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姓名 謝珮倫(Pei-lun Hsieh) 查詢紙本館藏 畢業系所 大氣物理研究所 論文名稱 應用衛星資料估算之熱力參數與ECMWF再分析資料監測西北太平洋熱帶氣旋生成
(Monitoring Tropical Cyclone Formation in the Northwest Pacific withSatellite-Derived Thermal Parameter and ECMWF Reanalysis Data)相關論文 檔案 [Endnote RIS 格式]
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摘要(中) 熱帶氣旋生命期大多發生於洋面上，故衛星遙測資料有助於熱帶氣旋監測。前人研究曾利用SSM/I微波資料與QuikSCAT風速風向資料建立熱力與動力指標以監測南海及西北太平洋區域熱帶氣旋之生成，其準確預報率很高，惟未進一步量化分析是否有誤判情況發生，故本研究參考Schumacher et al. (2009)分析方法，使用六項熱帶氣旋生成判斷條件，以逐步去除不利其生成位置，期望得到較準確且誤判率較少的熱帶氣旋可能生成區域。
本研究選用2001～2008年西北太平洋地區204個熱帶氣旋個案，以其中2/3個案建立熱帶氣旋生成條件，其餘1/3個案則做為驗證，再以2009年與2010兩年獨立個案進行分析。本研究挑選850hPa渦度閾值、850hPa渦度差異場、合成熱能閾值、合成熱能差異場、海表面溫度以及500hPa、700hPa、850hPa三個壓力層的相對溼度等六種判斷條件做為颱風生成的指標，並以預報得分進行評估。由2001～2008年1/3個案驗證結果顯示，使用4.5°×4.5°監測方框與滿足任五種熱帶氣旋生成判斷條件監測熱帶氣旋生成為較佳組合，可成功預測熱帶氣旋生成位置的比率約為60%，誤報生成位置的比率則為5%～6%；2009年個案分析顯示成功預報率約為50%，略低於2001～2008年之預報結果；然而2010年的14個TS個案則因有6個個案生成於陸地附近海域，導致其預報準確度明顯降低。進一步分析顯示本研究預報方法的準確度皆優於氣候法與使用曾（2010）研究閾值之預報結果。
摘要(英) The lifecycle of tropical cyclones mostly occur over the open ocean. Therefore, satellite remote sensing data is a viable tool for detecting the development of tropical cyclones. Some researches have employed SSM/I microwave satellite data to derive the heat energy. Meanwhile, QuikSCAT satellite data have been employed to derive the wind field data in establishing the thermal and vorticity thresholds, and monitoring the formation of tropical cyclones in Northwest Pacific and South China Sea. In previous studies, although the predictions of tropical cyclone formations were accurately made, there were also many false alarms. As a result, this study will use 6 different tropical cyclone formation parameters ( vorticity threshold, vorticity difference, thermal energy threshold, thermal energy difference, sea surface temperature and relative humidity) to remove the highly unfavorable tropical cyclone formation areas in attempting to find the probabilistic formation area of tropical cyclones.
This study selected 204 tropical cyclones cases during 2001-2008 in the Northwest Pacific. Two-thirds of these cases are used to establish the formation thresholds, while the remaining one-third is regarded as dependant cases for verification. Separately, 28 independent cases during 2009-2010 were used for verification. The skill score results show that utilization of the 5 formation parameters and 4.5 degree detecting was suitable for monitoring tropical cyclone formation. The prediction accuracy reached 60% and 5-6% for the false alarm ratio in 2001-2008. In 2009, the prediction accuracy reached 50%, which was smaller than dependant cases. However in 2010, as 6 cases formed near island, the prediction accuracy was lower in contrast to other years. Compared with Climatology and the method of Tzeng (2010), this study is shown to have a better prediction accuracy in tropical cyclone formation.
