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Understanding and Forecasting Tropical Cyclone Intensity Change with the Typhoon Intensity Prediction Scheme (TIPS)

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  • 1 Department of Atmospheric Science, Colorado State University, Fort Collins, Colorado
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Abstract

A multiple regression scheme with tropical cyclone intensity change as the dependent variable has been developed. The new scheme is titled the Typhoon Intensity Prediction Scheme (TIPS) and is similar to one used operationally at the National Hurricane Center. However, TIPS contains two major differences: it is developed for the western North Pacific Ocean, and utilizes digitized satellite data; the first time such satellite information has been combined with other predictors in a tropical cyclone multiple regression scheme. It is shown that the satellite data contains vital information that distinguishes between fast and slow developing tropical cyclones. The importance of other predictors (such as wind shear, persistence, climatology, and an empirical formula dependent on sea surface temperature) to intensity change are also clarified in the statistical analysis. A normalization technique reveals threshold values useful to forecasters. It is shown that TIPS may be competitive with the Joint Typhoon Warning Center in forecasting tropical cyclone intensity change.

* Current affiliation: Department of Physics, Atmospheric Sciences, and General Science, Jackson State University, Jackson, Mississippi

Corresponding author address: Dr. Patrick J. Fitzpatrick, Department of Physics, Atmos. Sciences and General Science, Jackson State University, P.O. Box 17660, Jackson, MS 39217-0460.

Email: patrick@stallion.jsums.edu

Abstract

A multiple regression scheme with tropical cyclone intensity change as the dependent variable has been developed. The new scheme is titled the Typhoon Intensity Prediction Scheme (TIPS) and is similar to one used operationally at the National Hurricane Center. However, TIPS contains two major differences: it is developed for the western North Pacific Ocean, and utilizes digitized satellite data; the first time such satellite information has been combined with other predictors in a tropical cyclone multiple regression scheme. It is shown that the satellite data contains vital information that distinguishes between fast and slow developing tropical cyclones. The importance of other predictors (such as wind shear, persistence, climatology, and an empirical formula dependent on sea surface temperature) to intensity change are also clarified in the statistical analysis. A normalization technique reveals threshold values useful to forecasters. It is shown that TIPS may be competitive with the Joint Typhoon Warning Center in forecasting tropical cyclone intensity change.

* Current affiliation: Department of Physics, Atmospheric Sciences, and General Science, Jackson State University, Jackson, Mississippi

Corresponding author address: Dr. Patrick J. Fitzpatrick, Department of Physics, Atmos. Sciences and General Science, Jackson State University, P.O. Box 17660, Jackson, MS 39217-0460.

Email: patrick@stallion.jsums.edu

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