Multi-scale Study of Chicago Heat Island and the Impacts of Climate Change

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Monday, 3 February 2014: 5:15 PM
Room C212 (The Georgia World Congress Center )
Patrick Conry, University of Notre Dame, South Bend, IN; and A. Sharma, M. Potosnak, H. J. S. Fernando, and J. Hellmann
Manuscript (986.6 kB)

Handout (2.4 MB)

Large cities such as Chicago experience a particularly acute form of local microclimate change known as the urban heat island (UHI). The UHI is characterized by elevated temperatures of urban environments in comparison to adjoining sub-urban and rural areas. Regional or global climate change can further exacerbate UHI's negative effects on human health, air quality, and energy consumption. Chicago's UHI encompasses multiple scales, which need to be studied to evaluate, monitor, and solve the problems caused by the combination of local and background climate change. Observations of limited records are difficult to use in this regard, given the difficulty of separating various climatic contributions to an observation. Numerical models are helpful in this regard, as they allow controlled computations by changing a particular set of variables while keeping others unchanged. The bane, however, is that none of the available models encompass all the relevant scales. We have attempted a comprehensive multi-scale approach to study Chicago's UHI, considering contributions of local land use and global climate change. The coupling of climate, mesoscale, and micro-scale models has allowed for a downscaling procedure from regional to city to neighborhood scales. The Weather Research and Forecasting (WRF) Model captures the mesoscale behavior of UHI, and output from WRF serves as the input to a micro-scale ENVI-met model, which provides finer resolution results of UHI within a representative Chicago neighborhood. Results of both models are compared with observational data from existing weather stations in the region, and a field experiment conducted in July and August 2013 at DePaul University provides further high resolution data.