a city that can make it more — or less — resilient to future weather extremes. Identifying these patterns can help guide development that is more sustainable in the face of increasing instances of extreme weather. Through their efforts, the research team hopes to provide actionable suggestions for how to design and build urban areas that reduce their residents’ exposures to weather extremes in the long run.

Importantly, the researchers emphasized that these characteristics will likely vary from region to region, now and as climate changes. For instance, what works in arid Phoenix, Arizona, will probably differ from what will work in humid New Orleans, Louisiana. Likewise, what might work today for a city could differ from what will work in the future, as climate conditions evolve.

“Eventually, we want our work to be directly useful to urban design and planning efforts, offering insights and tools for decision makers to influence long-term social and environmental well-being at scale,” Bukovsky said. “First, though, we need to identify what development patterns can improve various cities’ long-term climate resilience. We will continue collaborating in the future.”

Gao and Bukovsky recently reported their findings in a Nature Communications paper. The team’s modeling efforts and resulting datasets are publicly available online for those interested in conducting other human-environment investigations.

About the researchers

Jing Gao is an assistant professor of geospatial data science in the College of Earth, Ocean and Environment and a resident faculty member in the Data Science Institute at the University of Delaware. Gao is an author of the Fifth National Climate Assessment (NCA5) and a recent recipient of a Faculty Early Career Development Program (CAREER) award from the National Science Foundation for research on long-term large-scale urban climate resilience. Her work developing a new data-science-based urban land change modeling framework using machine learning methods was selected as a 2020 Top-50 article in Earth, Environmental and Planetary Sciences by Nature Communications.

Melissa Bukovsky is an associate professor in the Haub School of Environment and Natural Resources, a Derecho professor in the School of Computing, and the director of the CoLABorative for Intersectoral Modeling of the Earth System (CLIMES) at the University of Wyoming, following over a decade of a research scientist career at the National Center for Atmospheric Research (NCAR). CLIMES is a new NSF EPSCoR Track-1 center through the “Wyoming Anticipating Climate Transitions” (WyACT) project to build research and education capacities for holistically understanding environmental futures through computation-based multidisciplinary team science. Bukovsky is a recognized expert in regional climate modeling and climate change impacts across North America.