Uncertainties and Limitations in Simulating Tropical Cyclones

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The thesis work was in two major parts: development and testing of a new approach to detecting and <br>tracking tropical cyclones in climate models; and application of an extreme value statistical approach to <br>enable assessment of changes in weather extremes from climate models. <br>The tracking algorithm applied a creative phase-space approach to differentiate between modeled tropical <br>cyclones and their mid-latitude cousins. A feature here was the careful attention to sensitivity to choice of <br>selection parameters, which is considerable. The major finding was that the changes over time were <br>relatively insensitive to these details. This new approach will improve and add confidence to future <br>assessments of climate impacts on hurricanes. <br>The extremes approach utilized the Generalized Pareto Distribution (one of the standard approaches to <br>statistics of extremes) applied to present and future hurricane distributions as modeled by a regional <br>climate model, then applied the changes to current observations to extract the changes in the extremes. <br>Since climate models cannot resolve these extremes directly, this provides an excellent method of <br>determining weather extremes in general. This is of considerable societal importance as we are most <br>vulnerable to such extremes and knowledge of their changes enables improved planning and adaptation <br>strategies.