蘇門答臘島北部地區夏季年際間降水變化之機制探討

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姓名	葉海亞(Yahya Darmawan) 查詢紙本館藏	畢業系所	國際研究生博士學位學程
論文名稱	蘇門答臘島北部地區夏季年際間降水變化之機制探討 (Driving Mechanism of Inter-Annual Precipitation Variability in Northern Sumatra Island during Boreal Summer)
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摘要(中)	本研究分析比較蘇門答臘島北部地區由大尺度環流引導之降水異常特徵，並探討其與亞澳季風(Asian-Australian Monsoon，AAM)系統及其它環流系統間之遙相關。我們利用水氣收支分析方法量化北半球夏季六至八月(June, July, August；JJA)期間的降水變化，並探討造成此降水變化的主導要素。接著，再以合成分析及統計方法確認水氣收支的結果。除此之外，我們亦利用線性迴歸分析方法，比較各氣候指數在不同時空尺度的差異，如，偶極指數(Dipole Mode Index；DMI)、海洋聖嬰指數(Oceanic Niño Index ；ONI)及西北太平洋副高指數(Western North Pacific Subtropical High index；WNPSH index)。本研究使用1981至2016年歐洲中期預報中心(European Centre for Medium-Range Weather Forecasts；ECMWF)的再分析資料(Re-Analysis Interim；ERA-Interim)，分析蘇門答臘島北部地區夏季年際間之降水異常特徵。其中，我們分別定義九個乾季年及六個濕季年作為後續分析探討的依據。分析結果顯示，研究區域的乾/濕季年主要與下沉/上升垂直風速異常有關，而與比濕、水平風速及蒸發量較無明顯相關。另外，相較於聖嬰-南方震盪(El Niño-Southern Oscillation；ENSO)及印度洋偶極(Indian Ocean Dipole；IOD)，WNPSH與研究區域的降水異常有顯著相關性。然而，WNPSH指數卻與降水變化不一致，此指數無法在定義之乾/濕季年個案中顯現。比對結果顯示，絕大多數的濕季個案於熱帶西北太平洋區域，伴隨緯向風場的變動。此風場變化解釋了WNPSH指數與區域降水異常存在高度相關的原因。接著，我們定義一個新的氣候指數:東風指數(Easterly Wind Index；EWI)，以此指數探討蘇門答臘島北部地區的降水異常。EWI的強正/負相位和東/西風的強度異常有關，並導致蘇門答臘島北部地區正/負回饋的降水異常。此東/西風風場的異常可能與太平洋沃克環流(Pacific Walker Circulation)有關。AAM的變化在此地區降水變化扮演一個重要的角色。AAM與其他全球環流間的遙相關顯示，蘇門答臘島北部地區的降水異常並非一個區域現象，而是與菲律賓海與海洋大陸/東印度洋上空之大尺度熱帶環流有關。總結而言，東風風場異常為造成蘇門答臘島北部地區降水異常的主要特徵。當於北蘇門答臘地區產生下沉氣流的季風西風風場減弱(東風風場異常)時，此地區的降水將增加，反之亦然。
摘要(英)	This study explores the contrasting characteristics of large-scale circulation that led to the precipitation anomalies over the northern parts of Sumatra Island and investigates the schematic mechanism of teleconnection between the Asian-Australian Monsoon (AAM) and other circulations. The moisture budget analysis was applied to quantify the most dominant component that induces precipitation variability during the JJA (June, July, and August) period. Then, the composite analysis and statistical approach were applied to confirm the result of the moisture budget. The linear regression analysis was applied to compare the climate indices in both spatial and temporal scales, such as Dipole Mode Index (DMI), the Oceanic Niño Index (ONI), and the Western North Pacific Subtropical High (WNPSH) index. Using the European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis Interim (ERA-Interim) from 1981 to 2016, we identified 9 (nine) dry and 6 (six) wet years based on precipitation anomalies, respectively. The dry years (wet years) anomalies over the study area were supported mainly by downward (upward) vertical velocity anomaly instead of other variables such as specific humidity, horizontal velocity, and evaporation. Instead of El Niño-Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD), WNPSH has a stronger relationship with the study area′s precipitation anomalies. However, the WNPSH index is inconsistent with the precipitation variability because it cannot be found in all wet/dry year cases. By contrast, most cases (especially the wet events) were associated with the fluctuation of zonal winds in the tropical western North Pacific. This fluctuation explains why the WNPSH index has a stronger correlation with the precipitation in the study area. Then, a new climate index was proposed to identify the precipitation anomalies over the north of Sumatra Island, called the Easterly Wind Index (EWI). A strong positive (negative) phase of EWI is related to the magnitude of easterly (westerly) wind anomaly, which induces the positive (negative) precipitation anomaly over the northern part of Sumatra Island. The westerly and easterly wind anomaly is possibly related to the PWC modulation (Pacific Walker Circulation). Further, the AAM variability proven has a significant role in the precipitation variability over the study area. A teleconnection between the AAM and other global circulations implies that the precipitation variability over the northern part of Sumatra Island is not a regional phenomenon related to the large-scale tropical circulation over the Philippine Sea and the Maritime Continent/eastern Indian Ocean region. In conclusion, the easterly anomaly is the main feature resulting in precipitation anomaly over the northern Sumatra Island. When the monsoon westerly that creates subsidence in northern Sumatra is weaker (easterly anomaly), there tends to be more precipitation and conversely.
