Dr. Philip Sura
Professor Sura's current research is focused on the stochastic-dynamical understanding of extreme events in climate. Extreme events in climate (such as hurricanes, droughts, windstorms, etc.) are by definition rare, but they can have a significant impact on affected people and countryies. In non-technical terms, an extreme event is a high-impact, hard-to-predict phenomenon that is byond oru normal (Gaussian bell curve) expectations. In technical terms, an extreme event is often defined as the non-normal (non-Gaussian) tail of the data's probability density function (PDF). Understanding extremes has become an important objective in climate variability research because climate (and weather) risk assessment depends on knowing and understanding the non-Gaussian tails of PDFs.
In recent years, new tools that make use of advanced stochastic-dynamical theory have evolved to evaluate extreme events and the physics that govern these events. These tools take advantage of the non-Gaussian structure of the PDF by linking a stochastic (probabilistic) model derived from first physical principles to the observed non-Gaussianity. The detailed assessment of non-Gaussian variability in the atmosphere and the ocean is of great practical significance because it rpovides a framework to predict the probability of extreme events in the climate system.