有鑒於台灣地區降雨時空分配不均，尤其是降雨量不足的氣候型態導致水源短缺、可用水資源分配與管理不易，乾旱現象愈漸嚴重。
本研究首先建立台灣南部區域之標準化降雨指標(Standardized Precipitation Index, SPI)，並配合全球氣候變化的趨勢，由「聖嬰－南方振盪(El Nino－Southern Oscillation, ENSO)」所造成太平洋環流區域之大尺度氣候型態改變的環流資訊，以分析台灣南部區域乾旱與ENSO近60年來時空上的變動。應用時間稽延的自我相關及交互相關統計方法，探討台灣南部區域SPI與ENSO相關指標的關聯。並參考馬可夫鏈之狀態轉移機率的概念，由不同變數的間隔範圍計算其發生次數，以建置不同ENSO相關指標狀態下轉移至SPI的機率分布矩陣。再藉由所建置的狀態轉移機率矩陣予以建立乾旱機率預報模式，並進一步以多模式系集機率預報的概念，由ENSO相關指標資訊所處的狀態，預測台灣南部區域的乾旱現象，提供台灣南部區域乾旱短期預警及未來長期乾旱情況評估之參考依據。
本研究由1950至2009年台灣南部區域乾旱以及聖嬰現象趨勢分析結果顯示，聖嬰或反聖嬰的特性為台灣南部區域嚴重乾旱至極端乾旱的發生機率之間。而由不同乾旱程度與聖嬰現象發生時間始末的觀點，無法明顯看出乾旱與聖嬰兩者間的關聯性。於乾旱機率預報模式的分析結果，顯示2001至2009年台灣南部區域的乾濕比例為6：4，表示2001至2009年間之氣候特性偏乾。且由多模式系集機率預報的結果，顯示以多模式系集的方法來預報可以降低單一模式機率預報的不確定性。

Although Taiwan receives much precipitation (by an annual average of about 2,510 mm), Taiwan is an area prone to suffer droughts due to uneven temporal distribution of precipitation and small storage capacity of reservoirs. Therefore, how to make drought early warning and protection against possible losses of life and property has been an essential issue in Taiwan.
This study collected the information of Pacific large scale circulation patterns, i.e., El Nino–Southern Oscillation (ENSO) indices, and the historical rainfall records from 7 raingauges in southern Taiwan for calculating the standardized precipitation index (SPI) during 1950 to 2009. Autocorrelation statistical method was used to analyze the correlation between values of each variable (e.g., ENSO indices and SPI) at different points in time; and cross-correlation statistical method was used to analyze the relationships between ENSO indices and SPI. Based on the theory of Markov chains, this study calculated the frequencies from the intervals among different variables (e.g., ENSO indices and SPI) for building state transition probability matrixes to establish drought probability forecasting models. Different combinations of variables make different forecasting models. Therefore, for reducing the forecasting uncertainty of a single-model, the approach of multi-model ensemble (MME) which is considered as all single-models was used to forecast the SPI probability distribution 1-month ahead by using the ENSO indices at the present time as the predictors.
Analytical results show that the proposed models can well performed in providing short-term early warning of droughts in southern Taiwan and can be used to assess the long-term dry to wet conditions during a given period. For example, the ratio of dry to wet conditions in southern Taiwan is 6:4 during 2001 to 2009, which reveals that the weather pattern was prone to the dry condition during the period.

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