Uncertainties and Limitations in Simulating Tropical Cyclones

This two-pronged research paper details a new approach to detecting and tracking extreme weather in climate models as well as applying an extreme-value statistical model to facilitate modeling assessment of possible changes in severe weather patterns.

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

Nominated by the Georgia Univesity of Technology for a Springer Theses Prize This work investigates how tropical cyclone intensity will change over the next 50 years - a question of high interest to industrial and governmental communities New approach to asses weather extremes in climate models and current observations Includes supplementary material: sn.pub/extras

Klappentext

This theses is presented in two parts: development and testing of a new approach to detecting and tracking tropical cyclones in climate models; and application of an extreme value statistical approach to enable assessment of changes in weather extremes from climate models. The tracking algorithm applied a creative phase-space approach to differentiate between modeled tropical cyclones and their mid-latitude cousins. Special attention was paid to the considerable sensitivity of parameters. One major finding was that changes over time were relatively insensitive. This new approach will improve and add confidence to future assessments of climate impacts on hurricanes.
The Extremes Approach utilized the Generalized Pareto Distribution, one of the standard approaches to statistics of extremes. This method was applied to present and future hurricane distributions as modeled by a regional climate model. The results have been compared with current observations on changes in weather extremes. The author came to the conclusion that the Extremes Approach provides an excellent method of determining weather extremes, whereas it is still difficult to directly resolve these extremes using climate models. The results of this thesis are of considerable societal importance: Detailed knowledge about hurricane characteristics and their progression enable decision-takers to plan and adapt evacuation strategies.

Inhalt
Introduction.- Tropical cyclone detection and tracking method.- Simulated tropical cyclone climatology in the tropical channel experiment.- North Atlantic hurricane climate change experiment.- Statistical modeling of tropical cyclone intensity.- Concluding remarks.