博碩士論文 966201003 詳細資訊




以作者查詢圖書館館藏 以作者查詢臺灣博碩士 以作者查詢全國書目 勘誤回報 、線上人數:4 、訪客IP:34.204.189.171
姓名 蔡金成(Chin-cheng Tsai)  查詢紙本館藏   畢業系所 大氣物理研究所
論文名稱 衛星資料與虛擬渦旋四維變分同化對颱風數值模擬的影響
(The Impact of 4DVAR with Satellite and Bogus Vortex Data on Typhoon Simulation)
相關論文
★ 雲微物理參數化法應用於颱風模式中之研究★ 1998年臺灣梅雨個案模擬及其應用 -蘭陽平原之擴散研究
★ 地形對颱風路徑的影響之數值探討★ 中尺度MM5數值模式與大氣擴散模式之整合應用研究
★ 侵台颱風之GPS折射率3DVAR資料同化及數值模擬★ 地形及渦旋初始化對類似納莉颱風路徑及環流變化之影響
★ 類似桃芝颱風路徑之模擬★ WRF模式在颱風路徑預報應用與EOF分析誤差因素
★ 利用WRF3DVAR同化GPS折射率資料探討 對於颱風預報的影響★ 衛星資料結合變分分析對數值預報之影響
★ 利用MM5 4DVAR模式同化掩星折射率資料及虛擬渦旋探討颱風數值模擬之影響★ 利用MM5 4DVAR同化虛擬渦旋探討其對WRF模式預報颱風之影響
★ GPS掩星觀測資料同化及對區域天氣預報模擬之影響★ 西北向侵台颱風登陸前中心路徑打轉之模擬研究
★ 資料同化對台灣地區颱風和梅雨模擬之影響★ 聖帕颱風模擬的位渦反演之診斷分析
檔案 [Endnote RIS 格式]    [Bibtex 格式]    [相關文章]   [文章引用]   [完整記錄]   [館藏目錄]   [檢視]  [下載]
  1. 本電子論文使用權限為同意立即開放。
  2. 已達開放權限電子全文僅授權使用者為學術研究之目的,進行個人非營利性質之檢索、閱讀、列印。
  3. 請遵守中華民國著作權法之相關規定,切勿任意重製、散佈、改作、轉貼、播送,以免觸法。

摘要(中) 本研究以The Fifth-Generation NCAR / Penn State Mesoscale Model (MM5)並利用四維變分資料同化方法(4DVAR),同化衛星與虛擬渦旋資料,模擬2008年卡玫基颱風。資料同化所使用的三種衛星觀測資料,包括:Special Sensor Microwave Imager (SSM/I)垂直水氣積分(Integrated Water Vapor)與海面風速資料(Ocean Wind Speed)及Constellation Observing System for Meteorology Ionosphere & Climate (COSMIC)折射率(Refractivity)資料,期望同化觀測點分布較廣的衛星資料可對模式大氣有較大範圍之修正。經過同化虛擬渦旋之後,可在初始颱風環流中高層得到暖心結構、颱風中心附近亦有水氣輻合,同時能夠有較準確的颱風中心定位,進而改善颱風路徑與強度之模擬。
模擬實驗分為三組,第一組實驗中分別同化不同衛星資料,結果顯示,單獨同化衛星資料無法有效改善颱風的模擬路徑與強度。第二組實驗則只同化虛擬渦旋,當加入虛擬渦旋後可明顯改善卡玫基颱風在第二天與第三天之模擬路徑誤差。第三組實驗,在4個小時的同化窗區內,同時同化衛星與虛擬渦旋資料。實驗結果顯示,同化虛擬渦旋與COSMIC折射率資料,對於駛流場有較大之修正而更降低路徑誤差。當虛擬渦旋再加入同化SSM/I海面風速資料,則能夠維持颱風底層風場進而增加海氣交互作用產生較多潛熱,提供颱風發展較佳的環境條件。同化虛擬渦旋與垂直水氣積分之模擬,因水氣場受到修正,造成颱風的不對稱結構而影響颱風後期發展。
摘要(英) This study uses MM5 4DVAR to assimilate bogus vortex and satellite data to simulate Typhoon Kalmaegi (2008). There are three types of satellite data assimilated in the experiments. They are Special Sensor Microwave Imager (SSM/I) integrated water vapor (IWV), ocean wind speed (OWS) and Constellation Observing System for Meteorology Ionosphere & Climate (COSMIC) refractivity (REF) data. After applying bogus vortex data assimilation (BDA) based on 4DVAR, a cyclonic circulation with a warm core in the upper troposphere is produced. Moreover, moisture convergence near the typhoon center is induced and the location of the typhoon center is more accurate. Consequently, the simulated track and intensity of Kalmaegi (2008) were improved in these experiments with BDA.
