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Study on Wave Climate Change in Taiwan Water
wave climate changing trend
o and La Niñ
the big wave extreme events
the global warming
the Gumbel distribution
the Weber distribution
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|摘要:||近十年來太平洋暖池 (Warm pool)強度增加，導致平均海水表面溫度(Sea Surface Temperature, SST)增溫，根據研究指出(Emanuel, 2001, 2004, 2006)，海水表面增溫將直接造成熱帶氣旋(颱風)最大潛在強度(Maximum Potential Intensity, MPI)增強。台灣位於西太平洋颱風主要路徑上，必將直接面臨強度遽增颱風造成的極端波浪狀況。目前太平洋海水增溫的機制尚未有學術上的定論，有可能肇因於全球暖化的結果。若太平洋海水增溫現象持續，則迅速增多的極端事件將有可能改變台灣海域長期波候特性：颱風波浪的能量及高度的尖銳度將導致目前依賴各種海岸工法得以維持侵淤平衡的砂質海岸，因平衡條件的改變將使岸線迅速崩潰。
本研究應用波浪數值推算SWAN(Simulation of Wave in Nearshore)模式，以美國國家環境預報中心 (National Center for Environmental Prediction, NCEP)所提供1948-2008年全球歷史表面10公尺風速分析場，推算近60年來海面歷史波場，重建西北太平洋與台灣海域之波浪資料，所建置之波浪數值模式，經由2004年冬夏兩季台灣週邊海域實測花蓮、龍洞、七股及鵝鑾鼻等四測站資料的校驗，獲得最佳之源函數與模擬參數設定，並應用此參數進行推算，模式結果與觀測之示性波高均方根誤差小於0.5公尺。重建的波浪資料經與實測資料比對後確認其正確性後，分別應用於探討台灣海域波候變遷趨勢，就(1)波候於時間上之變異、(2)大波極端事件統計分析、(3)波候變遷對台灣海域海事工程可工作日的變化趨勢影響以及(4)波候變遷對海岸侵淤及波浪特性之影響等問題進行研究。研究結果發現：波候於時間上之變異，顯示台灣海域的波候存在有三種主要週期的震盪，包括季節性的變動，年際變動與十年際震盪，且波能年際震盪與聖嬰、反聖嬰現象具有高度相關，震盪的發生與南方震盪指標(Southern Oscillation Index,SOI)間不具有相位延遲；以往受限於波浪觀測歷史資料長度，此現象於波能發電潛勢評估中未曾被注意，惟分析結果顯示年平均波能在聖嬰年與反聖嬰年之差異可達一倍，故此波浪震盪影響應納入工程評估，不可忽略。
Recent reports by Emanuel (Emanuel 2001, 2004 and 2006) demonstrated the linear dependency of the increase of typhoon maximum potential intensity to the sea surface temperature. With the intensified warm pool activities in the northern Pacific from 2000, it is expected that the typhoon strength will be intensified. Taiwan, which located in the midway of the most populated trajectories of typhoons in the world, will be suffered from the direct impacts that brought by the extreme conditions. There are not yet conclusive theories explaining the increase of sea surface temperature in the Northern Pacific. The typhoon intensifications might be inter-annual oscillated or by global warming effects. Both will incur the wave climate change in the coastal region of Taiwan. The coastlines of Taiwan Island are currently protected and preserved by artificially means. Rapid erosions might be triggered by the collapse of temporally balance. With the wind speed analysis data of global historical surface 10-meter wave in the period of 1948-2008 provided by the National Center for Atmospheric Research and National Center for Environmental Prediction (NCAR/NCEP), this study applied the SWAN wave model in estimating the sea surface historical wave fields in recent 60 years to reconstruct the wave data of the Northwest Pacific and Taiwan's surrounding waters. The reconstructed wave data model was calibrated and tested by the actual measurement data measured in summer and winter of 2004 in four stations in Taiwan's surrounding waters to obtain the optimal source function and simulation parameter settings. The root mean square error between the simulation results by estimation using the parameters and the observed significant wave heights is smaller than 0.5 m. After confirming the accuracy of reconstructed wave data by comparison with the actual observation data, the reconstructed wave data were applied in the discussion of the wave climate changing trend, including (1) wave climate in the variation of time , (2) the statistical analysis of various big wave extreme events, (3) changes of Taiwan's surrounding waters in working days as well as (4) changes in coastal erosion and wave characteristic questions ets.,respectively. The results indicated that there is a rising trend of big wave extreme events in Taiwan's surrounding waters after 2000. In addition, before 1987, most big wave extreme events occurred in winter due to the impact of northeastern monsoon. However, the proportion of such events affected by typhoon has been relatively higher after 1987, indicating the impact of climate changes. Meanwhile, the wave climate of Taiwan's surrounding waters has three major cycles of shocks including seasonal shocks, annual shocks, and decadal shocks. Moreover, the annual wave energy fluctuations are highly related to El Niño and La Niña phenomena. The occurrence of shocks and SOI index has no phase delay. Due to limitations of wave observation historical data length, this phenomenon has not been considered in assessing wave energy power generation potentials. The analysis results suggested that the average annual wave energy may differ by 100% in years of El Niño or La Niña. Hence, the impact of wave shocks should be taken into consideration in engineering assessment rather than being neglected. The research findings suggested that Taiwan's wave climate has a significantly changing trend at two time periods. In the first period of 1981~1982, due to strong impact of the El Niño phenomenon, the average annual wave height tended to decline and returned to normal at the end of 1983. On the other hand, in the period starting from the beginning of 2003 to the present day, the wave steepness increased by 30% in three years and the unit area wave energy increased by 2.5 times, the wave direction gradually turned northward up to 10 degree. Such phenomena have been continuously happening, indicating the upcoming dramatic change in coastal erosion and coastal drifting sand. Secondly, this study explored the occurrence probability of various big wave extreme events in Taiwan's surrounding waters. The findings suggested that extreme events in recent 60 years occurred mainly in the period from 1967 to 1974 and the period from 2000 to 2008. In case of extreme events in the later period, the wave height was high and lasted for long time. There is a trend of decreasing extreme events occurring in winter in Taiwan's surrounding waters and a rising trend of summer extreme big wave events. The big wave extreme events in summer are completely caused by typhoon. With 1985 as the division line, the proportion of extreme events caused by typhoon is higher than the proportion of such events caused by northeaster monsoon, and the proportion has been increasing. This implies that global warming has a fundamental impact on the strength of typhoons in Taiwan's surrounding waters. Nevertheless, the number of extreme events has not changed significantly. Finally, based on the long term wave data of recent 60 years, this study further analyzed changes of Taiwan's surrounding waters in working days, and discussed the application of various common statistical distribution models in the comparison of estimation of the occurrence probability of extreme events in the Kinmen waters. The results suggested that the Gumbel distribution fitness level is better than the relatively commoner Weber distribution. However, it is too conservative in terms of extreme big value. This study found that generalized extreme value distribution can best describe the wave statistical characteristics in the Quemoy waters.
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