This study explores the sensitivity of high-resolution mesoscale simulations of urban heat island (UHI) in the Chicago metropolitan area (CMA) and its environs to urban physical parameterizations, with emphasis on the role of lake breeze. A series of climate downscaling experiments were conducted using the urban-Weather Research and Forecasting (uWRF) model at 1-km horizontal resolution for a relatively warm period with a strong lake breeze. The study employed best available morphological data sets, selection of appropriate urban parameters, and estimates of anthropogenic heating sources for the CMA. Several urban parameterization schemes were then evaluated using these parameter values. The study also examined (1) the impacts of land data assimilation for initialization of the mesoscale model, (2) the role of urbanization on UHI and lake breeze, and (3) the effects of sub-grid scale land-cover variability on urban meteorological predictions. Comparisons of temperature and wind simulations with station observations and Moderate Resolution Imaging Spectroradiometer satellite data in the CMA showed that uWRF, with appropriate selection of urban parameter values, was able to reproduce the measured near-surface temperature and wind speeds reasonably well. In particular, the model was able to capture the observed spatial variation of 2-m near-surface temperatures at night, when the UHI effect was pronounced. Results showed that inclusion of sub-grid scale variability of land-use and initializing models with more accurate land surface data can yield improved simulations of near-surface temperatures and wind speeds, particularly in the context of simulating the extent and spatial heterogeneity of UHI effects.
Bibliographical noteFunding Information:
The research work is supported by National Science Foundation (NSF) grant number: AGS 0934592, USDA-NIFA Agriculture and Food Research Initiative (awards 2015-67003-23508 and 2015-67003-23460), the Notre Dame Environmental Change Initiative, the Center for Sustainable Energy, and the City of Chicago. Simulations were performed with NCAR Yellowstone and the NCSA Blue Waters GLCPC computing grants for supercomputing facilities and the Center for Research Computing at the University of Notre Dame. Authors also acknowledge Dr. Dan Li for help with sub-grid scale land-use variability implementation and Zachariah Silver for processing raw station data sets.
© 2016 The Authors. International Journal of Climatology published by John Wiley & Sons Ltd on behalf of the Royal Meteorological Society.
Copyright 2017 Elsevier B.V., All rights reserved.
- lake breeze
- land data assimilation
- mesoscale modeling
- sub-grid scale land-use variability
- urban heat island
- urban meteorology