Three group experiments are designed to study the impact of different observations. In the first group experiment, SSM/I IWV, OWS and COSMIC REF are assimilated into the Kalmaegi case individually. However, there is no significant impact on Kalmaegi simulation when applying satellite data only. In the second group experiment, only the bogus vortex data are assimilated. When assimilating the bogus vortex data, a great improvement on the track simulation is found, especially after 24 simulation hours. The third group experiment assimilates not only bogus vortex data but also different satellite data. The results indicate that the bogus vortex with REF data leads to an adjustment of the steering flow and successfully improves the simulated track. On the other hand, the assimilation of the bogus vortex with SSM/I OWS data can enhance the low-level wind, resulting in more latent heating. Therefore, it generates an environment more favorable for typhoon development. However, the simulation with assimilation of SSM/I IWV causes the correction of water vapor. In simulation of Typhoon Kalmaegi, such correction results in a more asymmetric structure of wind field and latent heat flux which appears to weaken the typhoon intensity.
關鍵字(中) ★ 四維資料同化
★ 虛擬渦旋
關鍵字(英) ★ 4DVAR
★ BDA
論文目次 中文摘要…………………………………………………………………… i
英文摘要…………………………………………………………………… ii
誌謝………………………………………………………………………… iv
目錄………………………………………………………………………… v
圖表說明…………………………………………………………………… vi
第一章、前言
1.1 動機…………………………………………………………… 1
1.2 文獻回顧與研究目的………………………………………… 3
第二章、模式系統與資料處理
2.1 模式系統 …………………………………………………… 6
2.2 SSM/I 垂直水氣積分與海面風速…………………………… 7
2.3 GPS 掩星觀測與折射率……………………………………… 9
2.4 虛擬渦旋……………………………………………………… 12
第三章、實驗設計與模擬結果
3.1 個案介紹……………………………………………………… 14
3.2 實驗設計……………………………………………………… 15
3.3 同化衛星資料模擬結果……………………………………… 16
3.4 同化虛擬渦旋模擬結果……………………………………… 16
3.5 同化虛擬渦旋與衛星資料模擬結果………………………… 19
第四章、虛擬渦旋敏感度實驗
4.1 虛擬渦旋垂直層數測試……………………………………… 26
4.2 虛擬渦旋同化窗區測試……………………………………… 28
第五章、總結與未來展望 ………………………………………………… 30
參考文獻 …………………………………………………………………… 34
附錄 ………………………………………………………………………… 37
附表與附圖 ………………………………………………………………… 40
參考文獻 王潔如,2004:侵台颱風之GPS 折射率3DVAR 資料同化及數值模擬。國立中央大學,大氣物理研究所,碩士論文,108 頁。
吳俊澤,2007:利用MM5 4DVAR 模式同化掩星折射率資料及虛擬渦旋探討颱風數值模擬之影響。國立中央大學,大氣物理研究所,碩士論文,70 頁。
周昆炫,2003:颱風渦旋初始化之觀測系統模擬實驗研究。國立台灣大學,大氣科學系,博士論文,120 頁。
周鑑本,2006:衛星資料結合變分分析對數值預報之影響。國立中央大學,大氣物理研究所,博士論文,115 頁。
陳舒雅,2008:GPS掩星觀測資料同化及對區域天氣預報模擬之影響。國立中央大學,大氣物理研究所,博士論文,137頁
黃清勇、朱延祥,2004:FORMOSAT-3/COSMIC 科學研究簡介。大氣科學,32,293-328。
曾忠一,2006:大氣科學中的反問題。 國立編譯館主編及出版,1288頁。
Chen, S.-H., 2007: The impact of assimilating SSM/I and QuikSCAT satellite winds on hurricane Isidore simulations. Mon. Wea. Rev., 135, 549–566.
Chen, S.-H., F. C. Vandenberghe, G. W. Petty, and J.F. Bresch, 2004: Application of SSM/I satellite data to a hurricane simulation. Quart. J. Roy. Meteor. Soc., 130, 801-825.
Fujita, T., 1952: Pressure distribution within a typhoon. Geophys. Mag., 23, 437-451.
