在中尺度氣象模擬中常需使用土地分類資料和各類土地的地表參數，然而詳細的土地使用資料不易取得，過去RAMS模式常利用AVHRR遙測資料所推求的GLCC（全球土地覆蓋特性資料）作為其預設的輸入資料，然而GLCC所使用的遙測資料不但較舊，解析度較低，而且對都市地區的判讀較不準確。現今更新的全球土地使用資料庫是MOD12Q1地表覆蓋資料庫， MODIS的遙測資料不但較新，且具有較高的解析度，其分類演算法也較準確。在本研究中我們發現這兩個資料集在台灣有很大的差異，MODIS的都市範圍比GLCC大許多，如果和台灣人口分佈，建築物面積比較，也發現MODIS的資料較為合理。除了地表分類資料外，我們也發現不同地表參數也會對模式模擬的結果產生影響，尤其是在都市地面粗糙度上，RAMS所設定的地面粗糙度過低，與台灣都市建築物高度有很大的出入。因此，本研究除了比較兩種不同土地使用資料對RAMS模式模擬結果影響，也針對修正地面粗糙度後的模擬結果進行探討。
變更土地使用資料後，台灣西部沿岸的都市幅員大幅度增加，在地面氣象場模擬結果中，可以發現地表類型為都市與農田兩者間之溫度差異約在2℃左右，且都市空氣中水氣含量較農田降低了0.002 kg/kg-air，都市熱島效應非常顯著。而提升RAMS的都市地面粗糙度，在風速的模擬上有良好的結果，地面風速減弱3m/s，模擬值與實測值大幅度的趨近。

The land use dataset and surface parameters for different land categories are important inputs for mesoscale meteorological models. The Global Land Cover Characterization (GLCC) dataset generated form AVHRR data were widely used by mesoscale meteorological models such as RAMS. However, the GLCC data have several drawbacks. They are of out of date, low resolution, and inaccurate, especially for urban classification. Another newer dataset is MOD12Q1. This dataset uses new data, has higher resolution and more accurate classification for urban area. There are significant differences between these two dataset for Taiwan area. The urban areas in MODIS dataset are much larger than that of GLCC dataset. When compare with the distributions of population and building density in Taiwan, it is found that MODIS dataset is more reasonable. We also noted that the surface parameters, especially surface roughness, are important for urban meteorological simulation. Since the buildings are higher in Taiwan area, the default setting of surface roughness in RAMS is too low when it was used in Taiwan. In this study, we investigate the effects of different land use dataset and urban roughness on the results of meteorological simulations.
When the MODIS dataset was used, the surface temperatures in urban areas increased about 2℃ and the water contents in urban areas decreased about 2g/kg-air. Significant urban heat island effects were noted. If the surface roughness were increased, the surface wind speeds may decrease 3m/s in urban areas and have better agreement when compared with observations.

中文摘要	I
英文摘要	I
目錄	III
表目錄	V
圖目錄	VI
第一章 前言	1
1.1 研究緣起	1
1.2 熱島效應	4
1.3 研究目的	6
第二章 土地使用資料	8
2.1 本章簡介	8
2.2  GLCC	8
2.3  MODIS	9
2.4  輔助資料	10
2.4.1  GLCC與MOD12Q1的比較	10
2.4.2 人口分布情況與GLCC和MOD12Q1都市區塊差異比較	14
2.4.3 建築物和道路密度與GLCC和MOD12Q1都市區域差異比較	15
2.5 本章結論	17
第三章 氣象模式設定	18
3.2  RAMS氣象模式	19
3.3 制御方程式和網格結構	20
3.4 雙向鑲嵌網格（Two-way nesting）	22
3.5 地表參數設定	25
3.6 邊界條件	25
3.7 時間差分	29
3.8 四維資料同化和逼近邊界條件	29
3.9 資料分析技術	30
3.10 模式處理流程	31
第四章 氣象模擬結果與討論	34
4.1 模擬期間的綜觀天氣	34
4.2 模擬個案	38
4.3第二層網格模擬天氣概述	39
4.4 地面觀測值與模擬值比較	43
4.4.1 四公里網格地面溫度時序列圖和統計圖模擬結果比較	46
4.4.2 四公里網格地面風速時序列圖和統計圖模擬結果比較	54
4.5 地面氣象場模擬結果	61
4.5.1 第三層網格地面氣象場模擬結果	61
4.5.2 第四層網格地面氣象場模擬結果	68
4.6 位溫討論	74
4.7 第三層網格850mb氣象場模擬結果	79
第五章 結論與建議	81
參考資料	83

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