| dc.description.abstract | This project intends to answer the question of how rising disaster losses correlate to essential climate change variables. Despite the substantial upward trend in economic losses from disaster, there is still debate over whether anthropogenic climate change has been the main driver of losses. This is due to the need to control for complex socioeconomic variables such as population, social vulnerability, economic growth effects, and more. The project will investigate the effects of temperature, precipitation, and vulnerability on disaster losses to examine how these measures have predicted the human cost of disaster. I hypothesize that climate indicators will predict disaster damages, and that these effects will vary based on social vulnerability and physical exposure. I also predict regional climate data will predict damages more accurately than global data. By illuminating the variables that best predict losses and identifying quantitative trends, this project will quantify the relative contribution from anthropogenic climate change to disaster losses and provide helpful information about the predictive power of individual climate variables. Quantitative analysis of the secondary data will be conducted and the implications of climate change in the future will be discussed, as well as a review of the literature, especially in the area of disaster attribution. The secondary data are available through NOAA, SHELDUS and NLDAS datasets. These data will be used to quantitatively study the relationship of specific climate variables to disaster losses. Correlation and regression analysis will be conducted on a county-level and global scale using Stata. | |
