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研究生:林妗庭
研究生(外文):Jin-Ting Lin
論文名稱:WRF 4DVAR 虛擬渦旋及雷達資料同化對於颱風凡那比 (2010) 數值模擬之影響
論文名稱(外文):The impact of bogus vortex and radar data assimilation of typhoon Fanapi (2010) using WRF 4DVAR
指導教授:黃清勇黃清勇引用關係
指導教授(外文):Ching-Yuang Huang
學位類別:碩士
校院名稱:國立中央大學
系所名稱:大氣物理研究所
學門:自然科學學門
學類:大氣科學學類
論文種類:學術論文
論文出版年:2012
畢業學年度:100
語文別:中文
論文頁數:92
中文關鍵詞:WRF 四維變分資料同化凡那比颱風(2010)
外文關鍵詞:Fanapi(2010)WRF 4DVAR
相關次數:
  • 被引用被引用:3
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  • 下載下載:27
  • 收藏至我的研究室書目清單書目收藏:0
摘要
本研究為國內首次利用WRF 4DVAR (Weather Research and Forecasting four-dimensional variational data assimilation system) 探討同化虛擬渦旋及氣象雷達資料 (五分山、七股、墾丁、花蓮等四個雷達) 對於颱風凡那比 (2010) 模擬的影響。實驗設計以cold start及hot start分別使用不同的背景誤差 (cv3及cv5) 進行同化,討論四維變分資料同化對於颱風凡那比 (2010) 初始場修正及模擬的影響。此外,也於同化虛擬渦旋實驗中測試水平影響尺度對於同化分析場及模擬的影響。
經由四維變分資料同化虛擬渦旋,可以修正颱風凡那比的中心位置,改善颱風的強度及結構,使環流結構更為完整。同化過程中使用背景誤差cv3對於模式初始場會造成大範圍的修正,若使用背景誤差cv5,修正範圍明顯集中於植入虛擬渦旋處,兩者在路徑模擬上cv5明顯優於cv3,但仍不及未同化虛擬渦旋之實驗。不同的水平影響尺度測試實驗顯示,降低水平影響尺度能縮小同化修正的範圍,在本研究中降低水平影響尺度對於背景誤差cv3之同化模擬可降低路徑誤差。
同化雷達資料的部份在cold start實驗路徑模擬中,使用背景誤差cv5之路徑北偏,而cv3於未登陸台灣前於外海打轉,兩者移動速度緩慢,路徑誤差高。hot start實驗中,使用背景誤差cv3或cv5經雷達資料同化後,路徑模擬都有不錯的表現,cv3更在模擬24小時後路徑誤差低於未同化的模擬,改善路徑模擬誤差約23%,而同化對於路徑影響的原因有待未來作更進一步的探討。
Abstract
This study uses the Weather Research and Forecasting (WRF) model and its four-dimensional variational data assimilation system (4DVAR) to improve the model initial conditions for numerical simulations. A series of experiments were conducted to investigate the impact of bogus vortex and radar reflectivity and radial wind from Wufenshan, Cigu, Kenting and Hualien Weather Radars on assimilation of typhoon Fanapi (2010) using WRF 4DVAR. Both cold start and hot start experiments are compared, with different background errors (cv3 and cv5). In addition, we investigate the effect of reducing the horizontal scale of influence in 4DVAR. To better understand the performance of WRF 4DVAR, the model increments at the initial time and 48-h typhoon track forecasts were analyzed.
The assimilation results demonstrate that bogus data assimilation tends to intensify the initial typhoon and better relocate the typhoon center of Fanapi, but does not improve the track effectively. The initial analysis using cv3 was modified more widely compared to that using cv5. Consequently, cv5 is better than cv3 in the track simulation. The experiment with a reduced horizontal scale of influence in 4DVAR with cv3 shows that the lateral range of initial increment is reduced and leads to smaller track prediction errors.
Radar data assimilation results are associated with higher tracking errors in the cold start experiment. However, the track prediction is improved by 23 % in the hot start experiment, as compared to the simulation without radar data assimilation.
目錄
摘要....................I
Abstract...............II
目錄....................IV
圖表目錄.................V
第一章、前言.............. 1
1-1研究動機..............1
1-2文獻回顧與研究目的......2
第二章、模式系統與研究設定...7
2-1 模式系統與研究設定......7
2-2 四維變分資料同化系統.....8
2-3 背景誤差..............10
第三章、個案及資料介紹.......12
3-1 個案介紹..............12
3-2虛擬渦旋...............13
3-3雷達資料...............16
第四章、 虛擬渦旋及雷達資料同化對颱風模擬之影響...18
4 - 1同化虛擬渦旋-初始場修正與颱風模擬分析.......19
4-1-1同化虛擬渦旋-cold start實驗.............19
4-1-2同化虛擬渦旋-hot start實驗..............23
4-1-3同化虛擬渦旋-cv3水平影響尺度測試 ..........26
4-1-4同化虛擬渦旋-cv5水平影響尺度測試 ..........28
4-2同化雷達資料-初始場修正與颱風模擬分析.........30
4-2-1同化雷達資料-cold start實驗..............31
4-2-2同化雷達資料-hot start實驗...............32
第五章、結論與未來展望.........................35
參考文獻.....................................40
附表與附圖...................................43
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