關鍵字(中) ★ 預報得分
★ 衛星遙測
★ 颱風
★ 熱帶氣旋關鍵字(英) ★ Skill score
★ Remote sensing
★ Tropical cyclone formation
★ Typhoon論文目次 摘要 ......................................................................................................... i
Abstract .................................................................................................. ii
致謝 ....................................................................................................... iii
目錄 ....................................................................................................... iv
表目錄 ................................................................................................... vi
圖目錄 .................................................................................................. vii
第一章 緒論 ........................................................................................ 1
1.1 前言 ........................................................................................ 1
1.2 文獻回顧 ................................................................................. 2
1.3 研究目的 ................................................................................. 5
第二章 資料介紹 ................................................................................ 6
2.1 衛星微波資料 .......................................................................... 6
2.1.1 可感熱通量與潛熱通量 ......................................................... 7
2.1.2 潛熱釋放量 ..................................................................... 8
2.1.3 合成熱能 ...................................................................... 10
2.2 ECMWF ERA-Interim 再分析資料 ......................................... 11
2.3 紅外線衛星影像 ...................................................................... 11
2.4 JTWC最佳路徑資料 ............................................................. 13
2.5 研究範圍介紹 ........................................................................ 13
第三章 研究方法 ...............................................................................15
3.1 大氣環境差異場分析 ............................................................. 15
3.1.1 850hPa 渦度差異場 ..................................................... 15
3.1.2 合成熱能差異場 ............................................................ 17
3.2 生成閾值分析 ........................................................................ 18
3.2.1 850hPa 渦度閾值 ........................................................ 18
3.2.2 合成熱能閾值 ............................................................... 19
3.3 熱帶氣旋生成判斷方式 .......................................................... 20
3.4 統計得分方法 ........................................................................ 21
第四章 結果與討論 ............................................................................25
4.1 2001年至2008年1/3個案監測結果驗證 ............................. 25
4.1.1 熱帶氣旋滿生成滿足條件比較 ...................................... 26
4.1.2 監測方框比較 ............................................................... 27
4.1.3 使用曾（2010）閾值預報結果比較 .............................. 27
4.2 2009年與2010年預報結果討論 ........................................... 28
4.3 熱帶氣旋生成個案分析 .......................................................... 29
4.4 綜合討論 ............................................................................... 35
第五章 結論與展望 ............................................................................37
參考文獻 ..............................................................................................39
參考網站 ..............................................................................................44
參考文獻 劉崇治與劉振榮，2000：應用衛星資料在梅雨季海上中尺度對流系統生成前兆之初步探討。大氣科學，第二十八期，第四號，317-341 頁。
藍嘉偉，2006：利用HHT 之EMD 方法分析SSM/I 資料估算之客觀指數與颱風強度年際變化關係，國立中央大學大氣物理研究所碩士論文，114 頁，台灣中壢。
劉嘉騏，2007：應用SSM/I 衛星資料分析颱風形成之激發機制，國立中央大學大氣物理研究所碩士論文，92 頁，台灣中壢。
林欣怡，2008：應用衛星資料反演之海氣能量參數分析年際大氣環境差異對颱風生成條件之影響，國立中央大學大氣物理研究所碩士論文，108頁，台灣中壢。
賴勇瑜，2009：應用衛星資料反演之熱力及動力參數分析南海地區熱帶低壓之生成機制，國立中央大學大氣物理研究所碩士論文，96 頁，台灣中壢。
曾千佑，2010：應用衛星資料估算之熱力與渦度參數建立西北太平洋熱帶氣旋生成之指標，國立中央大學大氣物理研究所碩士論文，97 頁，台灣中壢。
Alliss, R. J., S. Raman, and S. W. Chang, 1992: Special Sensor Microwave /Imager (SSM/I) observations of Hurricane Hugo (1989). Mon. Wea. Rev., 120, 2723-2737.
Bessho, Kotaro, Tetsuo Nakazawa, Shuji Nishimura, Koji Kato, 2010: Warm core structures in organized cloud clusters developing or not developing into tropical storms observed by the Advanced Microwave Sounding Unit. Mon. Wea. Rev., 138, 2624–2643.
Black, P. G., and L. K. Shay, 1998: Observations of tropical cyclone intensity change due to air-sea interaction processes. Preprint, Symp. on Tropical Cyclone Intensity Change, Phoenix, AZ, Amer. Meteor. Soc., 161-168.
Dare, Richard A., John L. McBride, 2011: The threshold sea surface temperature condition for tropical cyclogenesis. J. Climate, 24, 4570–4576.
