臺灣博碩士論文加值系統

過去對於大氣長河的研究主要集中在大洋東側，討論大氣長河的氣候特徵、斜壓系統如何增強大氣長河，以及大氣長河登陸造成的極端降水事件；然而，西北太平洋地區亦受大氣長河影響，且正壓系統如熱帶氣旋在此區域的水氣輸送上扮演著重要角色。因此拓展大氣長河的研究範圍至西北太平洋沿岸地區，討論其氣候特徵、熱帶氣旋之影響和伴隨台灣極端降水事件的關係為本文的研究重點。
為探討36年大氣長河在西北太平洋之氣候特徵，此研究延續並修改前人發展之大氣長河偵測演算法，以圖形辨識分析1980年到2015年間瞬時垂直積分水氣輸送值大於 450 kg m^(-1) s^(-1)或距平值大於 250 kg m^(-1) s^(-1)之區塊，氣象變數資料取自NASA Modern-Era Retrospective Analysis for Research and Applications Version 2 (MERRA-2) 再分析資料，颱風中心是採用Joint Typhoon Warning Center (JTWC) 最佳路徑資料。結果顯示在西北太平洋區域，夏季（六、七、八月）的大氣長河發生頻率高於冬季（十二、一、二月），此季節變化恰與東北太平洋區域相反，且西北太平洋區域的大氣長河受颱風影響大於東北部；而熱帶氣旋與環境之交互作用有助於帶狀位渦生成，使大氣長河得以發展；若以大氣長河之發生當作判斷大雨強度以上的極端降水事件之指標，討論台灣地區此指數的預報能力，則平均而言，五六月梅雨季有高前估率71.0%和較低的後符率45.9%，七八月颱風季則有較高的後符率57.3%和較低的前估率38.0%，顯示梅雨季之極端降水事件多與大氣長河有關，而颱風季當中的大氣長河有過半數會伴隨極端降水事件發生。

Past research on atmospheric rivers (ARs) has explored their climatological features, baroclinic mechanisms of enhancement, and the relation to continual extreme precipitation events mainly on the eastern edges of ocean basins. However, ARs also threaten the Western North Pacific (WNP) region and tropical cyclones (TCs) seem to affect the ARs’ intensity. Therefore, extending the previous studies to characterize the ARs in this region, investigating how these ARs are affected by TCs, and examining the relation between extreme rainfall events and ARs are the main objectives of this paper. A modified occurrence-based detection algorithm is applied to the anomalous or total integrated water vapor transport field to identify the ARs from 1980 to 2015 in WNP, using the NASA Modern-Era Retrospective Analysis for Research and Applications Version 2 (MERRA-2) reanalysis dataset and the Joint Typhoon Warning Center (JTWC) best track data. The results emphasize that ARs occur more frequently in the warm season than in the cold season in the WNP, which is the exact opposite of the situation in the Eastern North Pacific (ENP), and that the impact of TCs is more significant in the WNP than in the ENP. Some of the insights into the influences of TCs on ARs reveal the importance of potential vorticity strips forming between TCs and ARs. Using AR occurrence as a heavy rain forecast index, the forecast skill in Taiwan is discussed briefly: during the “Mei-Yu Season” in May and June, the mean prefigurance is as high as 71.0% and the mean postagreement is relative lower than the prefigurance at a ratio of 45.9%; on the contrary, during the “Typhoon Season” in July and August, the postagreement is relatively high with 57.3% and the prefigurance is 38.0 %. This shows that most of the extreme rainfall events are associated with ARs in the “Mei-Yu Season” while over half of the ARs in the “Typhoon Season” are accompanied by extreme rainfall in Taiwan.

CONTENTS

口試委員會審定書 #
誌謝 i
中文摘要 ii
ABSTRACT iii
CONTENTS v
LIST OF FIGURES vii
Chapter 1 Introduction 1
1.1 Overview of Atmospheric Rivers (ARs) 1
1.2 Structure and Properties of ARs 2
1.3 Motivation – Influence of Tropical Cyclones (TCs) on ARs in Western North Pacific 5
Chapter 2 Data and Methods 12
2.1 Data Sources 12
2.1.1 Atmospheric Variables and the Best Track Data 12
2.1.2 El Niño-Southern Oscillation 12
2.2 Methods 13
2.2.1 Two Commonly Used Fields for AR Detection 13
2.2.2 The Modified AR-detection Algorithm 14
2.2.3 Prefigurance and Postagreement of AR and Extreme Rainfall 19
Chapter 3 Results and Discussion 26
3.1 Climatology of ARs in Western North Pacific 26
3.1.1 Seasonal Variability of ARs 26
3.1.2 Interannual Variability - ENSO 28
3.1.3 ARs with TC Influence in the WNP 29
3.2 The Hypotheses of TCs’ Impact on ARs in the WNP 32
3.2.1 The Case Study - Brief Introduction of TC Goni (2015 16W) 32
3.2.2 Mechanisms of the AR Formation and Maintenance 33
3.3 Heavy Rainfall and ARs in Taiwan 35
Chapter 4 Conclusions 60
REFERENCE 62
Appendix A. The Modified AR Detection Algorithm 66
Appendix B. AR Without Further TC Criteria 78
Appendix C. Details of the Boxplots 79
Appendix D. Prefigurance and Postagreement Based on anomalous IVT fields 80
Appendix E. Sensitivity Test of the Prefigurance and the Postagreement on the Smaller Domain of Taiwan 82
Appendix F. AR evolution in the Mei-Yu Season and in the Typhoon Season of Taiwan 84

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