| dc.description.abstract | This dissertation investigates extreme temperature events, their drivers, and their impact on society across three main sections. As the climate warms, understanding these events and their consequences becomes increasingly important for developing adaptation strategies and informing policy decisions.
In the first section, the dissertation examines the role of global warming and the internal variability of climate systems in extreme heat and humidity events using a large ensemble of climate models. It is found that extreme heat and humidity events significantly elevate between 1.5°C and 2.0°C of global warming. The El-Niño Southern Oscillation is the largest driver of extreme heat and humidity events on a smaller scale, while global warming becomes more significant when looking at larger regions. With 3°C of warming, 10% of the population will experience extreme heat conditions, and regions with lower GDP will be more vulnerable to extreme heat events. This highlights the need for targeted adaptation strategies in vulnerable regions.
The second section evaluates the impact of climate change on Texas' energy sector, focusing on the Electric Reliability Council of Texas (ERCOT), which controls the state's electric power. An empirical model for estimating power demand based on temperature is developed, accounting for the insufficiency of using only the last decade of temperature data for calculating seasonal power demand. The model reveals a 17% and 19% chance of power demand exceeding extreme peak-load scenarios in summer and winter, respectively. In the Texas winter storm Uri, the study concludes that power demand exceeded ERCOT's extreme peak load scenario by 15 GW or 22%, emphasizing the need for improved demand forecasting and infrastructure resilience.
The final section investigates the impact of climate change on temperature-related deaths in the United States. A temperature-mortality relationship for 106 cities is established, and a model is developed to approximate the role of adaptation by comparing cities with different climates. Using high-resolution climate model outputs, future temperature-related deaths are projected under various adaptation scenarios. At 3°C of global average warming, temperature-related deaths will reach 175,000 per year, a significant increase from the current 37,000 deaths. Adaptation can minimize this increase by 37,000 per year, with a notable northward shift in temperature-related deaths. This underscores the importance of proactive adaptation measures to minimize the human cost of climate change.
This dissertation serves as a capstone project for climate informatics, which combines climate data with data from other sectors to investigate the climate impact. Its findings contribute to a deeper understanding of extreme temperature events and their consequences, offering insights for effective adaptation strategies and policymaking in a warmer climate. | |
