臺灣博碩士論文加值系統

本研究利用區域波譜模式(Regional Spectral Model; RSM)執行1990年至2000年東亞(50公里解析度; RSM1)及台灣(15公里解析度; RSM2)區域氣候之降尺度模擬，其中RSM2模擬結果是使用RSM1結果執行降尺度模擬所得到(C2R)。另外本研究也比較在等壓面上和原來在sigma面上的擴散項計算方式來進行相同的模擬實驗(RSMp vs RSMs)，以探討此新的擴散項計算方式是否能改善其模擬結果。
由全球觀測及NCEP再分析資料顯示，在東亞地區陸地上降水分佈NCEP再分析資料在五至八月間顯著偏多，海洋上則偏少。50公里解析度之RSM1s逐年逐月模擬出和NCEP 再分析資料相似的降水分佈，但更能呈現出中、小尺度局部地區降水分佈特徵，也更能掌握住降水隨時間變化的趨勢。但RSM1s在中國地區降水模擬甚至比分析場更多，海洋上則更加偏少，尤其在夏季期間。推測可能是由於太平洋副熱帶高壓模擬偏強，伴隨在中國南部至台灣地區為較強南風，造成此區域降水過多，且最大降水中心較靠近中國內陸。
RSM1p的模擬改善了RSM1s在地形陡峭地區(如台灣地區)降水過多的問題。降水分佈時空特徵都較接近於觀測值，冬季期間尤其顯著。夏季期間中國地區的降水模擬仍傾向偏多，而台灣及海洋上偏少。
另外RSM1s及RSM1p都無法模擬出夏季期間東亞區域颱風日之強烈低壓特徵，且氣旋式特徵較不顯著。代表此靜力波譜模式無法有效掌握颱風所造成之強烈低壓環流及大降水特徵。非颱風日之RSM1s及RSM1p模擬結果皆和NCEP 再分析資料的環流特徵類似，但太平洋副熱帶高壓模擬皆偏強。
由15公里解析度之台灣地區(RSM2)模擬結果中，RSM2s及RSM2p除夏季外皆能顯示因地形作用所造成局部地區風場、溫度及降水變化特徵。而RSM2p更能改善RSM2s在山區過多降水模擬，使其降水分佈及降水量更接近觀測值。但夏季期間RSM2s及RSM2p仍無法掌握颱風在台灣地區所造成的強烈低壓環流及降水分佈特徵。可是RSM2s及RSM2p可大致掌握非颱風日之風場環流特徵，而RSM2p的降水分佈則優於RSM2s，但降水量則偏少。
本研究也使用NCEP全球再分析資料不經由第一層的網巢直接進行台灣地區(15公里解析度)之降尺度模擬(G2R)顯示。G2R模擬月平均降水分佈特徵和前述之C2R結果相似，但冬季則更接近觀測值。G2R也比C2R更能掌握住降水隨時間變化特徵及較高的降水得分指標，尤其夏季期間南部地區更加顯著。

摘要(p.I)
目錄(p.III)
圖表說明(p.V)
第一章 前 言(p.1)
第二章 區域波譜模式介紹(p.6)
2.1 模式之控制方程(p.6)
2.1 模式之數值方法(p.8)
2.3 模式之空間物理參數化(p.11)
第三章 模式設定及觀測資料(p.12)
3.1 模式範圍設定及初始資料(p.12)
3.2 評估資料(p.12)
3.3 診斷工具(p.13)
第四章 模式敏感度實驗(p.15)
4.1 區域波譜模式之敏感度實驗設計(p.15)
4.2 小結(p.21)
第五章 東亞區域氣候模擬(p.22)
5.1 各月之氣候平均場分析(p.22)
5.2 RSM之颱風環流場分析(p.33)
5.3 區域降水的季節變化和年際變化分析(p.35)
5.4 小結(p.40)
第六章 台灣區域氣候模擬(p.42)
6.1 各月之氣候平均場分析(p.42)
6.2 相關係數分析(p.47)
6.3 經驗正交函數分析(p.49)
6.4 台灣地區之降水特性分析(p.52)
6.5 颱風對台灣地區降水的影響(p.58)
6.6 台灣地區降水技術得分(p.60)
6.7 台灣地區降水單點相關分析(p.62)
6.8 單層網巢模擬結果(p.64)
第七章 結論與討論(p.68)
參考文獻(p.74)
附圖(p.80)

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