English  |  正體中文  |  简体中文  |  Items with full text/Total items : 26994/38795
Visitors : 2389680      Online Users : 47
RC Version 4.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Adv. Search
LoginUploadHelpAboutAdminister

Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/39965

Title: A study of typhoon intensity change by data mining technique
Authors: Ho, C.-R.;Cheng, Y.-H.;Lin, C.-Y.;Kuo, N.-J.;Huang, S.-J.
Contributors: 國立臺灣海洋大學:海洋環境資訊學系
Date: 2012-04
Issue Date: 2017-01-11T02:21:56Z
Publisher: EGU General Assembly 2012
Abstract: Abstract: The western North Pacific is the area of the most frequent typhoons strikes over the world. Each year, about 6-10 typhoons of Category 4 or 5 in the Saffir-Simpson hurricane scale emerging in the western North Pacific. These severe typhoons not only bring drastic impact for the coastal area through powerful winds and torrential rain, but also stir the ocean surface and cause upper ocean response along its passage. The ocean response plays one of the most important roles in air-sea interaction. The primary purpose of this study is employing a data mining technique in retrieving passible influence parameters on typhoon intensity change. The possible influence parameters include sea surface temperature, atmospheric water vapour, rain rate, sea surface height anomaly, and air-sea temperature difference. The sea surface temperature data is derived from the Microwave Imager (TMI) and the Advanced Microwave Scanning Radiometer. The atmospheric water vapour and rain rate data are from TMI. The sea surface height anomaly is a blended data accessed from satellite altimetry, and the air temperature data is from National Centre for Environmental Prediction. Totally 14 Category-5 typhoons occurred between 2003 and 2007 in the western North Pacific are analyzed in this study, which decision tree algorithm is applied as the data mining technique. The results show that air-sea temperature difference and sea surface temperature intensify the typhoon most. Due to higher sea surface temperature can provide more heat potential to the atmosphere, and the larger temperature difference between sea and air can also provide more heat energy to the atmosphere, once a typhoon passes over the ocean where sea surface temperature is higher than air temperature, about 88% of typhoon intensity is enhanced. This data mining model is further validated by using the data of super typhoon JANGMI (2008). It shows 82.3% of accuracy prediction and 85.7% for precision.
URI: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/39965
Appears in Collections:[海洋環境資訊系] 演講及研討會

Files in This Item:

File Description SizeFormat
index.html0KbHTML48View/Open


All items in NTOUR are protected by copyright, with all rights reserved.

 


著作權政策宣告: 本網站之內容為國立臺灣海洋大學所收錄之機構典藏,無償提供學術研究與公眾教育等公益性使用,請合理使用本網站之內容,以尊重著作權人之權益。
網站維護: 海大圖資處 圖書系統組
DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback