都卜勒雷達是輔助氣象預測的利器，藉由分析都卜勒雷達的回波強度資料可以瞭解水氣的分佈狀況與其結構，並可推算出風場以預測未來的天氣狀況。將水氣和風場資料視覺化將有助於天氣分析與預報。
本論文提出一個氣象雷達資料的視算系統，此系統著重於分析與顯示風場資料。在我們的方法中，我們首先利用地表高度資料過濾雜波，接著利用光流法從氣象雷達資料估算出風場。另外為了同步協調多個雷達站的資料，解決不同雷達站之間彼此掃描速度不同步的問題，我們使用一個和流場特性有關的內插法，計算出不同雷達站在相同時間點的風場資料，並合併它們以建立廣範圍的氣象資料。在完成資料的合併後，我們使用箭頭與流線的方法將風場繪製出來。

Doppler radars are useful facilities for gathering meteorological data. By analyzing radar data, meteorologists can understand the information about the state of weather, and predict the weather in the future. Therefore, a visualization system dedicated to the post-processing of Doppler radar data is important for weather forecasting and analysis.
In this thesis, we propose a visualization system to visualize the wind field gathered by Doppler radars. We use terrain information to filter out noises. Then, a hierarchical optical flow method is adopted to compute the horizontal wind field. To synchronize the meteorological data scanned by different radar stations with different scanning speeds, we interpolate the wind field by using special Navier Stokes equations. Therefore, we can calculate the vector field data at any time point for each radar. Once the vector field at all time points are available, streamline and glyph images are used to reveal the wind fields.

1. 緒論 1
1.1. 前言 1
1.2. 相關研究 1
1.3. 研究方法簡介與論文結構 3
2. 背景知識介紹 5
2.1. 氣象雷達資料 5
2.2. 光流法 6
2.3. 流線 7
3. 雷達資料重新取樣和濾波 8
3.1. 雜訊濾波器 8
3.2. 建構規則化網格資料 10
4. 估算水平風場 12
4.1. LK METHOD 12
4.2. 使用多層次解析度結構 15
5. 內插風場資料 17
5.1. 風場內插流程 17
5.2. 解NAVIER-STOKES EQUATION 19
5.2.1. 外力與對流 20
5.2.2. 壓力場梯度 21
5.3. 風場內插實作方法 22
5.3.1. 內插範例 23
5.4. 合併多個雷達站的雷達資料 25
6. 實作結果與分析 26
6.1. 風場內插結果與分析 26
6.2. 同步多個雷達站之結果 30
7. 結論與展望 32
7.1. 結論 32
7.2. 展望 32
參考文獻 33

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