Analysis of Typhoon Wind-Rain Relationships And the Assessment of the Typhoon Climatology Rainfall QPF model Integrating Pattern Classification Indicators

• Main Authors: Yu-Jung Lin, 林佑蓉
• Other Authors: Tim Hau Lee
• Format: Others
• Language: zh-TW
• Published: 2009
• Online Access: http://ndltd.ncl.edu.tw/handle/96062438933734437298

碩士 === 國立臺灣大學 === 土木工程學研究所 === 97 === The assessment of the original typhoon climatology rainfall QPF model cannot analyze typhoons which have similar path but different rainfall pattern such as Toraji in 2001 and Haitang in 2005. Typhoon Toraji has strong atmospheric structure, powerful current lead high speed passing and concentrating rainfall through the way. Typhoon Haitang has opposite atmosphere condition, which has week current lead slow passing. The typhoon center stay at offshore Hualien induce the outer circulation extend to northern and southern Taiwan. Haitang’s rainfall almost concentrated on Kaoping river basin upstream, and less in middle Taiwan. This two typhoon rainfall pattern shows: if similar path typhoon have different structure, the distribution pattern of rainfall would not in the same. The climatology use all similar path typhoon to compute the rainfall average but different case might be has big variation in QPF model. This research use historical wind and rainfall observation which has similar path to establish the classification indicators that can analysis the wind and rainfall pattern. Include the historical typhoon which has analogous indicators to compute the climatology average rainfall but exclude the different pattern historical typhoon. Data using process as follows: (1) Observe the interaction between typhoon and Taiwan topography, also the wind and rainfall distribution, then use historical wind and rainfall observation to establish the classification indicators. (2) Decide the threshold of similarity and difference, and use PCA method to realize the relation between the indicators. Use type 2 and type 3 typhoon path defined as CWB to be database. (3) Apply the indicators to the predicted area then check out the application of the all predicted region. (4) Improve the Climatology Rainfall QPF, then compute the error square of estimate and the coefficient of variation which is compared with original climatology rainfall QPF method. This research confirms that error variance of classification climatology might higher than traditional climatology in special rainfall pattern of typhoon begin from lag time is 1; when predict lag time increase, it will not better than traditional climatology. On the other hand, error variance in typical rainfall pattern of typhoon is better than it in special rainfall pattern cases; for 8 cases of rainfall: When lag time is 0 in northern and northeastern Taiwan, the error square of estimate calculated by classification climatology is less than traditional climatology. When lag time is 1 to 3, the error square of estimate is continued small but the error square of estimate is equal to traditional climatology in middle, southern and eastern Taiwan. In this few cases, classification climatology only can find the similar rainfall pattern cases in northern Taiwan area. The variance of rainfall pattern in other areas is like the traditional climatology. In the future, if we have more typhoon cases, this classification climatology will find all rainfall areas are almost the same with the true rainfall pattern and predict of rainfall will better than the traditional climatology in lag time is 1 to 3.