Davis, C. A.,and L. F. Bosart, 2001: Numerical simulations of the genesis of Hurricane Diana (1984). Part I: Control simulation. Mon. Wea. Rev., 129, 1859-1881.
Ferraro, R.R., 1997: SSM/I derived global rainfall estimates for climatological applications. J. Geophys. Res., 102, 16,715-16,735.
Ferraro, R. R.,and G. F. Marks, 1995: The development of SSM/I rain-rate retrieval algorithms using ground-based radar measurement. J. Atmos. Oceanic Technol., 12, 755-770.
Goodberlet, M. A., C. T. Swift, 1992: Improved retrievals from the DMSP wind speed algorithm under adverse weather conditions. IEEE Trans.Geosci. Remote Sensing, 30, 1076-1077.
Gray, W. M., 1968: Global view of the origin of the tropical disturbances and storm. Mon. Wea. Rev., 96, 669-700.
Grody, N. C., 1991: Classification of snow cover and precipitation using the Special Sensor Microwave/Imager (SSM/I). J. Geophy. Res., 96, 7423-7435.
Hennon, Christopher C., Caren Marzban, Jay S. Hobgood, 2005: Improving tropical cyclogenesis statistical model forecasts through the application of a neural network classifier. Wea. Forecasting, 20, 1073–1083.
Hilburn, K. A., and F. J. Wentz, 2008: Mitigating the impact of RADCAL beacon contamination on F15 SSM/I ocean retrievals. Geophys. Res. Lett., 35, L18806.
Katsaros, K. B., E. B. Forde, P. Chang and W. T. Liu, 2001: QuikSCAT’s Sea-Winds facilitates early identification of tropical depressions in 1999 hurricane season. Geophys. Res. Lett., 28, 1043-1046.
Lee, C.-S., Y.-L. Lin, and K. K. W. Cheung, 2006: Tropical cyclone formations in the South China Sea associated with the Mei-yu front. Mon. Wea. Rev., 134, 2670-2687.
Liu, G.-R., C.-C. Liu, and T.-H. Kuo, 2001: A contrast and comparison of near-sea surface air temperature/humidity from GMS and SSM/I data with an improved algorithm. IEEE Trans. Geosci. Remote Sens, 39, 2148-2157.
Liu, G.-R., C.-C. Liu and T.-H. Kuo, 2002: A satellite-derived Objective Potential Index for MCS development during the Mei-yu period. J. Meteor. Soc. Japan., 80, 503-517.
Lowag, A., M. L. Black, M. D. Eastin, 2008: Structural and intensity changes of Hurricane Bret (1999). Part I: Environmental influences. Mon. Wea. Rev., 136, 4320-4333.
McBride, J. L., 1995: Tropical cyclone formation. Global Perspectives on Tropical cyclones, WMO Tech Doc. 693, World Meteorological Organization, 63-105.
Rodgers, E. B., and R. F. Adler, 1981: Tropical cyclone rainfall characteristics as determined from a satellite passive microwave radiometer. Mon. Wea. Rev., 109, 506-521.
Rodgers, E. B., and H. F. Pierce, 1995: A satellite observational study of precipitation characteristics in Western North Pacific tropical cyclones. J. Appl. Meteor., 34, 2587-2599.
Rodgers, E. B.,W. Olson, J. Halverson, J. Simpson, and H. Pierce, 2000: Environmental forcing of Supertyphoon Paka’s (1997) latent heat structure. J. Appl. Meteor., 39, 1983-2006.
Schumacher, A. B., M. DeMaria, and J. A. Knaff, 2009: Objective estimation of the 24-h probability of tropical cyclone formation. Wea. Forecasting, 24, 456-471.
Shay, L. K., G. J. Goni, and P. G. Black, 2000: Effect of a warm oceanic feature on Hurricane Opal. Mon. Wea. Rev., 128, 1366-1383.
Sharp, B. J., M. A. Bourassa, and J. J. O’Brien, 2002: Early detection of tropical cyclones using seawinds-derived vorticity. Bull. Amer. Meteor Soc., 83, 879-889.
Wilks, D. S., 2006: Statistical Methods in the Atmospheric Sciences.2nd ed. Academic Press, 467 pp.
指導教授 劉振榮(Gin-rong Liu) 審核日期 2012-7-26 推文 plurk
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