Date of Award

May 2020

Degree Type


Degree Name

Doctor of Philosophy (PhD)


Civil and Environmental Engineering


David G. Chandler


Climate Change, Extreme Events, GCM, Hazard Mapping, Heatwave, Multi-Criteria Decision-Making

Subject Categories



Heatwaves are an important type of extreme climate event and directly result in more than 130 deaths and thousands of morbidities per year across the United States. Heat waves increase demands on water and energy, particularly in urban areas, because people use more water for drinking, showering, watering, recreational purposes, and evaporative cooling units. Global temperature is increasing due to natural cycles and greenhouse gases (GHGs) emitted by humans at an alarming rate and this increase is exacerbated in urban areas due to the Urban Heat Island (UHI) effect. Accordingly, more frequent and severe heat waves in the future years are inevitable with more challenging events in urban areas.

Despite the long-standing and excessive harmful impacts of heatwaves on humankind, environment, water resources, and energy, there is no single quantitative definition for heatwaves. Heat waves have been described by several attributes and combinations that constitute various event typologies. This inconsistency in heatwave definition and measurement components across different organizations and various climates, brings many challenges for study of this extreme event.

I develop eight definitions to differentiate heatwaves and test for temporal trends in key properties of heatwaves. I define heat wave profile to show how heatwave components are changing based on different definitions concurrently over the period 1950-2016. In this study, I focus on 10 cities across the USA with different climates; Baltimore, MD, Bismarck, ND, Colorado Springs, CO, Dallas, TX, Des Moines, IA, Miami, FL, New York City, NY, Phoenix, AZ, Portland, OR, and Syracuse, NY. I find that the greatest change in heatwave season length, frequency, and timing occurred in Miami, FL while Bismarck, ND showed the highest daytime intensity during the last 7 decades. These extremes pose many hazards to humans, environment, and infrastructure.

Heat wave risk is determined based on natural hazard, population vulnerability, and exposure; whereas urban managers typically assume a spatially uniform heat wave hazard. To challenge this simplification, I present a novel analytic approach to determine the spatial distributions of several heat wave properties and associated hazards. Then I apply a Multi-criteria Decision-making tool (TOPSIS) to evaluate the total hazard posed by heat wave components and show how this perspective highlights: a) the heat wave components across the urban areas are distributed unevenly and b) the Multi-criteria Decision-making based hazard mapping approach reveals regions with compound heat wave hazards not detected by single heat wave components. Demonstration of this method in Maricopa County, Arizona USA revealed that the first heat wave occurs 40 days earlier in the eastern part of the county. In addition, the northeast part of this region experiences 12 days further extreme hot days and a 30 day longer heat wave season than other regions of the area. This approach is intended to support local government planning for heat wave adaption and mitigation strategies based on the most accurate local hazard components and characteristics.

Policy makers and managers can benefit from better understanding and quantitative prediction of future extreme events. Studies in the United States of America indicated decadal scale variations in heat wave occurrence. In this regard, Regional Climate Models (RCMs) are responsive to local meteorology and surface properties within each region. Where RCMs are absent, General Circulation Models (GCMs) are the only reliable resources for future weather predictions. However, the relatively coarse resolution of GCM outputs challenges application for regional planning. Importantly, the wide breadth of these GCM outputs poses significant challenges to determine viable actions for heat preparedness. I examine 32 models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) to determine opportunities to use contemporary GCMs to represent various heat wave components across the CONUS for the period 1950-2005. The focus of this project is to understand heat wave hazard with a multi-criteria decision-making tool and then rank the capability of various GCMs to simulate historical outcomes of multiple simultaneous heat wave components. I find that ec-earth, mpi-esm-lr, canesm2, cmcc-cm, and gfdl-esm2m models show significantly better results and fgoals-g2, gfdl-esm2g, hadgem2-cc, access1-0, and inmcm4 GCMs performed the poorest. Generally, the results show that heat wave components may increase in frequency, start earlier, or last longer over the next 8 decades even under RCP4.5 path and based on optimistic GCMs. The frequency and duration of future heat waves could increase to the point that the events are contiguous, resulting in a “heat wave season”.

Based on the GCM analysis, I explore the nexus of quantitative description and social construction of heatwaves through the lens of the various regional metrics to describe heatwaves. This assessment is targeted to guide the development of various strategies to help communities understand and prepare for heat resilience, based on local heatwave components. The findings of this study are also intended to improve local climate impact studies by providing more robust, quantitative, and reliable local heat wave predictions from contemporary models.


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