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研究生： 童裕翔
Yu-Shiang Tung
論文名稱： 氣候變遷下的亞洲 – 極端事件與夏季季風
Changing climate in Asia – Extreme events and summer monsoon
指導教授： 陳正達
Chen, Cheng-Ta
學位類別： 博士
Doctor
系所名稱： 地球科學系
Department of Earth Sciences
論文出版年： 2014
畢業學年度： 102
語文別： 中文
論文頁數： 60
中文關鍵詞： 氣候變遷 、極端事件 、季風肇始 、一般極限值
英文關鍵詞： Climate change, Extreme event, Monsoon onset, GEV
論文種類： 學術論文
相關次數： 點閱：213  下載：52 
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    • 近年研究全球極端事件發生頻率的趨勢重點多放在全球平均值的表現，亞洲地區的內容則不多。當使用模式資料分析極端事件時，改變資料解析度造成的空間頻散效應(areal reduction)造成分析結果錯誤常被忽略。夏季極端降雨事件(如颱風)降雨型態，發生時間多涵蓋於的亞洲夏季季風(Asian Summer Monsoon, ASM)所伴隨的大量而持續性的氣候型態降雨。過去用模式降雨資料分析亞洲季風推演時間常因為東亞地區缺乏降雨的系統性誤差而失去預報準確率。因此，本研究將應用一般極值分布(Generalized Extreme Value distribution, GEV)，把溫度與降雨的極端值轉換為可能性指標(Probability Index, PI)，減少各別模式間的不確定性與因改變解析度造成的空間頻散。另外，ASM的肇始(消退)時間則將5天的氣候降水平均(Climatology Pentad precipitation Mean, CPM)轉換為季風降雨指標比(ratio of monsoon precipitation index, RPI)，並運用各別模式的特徵門檻值，表現其季風肇始能力。
    觀測極端溫度變化趨勢空間分布發現，全球低溫事件比高溫事件有較多的正趨勢含蓋範圍且變化幅度較大，而模式的各種溫度指標都普遍正趨勢。亞洲地區氣候長期趨勢而言，極端低溫事件頻率(TNn與TXn)在減少，說明氣候變遷(暖化)的趨勢。而極端高溫事件部份，夜晚高溫(TNx)在1980年代後頻率開始增加，但白天高溫(TXx)沒有明顯的趨勢。觀測極端降雨資料(rx1day)在人口稠密的亞洲地區陸地，1990年代為上升的趨勢。模式則無明顯的趨勢。在改變模式解析度的過程中，各別模式在原始解析度即應取得其極端指標，以避免產生空間頻散效應，失去模式原本應有的強度表現。
    從模式降雨資料分析亞洲季風推演(肇始、消退與持續)時間的分析，發現使用各別模式特徵門檻值比固定門檻值的預能力更好；CMIP5(Couple Model Intercomparison Project Phase-5)的結果比CMIP3(Couple Model Intercomparison Project Phase-3)更好，特別是在熱帶強降雨的區域。應用觸發對流方式的參數化法(bulk|CAPE)的模式於季風降雨推演變化能有較好的表現。季風覆蓋面積雖然模式驗證結果相較觀測為低估，但強度則有很高的相似性，說明模式可以在有季風訊號的區域準確描述季風強度與降雨型態。
    兩種不同暖化情境下，ASM肇始時間稍微提早；消退時間則是明顯推遲，印度半島附近區域持續時間主要因為消退時間的推遲。而在東北亞地區與西北太平洋(West-North Pacific, WNP)東部則因肇始時間提早同時消退時間也延後，使得持續時間延長的幅度較大。由不確定性分析也得到未來可能發生(likely)的類似結果，且強暖化情境愈嚴重推遲與延長的情況愈明顯。本研究在夏季季風的未來推估部份若能增加定性上的分析，將有助於完整描述氣候變遷下的亞洲夏季季風。

    表說……………………………………………………………………………I 圖說……………………………………………………………………………I 第一章 前言…………………………………………………………………1 第二章 資料使用與分析方法……………………………………4 2.1 資料使用………………………………………………………………4 2.1.1 觀測資料…………………………………………………………4 2.1.2 模式資料…………………………………………………………5 2.2 分析方法………………………………………………………………6 2.2.1 極端事件指標…………………………………………………6 2.2.2 可能性指標(Probability Index, PI)………………………………6 2.2.3 亞洲夏季季風肇始與消退………………………………………7 2.2.4 統計分析…………………………………………………………8 第三章 模擬過去氣候的驗證……………………………………9 3.1 極端指標………………………………………………………………9 3.1.1 解析度變化的效應…………………………………………9 3.1.2 極端溫度…………………………………………………………10 3.1.3 極端降雨…………………………………………………………12 3.2 亞洲夏季季風(ASM) ………………………………………13 3.2.1 觀測與模擬的降雨氣候型態…………………………………… 13 3.2.2 季風降雨指標比(RPI)的應用……………………………………14 3.2.3 深對流參數化法(deep convection scheme)分類討論……………15 3.2.4 肇始(onset)、消退(retreat/withdraw)與持續(duration) …………15 3.2.5 夏季季風的強度與覆蓋區域驗證………………………………19 第四章 亞洲夏季季風未來推估………………………………………………21 4.1 肇始、消退與持續時間……………………………………………………21 4.2 季風覆蓋範圍與強度的變化………………………………………… 22 4.3季風大尺度環流場的變化……………………………………………… 24 第五章 結論…………………………………………………………………25 參考文獻………………………………………………………………………27 圖表………………………………………………………………………………30

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