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Projecting the Most Likely Annual Urban Heat Extremes in the Central United States

Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma and Storm Prediction Center/National Weather Service/National Oceanic and Atmospheric Administration, Norman, OK 73072, USA
Department of Geological and Atmospheric Sciences, Iowa State University, Ames, IA 50011, USA
Department of Civil, Architectural and Environmental Engineering, University of Texas at Austin, Austin, TX 78712, USA
Department of Industrial and Operations Engineering, University of Michigan, Ann Arbor, MI 48109, USA
Department of Civil and Environmental Engineering, Michigan State University, East Lansing, MI 48824, USA
Department of Civil, Construction and Environmental Engineering, Iowa State University, Ames, IA 50011, USA
Author to whom correspondence should be addressed.
Atmosphere 2019, 10(12), 727;
Received: 30 September 2019 / Revised: 13 November 2019 / Accepted: 15 November 2019 / Published: 20 November 2019
(This article belongs to the Section Meteorology)
Climate studies based on global climate models (GCMs) project a steady increase in annual average temperature and severe heat extremes in central North America during the mid-century and beyond. However, the agreement of observed trends with climate model trends varies substantially across the region. The present study focuses on two different locations: Des Moines, IA and Austin, TX. In Des Moines, annual extreme temperatures have not increased over the past three decades unlike the trend of regionally-downscaled GCM data for the Midwest, likely due to a “warming hole” over the area linked to agricultural factors. This warming hole effect is not evident for Austin over the same time period, where extreme temperatures have been higher than projected by regionally-downscaled climate (RDC) forecasts. In consideration of the deviation of such RDC extreme temperature forecasts from observations, this study statistically analyzes RDC data in conjunction with observational data to define for these two cities a 95% prediction interval of heat extreme values by 2040. The statistical model is constructed using a linear combination of RDC ensemble-member annual extreme temperature forecasts with regression coefficients for individual forecasts estimated by optimizing model results against observations over a 52-year training period.
Keywords: urban heat extremes; climate modeling; energy planning urban heat extremes; climate modeling; energy planning
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Jahn, D.E.; Gallus, W.A., Jr.; Nguyen, P.T.T.; Pan, Q.; Cetin, K.; Byon, E.; Manuel, L.; Zhou, Y.; Jahani, E. Projecting the Most Likely Annual Urban Heat Extremes in the Central United States. Atmosphere 2019, 10, 727.

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