颱風的生成發展機制目前尚未能完全被瞭解，因此本研究嘗試分析熱帶雲簇能否發展成為颱風的關鍵海氣環境條件。首先收集洋面上發展雲簇與非發展雲簇個案，應用統計學上的線性判別分析（Linear Discriminant Analysis，LDA）方法，以歸納此兩類雲簇間海氣環境條件的差異性，進而做為颱風生成潛勢之預報參考。
在分類工作上，LDA常用於決定未分類樣本的類別歸屬，實務上則需先建立判別函數（discriminant function）做為分類依據。因此，本研究收集西北太平洋2000年至2009年間的聯合颱風警報中心（JTWC）颱風最佳路徑、全球熱帶雲簇資料庫（Global Tropical Cloud Cluster Dataset），及NCEP Final Analysis（FNL）再分析資料，挑選七項海氣環境參數以建立完整的判別函數。此七項參數分別為：1）850hPa 相對渦度、2）850hPa－200hPa 垂直風切、3）925hPa 輻散值、4）緯度、5）850hPa 相對溼度、6）SSM/I 反演之合成熱能、7）海表面溫度。而後，即可應用LDA方法及所得之判別函數量化歸納出雲簇能發展為颱風的海氣條件閥值。
接下來，再以發生於2010年至2013年間83個獨立颱風個案進行驗證，並將判別函數換算為颱風生成機率分佈圖。本研究結果顯示：若設定60% 發展機率為門檻值，本方法預報發展個案命中率達96.4%，且平均可早於JTWC發佈TS警報前53.1小時發佈颱風生成預警。

Up until now, the mechanisms behind tropical cyclogenesis is still not fully understood. Thus, this study seeks to find the primary air-sea environmental parameters of tropical cloud clusters (TCC) that may eventually lead to the development of a typhoon. First, this study collected data related to developing and nondeveloping TCCs, and applied the linear discriminant analysis (LDA) to analyze the air-sea parameters differences between developing and nondeveloping TCC sets. The thresholds from the differences can thus be used to establish the tropical cyclogenesis potential index (TCPI) for early typhoon formation detection.
LDA is usually used to classify unknown cases to different groups according to discriminant functions. In this study, the Western Pacific JTWC best tracks, global tropical cloud cluster dataset, and NCEP FNL Analyses data are collected and used to establish a comprehensive environmental LDA discriminant function with seven air-sea parameters: 1) 850hPa relative vorticity, 2) 850hPa-200hPa vertical wind shear, 3) 925hPa divergence, 4) latitude, 5) 850hPa relative humidity, 6) SSM/I composite heat energy, and 7) sea surface temperature. Eventually, we can apply the discriminant function established by the historical cases to classify future unknown cases.
Meanwhile, the air-sea environmental thresholds for cyclonegensis from the LDA method are verified by 83 independent typhoon cases that occurred during 2010 to 2013. The discriminant functions are then converted into tropical cyclogenesis probability (TCP) maps. Results show that if the threshold for tropical cyclogenesis probability is set to 60%, the average hit rate of the method is 96.4%, and the average forecast time is roughly 53.1 hours ahead of JTWC’s official tropical cyclone warning.

曾忠一著，大氣衛星遙測學，國立編譯館，臺北市，民國七十七年，630頁。
（美）伊曼紐（Kerry Emanuel）著，颱風，吳俊傑與金棣譯，天下文化書坊，臺灣臺北，民國九十六年，357頁。
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，臺灣中壢。
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，臺灣中壢。
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，臺灣中壢。
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，臺灣中壢。
曾千祐，2010：應用衛星資料估算之熱力與渦度參數建立西北太平洋颱風生成之指標，國立中央大學大氣物理研究所碩士論文，97頁，臺灣中壢。
謝珮倫，2012：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颱風生成，國立中央大學大氣物理研究所碩士論文，94頁，臺灣中壢。
吳戎富，2013：雲簇海氣環境參數差異分析在西北太平洋颱風生成機制之研究，國立中央大學遙測科技碩士學位學程碩士論文，77頁，臺灣中壢。
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.
Briegel, L. M., and W. M. Frank, 1997: Large-scale forcing of tropical cyclogenesis in the Western North Pacific. Mon. Wea. Rev., 125, 1397-1413.
