| dc.description.abstract | Climate change is creating more frequent and more severe weather events across the world and the reality is that this trend will continue for the foreseeable future. As a result, society must prepare for these impacts and adapt accordingly while recognizing that the circumstances will vary across geographical regions. In order to make more effective adaptation investment decisions, the future impacts of these events must be understood. Databases on loss and damage direct costs associated with individual severe weather events have been recorded for decades and are publicly available online, presenting a rich resource for use in predictive modeling of future loss and damage. By developing a model to simulate these impacts, it reduces the burden to access information to help in adaptation investment decision making, particularly important for rural communities and locations of disproportionately high socially disadvantaged populations, who are typically resource-constrained. The focus of this dissertation is to leverage this data in concert with utilizing future climate change pathways and their associated outcomes, as well as representing how, in addition to direct impacts, non-economic and indirect damages can be considered. Such a modeling effort can create a more complete evaluation of the business case for allocating resources to strategies designed to mitigate extreme weather risk, which can be utilized in traditional benefit-cost and return-on-investment methods. The results of this research also set the stage for opportunities to further enhance modeling efforts that can leverage improvements in loss and damage accounting achieved when utilizing smaller spatial resolution. | |
