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研究生: 柯明格
Miguel Conrado Valdez Vasquez
論文名稱: 探討海平面溫度對中美洲巴拿馬地區 降雨與森林物候之非線性與非穩態性影響
Exploring the Non-linear and Non-stationary Effects of Sea Surface Temperature on Regional Precipitation and Forest Phenology in Panama
指導教授: 陳繼藩
Chi Farn Chen
口試委員:
學位類別: 博士
Doctor
系所名稱: 工學院 - 土木工程學系
Department of Civil Engineering
論文出版年: 2015
畢業學年度: 103
語文別: 英文
論文頁數: 133
中文關鍵詞: 海平面溫度降雨森林物候遙相關
外文關鍵詞: Sea Surface Temperature, Precipitation, Forest Phenology, Teleconnection
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  • 全球海平面溫度的固有效應與在水文循環與植被覆蓋的反應異常性,複雜了熱帶區域尺度的氣候結構。而被太平洋與大西洋兩大洋以及南美與北美大陸塊體所包圍的中美洲,評估關聯性氣候驅力影響下的水文過程十分重要。本研究以時序性遙測影像進行小波分析,找出水文與植物的非穩態特徵。研究歸納十年與三十年兩個不同的時間窗期,同時以在大西洋與太平洋洋面溫度,與在中美洲巴拿馬拉阿米斯塔德國際公園研究區內的增強植生指數與降水量,進行一系列非穩態與非線性的引領與非引領遙相關信號之研究。選中此研究區域主要是避免人為影響可能掩蓋氣候遙相關信號,研究指出,跨越異常資料集中的線性遙相關特徵,展現洋面溫度與陸地區域有顯著的相關關係;同樣地,二年與三年非穩態的資料訊號呈現了陸區反應與穿越兩個海洋的洋面溫度異常,並與聖嬰-南方現象(ENSO)、北大西洋震盪(NAO)及可能與季節變化有一致的常數低頻訊號有關聯。藉由小波經驗正交函數(WEOF)分析,進一步反映了大西洋與太平洋的洋面溫度和研究區原始林地綠化之間的非線性關係。以遙測資料進行小波分析的結果顯示增強型植被指數/降水數據跟大西洋跟太平洋的洋面溫度呈現年度內的高頻訊號和兩年到三年期的低頻訊號。時空優先搜索進一步證實聖嬰-南方現象對研究區陸地反應的重要性。聖嬰-南方震盪遙相關型態可能會影響中美洲在雨季開始前幾個月,因雨量減少所造成的乾旱與乾季時植被覆蓋區域的減少。此外,這個長期的遙相關信號可以助於瞭解在地氣候變遷衝擊,並可藉由建立確定訊號之間的關係而幫助降雨的預測。


    The inherent effects of global Sea Surface Temperature (SST) anomalies on hydrological cycle and vegetation cover complicate the structure of tropical climate at the regional scale. Assessing hydrological processes related to climate forcing is important in Central America because it is surrounded by both the Pacific and Atlantic oceans and two continental landmasses. In this study, the use of high-resolution remote sensing imagery and wavelet analysis helps identify nonstationary characteristics of hydrological and ecological responses. The study is conducted in two different time frames, 10 years and 30 years. In this study, a series of non-stationary and non-linear leading and non-leading teleconnection signals are identified between SST at the Atlantic and Pacific oceans and the Enhanced Vegetation Index (EVI) and precipitation in the La Amistad international Park at Panama, Central America. The site was selected to avoid anthropogenic influences that could mask climate teleconnection signals. Linear teleconnection patterns across anomalous datasets found significant correlation regions between SST and the terrestrial sites. Biennial and triennial Non-stationary signals are also exhibited between terrestrial responses and SST anomalies across ocean regions related with the El Niño Southern Oscillation (ENSO), North Atlantic Oscillation (NAO) signals as well as constant low frequency signals, which may coincide with the seasonality changes.
    The Wavelet-based Empirical Orthogonal Function (WEOF) further reflects the nonlinear relationship between the Atlantic and Pacific SST and the greenness of a pristine forested site in Panama, La Amistad International Park.
    The results of our remote sensing based wavelet analysis showed intra-annual high-frequency and biennial to triennial low-frequency signals between EVI/precipitation datasets and SST indices in both Atlantic and Pacific oceans. A spatiotemporal priority search further confirmed the importance of the effects of the ENSO over terrestrial responses in the selected study site. In addition, a series of potential non-leading teleconnection patterns were identified in the Pacific ocean.
    Coincidence of the effect of ENSO teleconnection patterns on precipitation and vegetation suggests possible impacts of El Niño-associated droughts in Central America, accompanied by reduced rainfall, specifically during the first months of rainy season, and decline in vegetation cover during the dry season. In addition, this identified long-term teleconnection signals can aid for understanding the climate change impacts at local scales, and can aid to forecast precipitation by establishing a relationship in the information identified.

    Table of Contents 摘要 ................................... i ABSTRACT .................................................. ii ACKNOWLEDGMENT ............................................iv LIST OF FIGURES ...................................................ix LIST OF TABLES .....................................................xi LIST OF ACRONYMS ............................................. xii 1. Introduction ....................................................... 1 1.1 General Background .................................................... 1 1.2 Research Science Questions ........................................................ 6 1.3 Dissertation Structure .................................................... 7 2. Literature Review .................................................. 8 2.1 Teleconnection and Climate Change Studies in the Region .................................... 8 2.1.1 El Niño Southern Oscillation ...................................................... 10 2.1.2 North Atlantic Oscillation .................................................... 14 2.1.3 Pacific North American Pattern .......................................................... 16 2.2 Stationary and Non-stationary stochastic processes. ............................................. 19 2.3 Non-stationary, nonlinear processes studies. ......................................................... 19 2.4 Methods for non-linear non-stationary time series analysis. ................................. 22 2.5 Climate Anomalies in Panama ....................................24 3. Study Area .................................................... 27 3.1 Terrestrial Study Area ............................... 27 3.2 Oceanic Study Area ...................................................... 28 4. Methodology ....................................................... 30 4.1 Conceptual Framework ....................................................... 31 4.2 Data Collection ................................................... 32 4.2.1 Enhanced Vegetation Index Data ........................................................... 32 4.2.2 Precipitation data ......................................................... 35 4.2.3 Land Surface Temperature.............................................. 36 4.2.4 Sea Surface Temperature ..................................................... 37 4.3 Data Pre-Processing ....................................................... 37 4.3.1 TRMM precipitation data correction ....................................................... 39 4.4 Assessment of variability via box plot .............................................. 42 4.5 Wavelet analysis of variability .......................................................... 43 4.5.1 Principal Component Analysis ...................................................... 46 4.6 Wavelet analysis of teleconnectivity ............................................... 48 4.6.1 Linear correlation analysis ........................................................ 48 4.6.2 Stepwise Regression Analysis ............................................. 49 4.6.3 Wavelet Analysis .............................. 50 5. Results and discussion ........................................................... 54 5.1 Results for short term analysis .................................................... 54 5.1.1 Assessment of variability via box plot ............................................................ 54 5.1.2 Wavelet Analysis of Variability ..................................................................... 55 5.1.3 Wavelet Analysis of Teleconnectivity ............................................................ 62 5.2 Results of Long Term Analysis............................................... 81 5.2.1 Wavelet analysis of variability ......................................................... 81 5.2.2 Principal Component Wavelet Processing ..................................................... 85 5.2.3 Mapping Teleconnection Regions ........................................................... 86 6. Conclusions ...................................................... 91 7. References .........................................................95

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