Our group pursues research questions related to the causes, impacts, and potential for mitigation of urban heat islands.

As part of an NSF Biocomplexity project (see FUSE) we have developed a suite of mobile sensors that acquire and log temperature, humidity, and GPS location data at 5-second intervals. The sensors are all fast response high accuracy sensors, mounted on masts that mount on car-windows. The sensors themselves acquire data at a height of approximately 2 m above the road surface. We have developed software that automatically filters and combines the resulting data streams for easy display in a Geographical Information System. We have been linking these data with high resolution data related to land use, building type/density, road type/density, vegetative cover, albedo, and anthropogenic heating. The end result is a capability to map the Urban Heat Island and quantify the relative role of each of the contributing factors.

Also, as part of the NSF-funded FUSE project we are looking at the feedback mechanisms in the urban climate system. Specifically, during episodes of extreme heat or poor air quality it is hypothesized that individuals modify their behavior - either in response to their own perception of the episode, or in response to a public advisory. The FUSE project is concerned with understanding the potential for this behavior modification to impact the heat or air quality episode. To address these questions we are conducting phone surveys during episodes. The survey data then feed into our integrated modeling effort that includes waste heat and pollutants released from energy consuming activities and the interaction between photochemistry and local meteorology.

As part of an EPA-funded effort we developed an Urban Heat Island Mitigation Impact Screening Tool (MIST) which is used by public officials to gain an initial assessment of the potential for mitigation strategies such as high albedo surfaces and increased urban vegetative cover to reduce urban air tempertures, lower building energy consumption, and improve air quality. While MIST is based on a number of very detailed atmospheric model simulations we recommend that it be used in the initial stages of planning only, with subsequent location-specific modeling to optimize the use of mitigation strategies.