關鍵字(中)	★ 降水 ★ 水氣收支 ★ 亞澳季風(AAM) ★ 蘇門答臘島 ★ 歐洲中期預報中心再分析資料(ERA-Interim)	關鍵字(英)	★ Precipitation ★ Moisture Budget ★ AAM ★ Sumatra Island ★ ERA-Interim
論文目次	摘要 i Abstract ii Acknowledgments iii Table of Content iv List of Figures vi List of Table ix Chapter 1. Introduction 1 1.1. Research backgrounds 1 1.2. Hypothesis 8 1.3. Benefit of outcomes 9 1.4. Objectives 9 1.5. Overview of approach 10 1.5.1. Characteristics of Large-Scale Circulation Affecting the Inter-Annual Precipitation Variability in Northern Sumatra Is-land during Boreal Summer 10 1.5.2. Large-scale teleconnection impacting on summer precipitation variability over Northern Sumatra Island 10 1.6. Outline of Dissertation 10 Chapter 2. Methodology 12 2.1. Study Area 12 2.2. Data used 12 2.3. Methods 14 Chapter 3. Characteristics of Large-Scale Circulation Affecting the Inter-Annual Precipitation Variability in Northern Sumatra Island during Boreal Summer 19 3.1. Precipitation of Northern Parts of Indonesia Based on ERA-Interim 19 3.2. Precipitation Variability over Northern Parts of Sumatra Island 21 3.3. Moisture Budget Analysis 27 3.3.1. The Dry Years 27 3.3.2. The Wet Years 30 3.4. Moisture Flux Convergence (MFC) 33 3.5. Velocity Potential 35 3.6. Summary 36 Chapter 4. Large-scale teleconnection impacting on summer precipitation variability over Northern Sumatra Island 38 4.1. Time series analysis 38 4.2. Linear Regression Analysis 40 4.3. Diagnosis of the wet years 42 4.3.1. The wet year in 1988: DMI (N), ONI (-), WNPSH (+) 43 4.3.2. The wet year in 1995: DMI (N), ONI (N), WNPSH (+) 44 4.3.3. The wet year in 1996: DMI (-), ONI (N), WNPSH (+) 45 4.3.4. The wet year in 1998: DMI (-), ONI (-), WNPSH (+) 46 4.3.5. The wet year in 2008: DMI (N), ONI (N), WNPSH (N) 48 4.3.6. The wet year in 2015: DMI (+), ONI (+) 49 4.4. Diagnosis of the dry year 50 4.4.1. The dry year in 1981, 2005 & 2006: DMI (N), ONI (N), WNPSH (N) 51 4.4.2. The dry year in 1985: DMI (-), ONI (-), WNPSH (-) 53 4.4.3. The dry year in 2000: DMI (N), ONI (-), WNPSH (N) 55 4.4.4. The dry year in 2001: DMI (-), ONI (N), WNPSH (-) 56 4.4.5. The dry year in 2004: DMI (-), ONI (+), WNPSH (-) 57 4.4.6. The dry year in 2011: DMI (+), ONI (-), WNPSH (N) 58 4.4.7. The dry year in 2012: DMI (+), WNPSH (-) 59 4.5. A proposed index: The Easterly Wind Index (EWI) 60 4.6. Summary 64 Chapter 5. Conclusions, recommendations and future works 66 5.1. Conclusions 66 5.2. Recommendations 69 5.3. Future works 70 References 70
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指導教授	許晃雄余嘉裕(Huang-Hsiung Hsu Jia-Yuh Yu)	審核日期	2021-9-29
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