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研究生:黃思涵
研究生(外文):Huang, Si-Han
論文名稱:從波高與水位聯合發生機率評估颱風對海岸衝擊的強度
論文名稱(外文):Intensity Classification of Typhoon Impacts to Coasts Based on the Joint Effect of Tide Level and Wave Height
指導教授:蔡政翰蔡政翰引用關係董東璟董東璟引用關係
指導教授(外文):Tsai, Cheng-HanDoong, Dong-Jiing
口試委員:董東璟蔡仁智蔡政翰
口試委員(外文):Doong, Dong-JiingTsai, Jen-ChihTsai, Cheng-Han
口試日期:2016-06-14
學位類別:碩士
校院名稱:國立臺灣海洋大學
系所名稱:海洋環境資訊系
學門:自然科學學門
學類:海洋科學學類
論文種類:學術論文
論文出版年:2016
畢業學年度:104
語文別:中文
論文頁數:84
中文關鍵詞:聯合機率耦合函數複合極值分布颱風強度
外文關鍵詞:Joint probabilityCopulaCompound Extreme Value DistributionTyphoon Intensity
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現行颱風強度等級主要是依據風速來定義,但此方法不適宜描述颱風對海岸的衝擊,因此本文擬重新定義颱風強度,提出一個衡量對海岸衝擊程度的颱風強度新定義。由於海岸衝擊主要受波浪和水位(含暴潮)影響,因此,本文研究波高與水位聯合發生機率,以作為新颱風強度定義的依據。

本文採用耦合(Copula)函數及複合極值分布(Compound Extreme Value Distribution , CEVD)方法來計算波高與水位聯合發生機率,並與傳統方法比較。耦合函數可以表現兩變數間的相關性,複合極值分布是考量颱風發生頻率,用以解決資料不足問題。選取颱風資料時,本文先對颱風期間提出了新的決定方法,該方法同時考慮了海域背景波高與颱風湧浪影響,分析結果評估可以決定更合理的颱風期間,取用新定義之颱風期間資料進行分析,可獲取更高可信度的結果。

本文分別採用颱風最大波選取法(Typhoon Extreme Value Culling Method, TEVC)及波高過閥值選取法(Wave Height Threshold Culling Method, WHTC)來挑選分析資料,其中,颱風極值法由於資料過少,需搭配資料繁衍技術擴充研究資料。分析結果顯示,最大波資料選取法和波高過閥值資料選取法對聯合發生機率所得結果差異不大,但波高過閥值選取法的閥值對結果較為敏感,因此建議採用最大波資料選取法搭配繁衍技術來進行聯合機率分析。而複合極值分布方法分析所得各重現期結果較耦合函數分析所得為小,但在分析高重現期結果與傳統方法相近,為本文所建議採用,事實上,複合極值分布理論亦包含了耦合函數觀念在內。

本文根據波高與水位聯合發生的重現期來重新定義颱風強度,將聯合重現期10年以下的颱風定義為輕微(Slight)衝擊颱風,簡稱SL;將聯合重現期10-25年的颱風定義為中等(Moderate Impact)衝擊颱風,簡稱MO;重現期25-50年間的颱風定義為重大(Severe Impact)衝擊颱風,簡稱SE;而重現期大於50年者稱之為嚴重衝擊颱風(Destructive Impact),簡稱DI。重新分類結果顯示大部分颱風均屬對海岸輕微影響颱風(SL),佔95%以上,幾個對海岸衝擊大的颱風(約佔總數1~2%)經比對,與實際海岸受災情形大致符合,顯示本方法可合理判定對海岸可能產生重大衝擊的颱風,未來可用於颱風前之預測。

The typhoon strength scales used by the Center Weather Bureau is based solely on the wind speed. However, this intensity scale may not be sufficient in describing typhoon impact on the Taiwan coasts. This study analyzed observed data from the Taiwan coasts to define typhoon impact, according to extreme climate factors. This new strength definition can help prevent the destruction of coastal structure and coastal disaster.

Copula function and Compound Extreme Value Distribution (CEVD) were used in this study to calculate the joint probability of significant wave height and water level. Comparing with the traditional method, the copula function can quantify the correlation between different variables. On the other hand, the Compound Extreme Value Distribution solves the problem of shortage in samples by the use of the typhoon occurrence frequency. This study purposed a new definition for the destructive time period by typhoons for a coast with considerations of background wave height and swell simultaneously.

This study employed Typhoon Extreme Value Culling Method (TEVC) and Wave Height Threshold Culling Method (WHTC) to select data for our analysis. The data selected by TEVC needed to be multiplied by simulations due to the lack of samples. The joint probabilities of wave height and water level obtained by the TEVC as well as WHTC are very close. It was found that the result of WHTC is more sensitive to the threshold of wave height. The return period calculated by CEVD was smaller than copula, while the return period calculated by CEVD is similar to that of the traditional method. This study showed that CEVD is more suitable than WHTC.

Lastly, through the hydrologic conditions, we classified and defined typhoon strength into four types: Slight (SL), Moderate Impact (MO), Severe Impact (SE) and Destructive Impact (DI). This new definition can reflect the sea-state during the typhoon period, and much suitable to describe the impact on the coast. In the past 15 years, only 10% of typhoons had the moderate impact strength and 50% of them CWB have issued typhoon warnings. There were 2% of the typhoon which CWB did not issued any warnings, because they were still far away from Taiwan, but their swells were strong enough to cause severe impacts equivalent to typhoons with a 50 years return period. The results showed our method can reasonably determines how severe the impact of the typhoon is, and it can also be used to predict impact strength before the arrival of typhoons.

摘要 I
Abstract II
謝辭 III
目次 V
圖次 VII
表次 IX
第一章 前言 1
1-1 研究背景 1
1-2 前人研究 2
1-3 研究目的與方法 3
1-4 論文架構 4
第二章 颱風期間波高與水位分布 5
2-1 波高分布的前人研究 5
2-2 水位分布的前人研究 5
2-3 本文所選用的套配模型 6
第三章 聯合機率分布理論基礎 8
3-1 傳統聯合機率分析方法 8
3-2 耦合函數(Copula function) 8
3-3 複合極值分布 14
第四章 分析資料 17
4-1 資料來源與內容 17
4-2 影響台灣之颱風探討 18
4-2-1 重新定義颱風期間方法 22
4-2-2 驗證 26
4-3 同步波高與水位資料之選取 29
第五章 分析結果與討論 31
5-1 花蓮測站 31
5-2 新竹測站 38
5-3 龍洞測站 45
5-4 鵝鑾鼻測站 52
第六章 颱風強度之新定義 58
6-1 重現期計算與新颱風強度標準 58
6-2 聯合發生重現期分析 59
6-2-1 聯合發生機率分析方法 59
6-2-2 颱風發生頻率的影響 64
6-2-3 Copula與CEVD法結果的差異 65
6-3 新颱風強度分類結果與驗證 68
第七章 結論與建議 72
參考文獻 74
附錄 78


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