Grant: Discovery Grants Program - Individual

Extreme value theory provides the basis for the estimation of probabilities and likely future levels associated with extreme events. These quantities are used as inputs for managerial and policy decisions to prevent or limit the damage caused by extreme negative outcomes. In this research, we develop statistical models and tools to gain a better understanding of the extreme behavior of time series in climate and environmental sciences. Focused on the extreme occurrences, we develop statistical models that can handle the complex nature of processes such as temperature, rainfall, ground-level ozone, etc. Models should exploit any knowledge that we have about such physical processes at any scale to gain a better comprehension of how the extreme behavior of these processes has changed, is changing, and is likely to change in the future. There are many other areas that require these types of statistical models, for example: oceanography, hydrology, climatology, reliability, economics, reinsurance, and finance. In short, where inadequate estimates of the frequency and size of extreme occurrences can have a devastating impact, for example: wave heights, water levels, heat waves, structural load, energy supply, insurance claims, and equity returns, respectively.