Charney, J. G., and A. Eliassen, 1964: On the growth of the hurricane depression. J. Atoms. Sci., 21, 68-75.
Cheung, K. K. W., 2004: Large-scale environmental parameters associated with tropical cyclone formations in the Western North Pacific. J. Climate, 17, 466-484.
Dare, R. A., and J. L. McBride, 2011: The threshold sea surface temperature condition for tropical cyclogenesis. J. Climate, 24, 4570-4576.
DeMaria, M., 1996: The effect of vertical shear on tropical cyclone intensity change. J. Atoms. Sci., 53, 2076-2087.
DeMaria, M., J. A. Knaff, and B. H. Connell, 2001: A tropical cyclone genesis parameter for the tropical Atlantic. Wea. Forecasting, 16, 219-233.
Emanuel, K. A., 1993: The physics of tropical cyclogenesis over the eastern Pacific. Tropical Cyclone Disasters, J. Lighthill et al., Eds., Peking University Press, 136-142
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.
Ferraro, R. R., 1997: SSM/I derived global rainfall estimates for climatological applications. J. Geophys. Res., 102, 16715-16735.
Frank, N. L., and G. Clark, 1980: Atlantic tropical systems of 1979. Mon. Wea. Rev., 108, 966-972.
Fu, B., M. S. Peng, T. Li, and D. E. Stevens, 2012: Developing versus nondeveloping disturbances for tropical cyclone formation. Part II: Western North Pacific. Mon. Wea. Rev., 140, 1067-1080.
Gray, W. M., 1968: Global view of the origin of the tropical disturbances and storm. Mon. Wea. Rev., 96, 669-700.
Gray, W. M., E. Ruprecht, and R. Phelps, 1975: Relative humidity in tropical weather systems. Mon. Wea. Rev., 103, 685-690.
Gray, W. M., 1979: Hurricanes: Their formation, structure and likely role in the tropical circulation. Meteorology over the Tropical Oceans, D. B. Shaw, Ed., Royal Meteorological Society, 155-218.
Grody, N. C., 1991: Classification of snow cover and precipitation using the Special Sensor Microwave/Imager (SSM/I). J. Geophy. Res., 96, 7423-7435.
Halverson, J. B., J. Simpson, G. Heymsfield, H. Pierce, T. Hock, and L. Ritchie, 2006: Warm core structure of Hurricane Erin diagnosed from high altitude dropsondes during CAMEX-4. J. Atmos. Sci., 63, 309-324.
Hawkins, H. F., and D. T. Rubsam, 1968: Hurricane HILDA, 1964. Mon. Wea. Rev., 96, 617-636.
Hendricks, E. A., and M. T. Montgomery, 2006: Rapid Scan Views of Convectively Generated Mesovortices in Sheared Tropical Cyclone Gustav (2002). Wea. Forecasting, 21, 1041–1050.
Hennon, C. C., and J. S. Hobgood, 2003: Forecasting Tropical Cyclogenesis over the Atlantic Basin Using Large-Scale Data. Mon. Wea. Rev., 131, 2927–2940.
Hennon, C. C., C. N. Helms, K. R. Knapp, and A. R. Bowen, 2011: An objective algorithm for detecting and tracking tropical cloud clusters: implications for tropical cyclogenesis prediction. J. Atmos. Oceanic Technol., 28, 1007-1018.
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.
Kerns, B. W., and S. S. Chen, 2013: Cloud clusters and tropical cyclogenesis: developing and nondeveloping systems and their large-scale environment. Mon. Wea. Rev., 141, 192-210.
Knapp, K. R., M. C. Kruk, D. H. Levinson, H. J. Diamond, and C. J. Neumann, 2010: The international best track archive for climate stewardship (IBTrACS). Bull. Amer. Meteor. Soc., 91, 363-376.
Knapp, K. R., S. Ansari, C. L. Bain, M. A. Bourassa, M. J. Dickinson, C. Funk, C. N. Helms, C. C. Hennon, C. D. Holmes, G. J. Huffman, J. P. Kossin, H.-T. Lee, A. Loew, and G. Magnusdottir, 2011: Globally gridded satellite (GridSat) observations for climate studies. Bull. Amer. Meteor. Soc., 92, 893-907.
Kruk, M. C., K. R. Knapp, and D. H. Levinson, 2010: A technique for combining global tropical cyclone best track data. J. Atmos. Oceanic Technol., 27, 680-692.
