Quantifying Climate Change Impacts on Infrastructure: Three Case Studies

Over the coming century, climate change has the potential to impact infrastructure, particularly in population-dense areas that depend on transportation and built environments. Many of these impacts may occur via changes in the frequency and magnitude of extremes: high and low temperature, precipitation, coastal flooding, and storm events. High temperatures, for example, accelerate the deterioration of some types of infrastructure materials; affect aircraft performance; require increased refrigeration and cooling for ports and terminals; and shorten construction times for work crews. Heavy precipitation events affect bridge scour, culvert performance, roadways, and transportation safety, impairing operations and travel or bringing them to a standstill. Stronger hurricanes and increased risk of coastal flooding due to storm surges and sea level rise can lead to temporary and permanent flooding of transportation- and built infrastructure as well as residential areas.

We describe the development of, and projected future changes in, a collection of infrastructure-relevant climate indices for three different locations within the United States: the Mobile Bay region in the Southeastern U.S., the city of Cambridge, MA in the Northeastern U.S., and the city of Austin, TX in the Southern Great Plains. The indices are based on mean and extreme temperature, precipitation, humidity, and combinations thereof, and vary depending on the region. Historical trends are calculated from long-term weather stations, while projected future changes are based on GCM simulations corresponding to a lower and a higher scenario, statistically downscaled to the same individual station records using the ARRM model.

We find that all three locations are likely to be affected by an increase in average temperatures as well as a greater number of extremely hot days and heat waves with increasing risk under a higher scenario as compared to a lower. For precipitation, projected changes differ based on both the nature of the indices relevant to each region as well as the spatially inhomogeneous rate of change in mean and extreme precipitation. These results highlight the importance of local knowledge and flexibility in identifying thresholds and potential indices relevant to quantifying the impacts of climate change at the regional scale.