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Statistical Prediction of Tropical Cyclone Intensity Using Dynamical and Thermodynamical Inner-Core Parameters Derived from Hwrf Analysis and Forecasts

A new multiple linear regression model for short range tropical cyclone intensity prediction is developed. Four new dynamical and thermodynamical predictors based on HWRF output are considered: (1) the horizontal advection of relative angular momentum, (2) energy exchange from the divergent to the rotational kinetic energy (Psi-Chi interactions), (3) the conversion of shear vorticity to curvature vorticity, and (4) the vertical differential of heating in the complete potential vorticity equation. Predictors were calculated using Hurricane Research Weather and Forecast (HWRF) model initial fields. Each predictor was determined to exhibit a statistically significant relationship with 12 hour intensity change in tropical cyclones by an F-test. The predictors were then used as the basis for a multiple linear regression model, following the methodology of the operational Statistical Hurricane Intensity Prediction Scheme (SHIPS). Four additional predictors, intended to represent basic storm information and environmental conditions, were included in the development of a second model. Retrospective forecasts of hurricanes in 2004, 2005, and 2006 were created for both models, and compared to operational SHIPS and HWRF forecasts. Despite relying on HWRF fields for the calculation of predictors, the new model produces better forecasts than HWRF for short term (less than 48-hr) forecasts. Additional methods were developed to extend forecasts beyond 48 hours. This resulted in a systematic improvement of HWRF forecasts. It is proposed that the new model could be used operationally as a new version of the "early" HWRF. / A Thesis submitted to the Department of Earth, Ocean, and Atmospheric Science in
partial fulfillment of the requirements for the degree of Master of Science. / Degree Awarded: Summer Semester, 2011. / Date of Defense: April 27, 2011. / Inner-Core, Hurricanes, Statistical Hurricane Intensity Prediction, Tropical Cyclone Intensity, Tropical Cyclones, Multiple Linear Regression, Diagnostics / Includes bibliographical references. / T.N. Krishnamurti Co-, Professor Directing Thesis; Paul Ruscher Co-, Professor Directing Thesis; Vasu Misra, Committee Member; Robert Hart, Committee Member.

Identiferoai:union.ndltd.org:fsu.edu/oai:fsu.digital.flvc.org:fsu_168730
ContributorsZelinsky, David A. (authoraut), Co-, T.N. Krishnamurti (professor directing thesis), Co-, Paul Ruscher (professor directing thesis), Misra, Vasu (committee member), Hart, Robert (committee member), Department of Earth, Ocean and Atmospheric Sciences (degree granting department), Florida State University (degree granting institution)
PublisherFlorida State University
Source SetsFlorida State University
LanguageEnglish, English
Detected LanguageEnglish
TypeText, text
Format1 online resource, computer, application/pdf

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