Kurihara, Y., and R. E. Tuleya 1974: Structure of a tropical cyclone developed in a three-dimensional numberical simulation model. J. Atmos. Sci., 31,893-919.
Lee, C.-S., Y.-L. Lin, 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.
Leipper, D. F., 1967: Observed ocean conditions and Hurricane Hilda, 1964. J. Atoms. Sci., 24, 182-186.
Lin, I.-I., P. Black, J. F. Price, C.-Y. Yang, S. S. Chen, C.-C. Lien, P. Harr, N.-H. Chi, C.-C. Wu, and E. A. D'Asaro, 2013: An ocean coupling potential intensity index for tropical cyclones. Geophys. Res. Lett., 40, 1878–1882.
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.
Malkus, J. S., and H. Riehl, 1960: On the dynamics and energy transformation in steady-state hurricanes. Tellus, 12, 1-20.
Maloney, E. D., and D. L. Hartmann, 2001: The Madden-Julian oscillation, barotropic dynamics, and North Pacific tropical cyclone formation. Part I: Observations. J. Atoms. Sci., 58, 2545-2558.
McBride, J. L., 1981: Observational Analysis of Tropical Cyclone Formation. Part I: Basic Description of Data Sets. J. Atmos. Sci., 38, 1117–1131.
McBride, J. L., 1995: Tropical cyclone formations. Chapter 3 of Global Perspectives on Tropical Cyclones. Being published by the WMO, 57 pp.
McBride, John L., Raymond Zehr, 1981: Observational Analysis of Tropical Cyclone Formation. Part II: Comparison of Non-Developing versus Developing Systems. J. Atmos. Sci., 38, 1132–1151.
Molinari, J., and D. Vollaro, 2000: Planetary- and synoptic-scale influences on eastern Pacific tropical cyclogenesis. Mon. Wea. Rev., 128, 3296-3307.
Molinari, J., K. Lombardo, and D. Vollaro, 2007: Tropical cyclogenesis within an equatorial Rossby wave packet. J. Atoms. Sci., 64, 1301-1317.
Nelson, D. N., 2013: A statistical approach to understanding and predicting tropical storm formation in the east pacific basin. Doctoral dissertation, University of Wisconsin – Madison, Wisconsin, 172pp.
Ooyama, K. V., 1964: A dynamical model for the study of tropical cyclone development. Geophys. Int., 4, 187-198.
Palmen, E., 1948: On the formation and structure of tropical cyclones. Geophysics, 3, 26-38.
Peng, M. S., B. Fu, T. Li, and D. E. Stevens, 2012: Developing versus nondeveloping disturbances for tropical cyclone formation. Part I: North Atlantic. Mon. Wea. Rev., 140, 1047-1066.
Perrone, T. J., and P. R. Lowe, 1986: A statistically derived prediction procedure for tropical storm formation. Mon. Wea. Rev., 114, 165-177.
Reynolds, R. W., T. M. Smith, C. Liu, D. B. Chelton, K. S. Casey, and M. G. Schlax, 2007: Daily high-resolution-blended analyses for sea surface temperature. J. Climate, 20, 5473-5496.
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.
Rosenthal, R., 1978: Combining results of independent studies. Psychological Bulletin, 85, 185-193.
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.
Sharkov, E. A., 2012: Global Tropical Cyclogenesis. 2nd ed. Springer Press, 604 pp.
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.
Shapiro, L. J., and S. B. Goldenberg, 1998: Atlantic sea surface temperatures and tropical cyclone formation. J. Climate, 11, 578-590.
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.
Stern, D. P., and D. S. Nolan, 2012: On the height of the warm core in tropical cyclones. J. Atmos. Sci., 69, 1657-1680.
Tang, B., and K. Emanuel, 2012: A ventilation index for tropical cyclones. Bull. Amer. Meteor. Soc., 93, 1901-1912.
Wilks, D. S., 2011: Statistical Methods in the Atmospheric Sciences. 3rd ed. Academic Press, 676 pp.
Zhou, Y., W. K. M. Lau, and C. Liu, 2013: Rain characteristics and large-scale environments of precipitation objects with extreme rain volumes from TRMM observations. J. Geophys. Res. Atoms., 118, 9673-9689.