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Please use this identifier to cite or link to this item: http://hdl.handle.net/2031/4659

Title: Ensemble forecasting of tropical cyclone motion-combining environment and vortex perturbations
Other Titles: Re dai qi xuan yi dong de ji he yu bao : jie he huan liu yu wo xuan rao dong
熱帶氣旋移動的集合預報 : 結合環流與渦旋擾動
Authors: Li, Kwun Kau (李冠球)
Department: Dept. of Physics and Materials Science
Degree: Master of Philosophy
Issue Date: 2004
Publisher: City University of Hong Kong
Subjects: Cyclone forecasting
Cyclones -- Tropics
Numerical weather forecasting
Perturbation (Quantum dynamics)
Notes: CityU Call Number: QC942.L53 2004
Includes bibliographical references (leaves 149-155)
Thesis (M.Phil.)--City University of Hong Kong, 2004
xvii, 155 leaves : ill. ; 30 cm.
Type: Thesis
Abstract: The numerical weather prediction (NWP) model for tropical cyclone (TC) motion forecasting provides a single forecast. However, small errors of an initial analysis can cause a forecast to deviate far away from the real state. These errors can come from the environmental flow or the vortex structure. In previous research, either isolated environment or vortex perturbations were simulated as the initial errors to be added on the analysis condition. The ensemble forecasts generated from these different perturbed conditions provide more dynamical information for TC motion. This study is a continuation of a previous investigation into the applicability of the ensemble forecasting technique in predicting TC motion. In the real atmosphere, the environment and vortex interact with each other and so should their perturbations. The interaction uncertainties can change the final TC motion. Therefore, the combined environment and vortex perturbations are introduced in the present research to simulate these interaction uncertainties. In this study, the simple barotropic model is used to forecast the ensemble TC tracks under different perturbed conditions. Different combined perturbation methodologies are designed to provide different perturbation distributions and errorgrowth processes. The perturbation schemes are mainly based on the breeding of growing modes (BGM) and lagged average forecast (LAF) methods. Sixty-six cases from the Tropical Cyclone Motion Experiment TCM90 are employed to compare the performance of the combined perturbation and the individual environment and vortex perturbations using several statistical measures including relative skill score, spread of ensemble and the forecast error. Verification of the ensemble forecast tracks generally shows that the ensemble mean forecasts of the combined perturbation have higher skill than those of the individual perturbations. It indicates that combining the environment and vortex perturbations can provide more accurate vortex structure to improve track forecasts. In some case studies, the combined perturbation also provides smaller spreads of the ensemble, which increases the predictability when compared with individual perturbations. Besides examining the performance of the combined and individual perturbations, the different combined perturbation schemes are also compared with each other. The combined perturbations are mainly divided into two error-growth processes. One scheme [BGMC(1)] generates the environment and vortex perturbations separately during the error-growth period and combines these perturbations at the initial forecast time. Two other schemes [BGMC(2) and LAFC] combine these two perturbations during the error-growth period. It was found that different combined perturbations could provide different forecast skill under different synoptic conditions and vortex structures. The separated error-growth generation BGMC(1) achieves better ensemble mean forecast than the control under the transition synoptic region. In some case studies, the combined error-growth generation BGMC(2) provides various forecast scenarios even in a stable dominant subtropical ridge. Therefore, it is valuable to study these different combined perturbation systems for further understanding of TC motion dynamics in the different sensitive atmospheric conditions.
Online Catalog Link: http://lib.cityu.edu.hk/record=b1871308
Appears in Collections:AP - Master of Philosophy

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