Guo, Y.-R., Y.-H. , Kuo, J. Dudhia, D. Parsons, and C., Rocken, 2000:Four-dimensional variational data assimilation of heterogeneous mesoscale observations for a strong convective case. Mon. Wea. Rev., 128, 619-643.
Healy, S. B., and J.-N. Thepaut, 2006: Assimilation experiments with CHAMP GPS radio occultation measurements. Quart. J. Roy. Meteor. Soc., 132, 605-623
Huang, C.-Y., Y.-H. Kuo, S.-H. Chen and F. Vandenberghe, 2005: Improvements on typhoon forecast with assimilated GPS occultation refractivity. Wea. Forecasting, 20, 931-953.
Kuo, Y.-H., S. V. Sokolovskiy, R. A. Anthes, and F. Vandenberghe, 2000: Assimilation of GPS radio occultation data for numerical weather prediction. Terr. Atmos. Oceanic Sci., 11, 157-186.
Kuo, Y.-H., T.-K. Wee, S. Sokolovskiy, C. Rocken, W. Schreiner, D. Hunt, and R.A. Anthes, 2004 : Inversion and error estimation of GPS radio occultation data. J.Meteor. Soc. Japan, 82, 507-531.
Kurihara, Y., M. A. Bender, R. E. Tuleya, and R. J. Ross, 1995: Improvements in the GFDL hurricane prediction system. Mon. Wea. Rev., 123, 2791-2801.
Kursinki, E. R.,G. A. Hajj, K. R. Hardy, L. J. Romans, and J. T. Schofield, 1995: Observing tropospheric water vapor by radio occultation using the global positioning system. Geophys. Res. Letter, 22, 2365-2368.
Neumann, C. J., 1993: Global overview. Chapter 1, Global Guide to Tropical Cyclone Forecasting. WMO, 1.1-1.56.
Park, K., and X. Zou, 2004: Toward developing an objective 4DVAR BDA scheme for hurricane initialization based on TPC observed parameters. Mon. Wea. Rev., 132, 2054–2069.
Thayer, D., 1974: An improved equation for the radio refractive index of air. Radio Sci., 9, 803-807.
Wentz, F. J., 1993: manual SSM/I antenna temperature tapes revision 2. RSS Tech. Rep. 120193, Remote Sensing Systems, Santa Rosa, CA, 13 pp.
Wu, C.-C., K.-H. Chou, Y. Wang and Y.-H. Kuo, 2006: Tropical cyclone initialization and prediction based on four-dimensional variational data assimilation. J. Atmos. Sci., 63, 2383–2395.
Wu, C.-C., and Coauthors, 2005: Dropwindsonde Observations for Typhoon Surveillance near the Taiwan Region (DOTSTAR): An overview. Bull. Amer. Meteor. Soc., 86, 787-790.
Xiao, Q., X. Zou, and B. Wang, 2000: Initialization and simulation of a landing hurricane using a variational bogus data assimilation scheme. Mon. Wea.Rev., 128, 2252-2269.
Zhang, X., Q. Xiao, and P.J. Fitzpatrick, 2007: The impact of multisatellite data on the initialization and simulation of Hurricane Lili’s (2002) rapid weakening phase. Mon. Wea. Rev., 135, 526–548.
Zou, X., Y.-H. Kuo, and Y.-R. Guo, 1995: Assimilation of atmospheric radiorefractivity using a nonhydrostatic adjoint model. Mon. Wea. Rev., 123, 2229-2249.
Zou, X., and Q. Xiao, 2000: Studies on the initialization and simulation of a mature hurricane using a varitional bogus data assimilation scheme. J. Atmos. Sci., 57, 836-860.
Zou, X.,W. Huang and Q. Xiao, 1997: A user’s guide to the MM5 adjoint modeling system. NCAR TN-437+IA. MMM division, NCAR, 92pp.[Available from UCAR Communications, P.O. Box 3000, Boulder, CO80307.]
指導教授 黃清勇(Ching-yuang Huang) 審核日期 2009-7-14
推文 facebook   plurk   twitter   funp   google   live   udn   HD   myshare   reddit   netvibes   friend   youpush   delicious   baidu   
網路書籤 Google bookmarks   del.icio.us   hemidemi   myshare   

若有論文相關問題,請聯絡國立中央大學圖書館推廣服務組 TEL:(03)422-7151轉57407,或E-mail聯絡  - 隱私權政策聲明