博碩士論文 93621002 詳細資訊




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姓名 藍嘉偉(Chia-Wei Lan)  查詢紙本館藏   畢業系所 大氣物理研究所
論文名稱 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
(Using the Empirical Mode Decomposition of Hilbert-Huang Transform to analyse the relationship between the annual typhoon intensity and Objective Potential Index estimated by SSM/I data.)
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摘要(中) 台灣每年所遭受的天然災害中最嚴重的就為颱風的侵襲,大多數颱風帶來的災害不是風所造成,而是颱風所夾帶的大量降雨引發土石流及水災。儘管政府每年投資大筆經費進行颱風的各項研究與天然災害的預防,但極少數的研究是針對颱風年際強度問題來探討,因此本研究將針對南海與西北太平洋地區颱風年際強度變化來加以研究並找出其與海洋間的相互關係。
本研究利用Huang and Coauthors(1998)所提出的希伯特-黃轉換中的經驗模態分解法來分析Liu, Liu, and Kuo(2002)提出的海氣參數及估算出來的客觀指數,首先針對兼具颱風強度與生命期的颱風破壞潛勢(HDP)進行經驗模態分解法分析,接著針對能夠代表海氣交互能量的各海氣參數與客觀指數進行經驗模態分解法分析,最後建立客觀指數經過經驗模態分解法分析後的各內建模態函數(IMF)與HDP的線性相關性。
結果顯示在南海地區的颱風強度年際變化均值趨勢與西北太平洋地區是不相同的,但西北太平洋的年際變化均值趨勢則與Emanuel(2005)相同。而各海氣參數與客觀指數的經驗模態分解法分析後,具有明顯的年變化週期,其餘的內建模態函數則尚未發現其與大氣間的相關性。不管在南海或西北太平洋地區,皆可發現從前年的十月至當年的三至四月中,客觀指數的第四個內建模態函數與當年的颶風破壞潛勢有相對於其他月分與其他內建模態函數來的高,在西北太平洋地區最高的R^2值甚至可以高達0.7左右。且OPI的第四個Mode與Southern Oscillation Index(SOI)有些許反相位的關係,所以當SOI為負值(聖嬰事件)時OPI則有較大的值,表示海洋提供較多能量至大氣中以致於颱風發展較強,因而造成較大的HDP值。
在未來累積一定資料量後,此研究的線性關係結果可以做為未來估算當年颱風強度的一個依據或指標。
摘要(英) Taiwan was attacked by many typhoons every year before. Most damages were not caused by gust wind. Instead, they were caused by the landslides and flood which were leaded by heavy rain. Although our government invested much money in studies about typhoon and disaster protection, there were few scientists aimed at studying annual typhoon intensity. Therefore, our study is about annual typhoon intensity. Meanwhile, we want to find out the relationship between annual typhoon intensity and the air-sea interaction in South China Sea and Western North Pacific Ocean.
In our study, we use Empirical Mode Decomposition (EMD) which is one part of Hilbert-Huang Transform (HHT) suggested by Huang and Coauthors in 1998, to analyze Objective Potential Index (OPI) suggested by Liu et al. in 2002. At first, we analyze the Hurricane Destruction Potential (HDP) which combines the life of typhoon and typhoon intensity by using EMD. Secondly, EMD is also used to analyze the air-sea parameters and OPI. At last, we establish the linear correlation between each Intrinsic Mode Function (IMF) of OPI and HDP.
The results show the mean trend of annual typhoon intensity in Western North Pacific Ocean is the same as the mean trend suggested by Emanuel in 2005, but in South China Sea, we have the contrary results. After each parameter and OPI were separated by using EMD, we can see the annual cycle observably, but it is not easy to understand the atmospheric properties of other IMFs. Whether in South China Sea or in Pacific Ocean region, we could find higher R^2 between OPI in IMF4 and HDP. And R^2 was higher in the months from the last October to that April. Even the value in Western North Pacific Ocean could be as high as more than 0.7. Moreover, we find that the southern oscillation index (SOI) show an slightly antiphase with OPI in IMF4. Therefore, the negative SOI value shows that higher OPI value, and means that ocean supplies more energy into atmosphere and results in stronger typhoons.
In the future, if more data is recorded, the results of this study could be an index to estimate typhoon intensity that year.
關鍵字(中) ★ HHT/EMD
★ 客觀潛力指數
★ SSM/I
關鍵字(英) ★ Objective Potential Index
★ HHT/EMD
★ SSM/I
論文目次 摘要. I
Abstract III
目錄 IV
表目錄 VIII
圖目錄 X
第一章 緒論 1
1.1 前言 1
1.2 文獻回顧 3
1.3 研究目的 7
第二章 基礎理論 9
2.1 傅利葉轉換(Fourier Transform) 9
2.2 希伯特-黃轉換(Hilbert-Huang Transform) 10
2.2.1經驗模態分解法(Empirical Mode Decomposition) 11
2.2.2希伯特轉換(Hilbert Transform) 13
2.3微波頻譜與微波輻射傳送方程 15
2.4颶風破壞潛勢 17
第三章 衛星儀器介紹與資料來源 20
3.1 SSM/I衛星資料 20
3.2 JTWC資料 22
3.3 資料來源與資料範圍 23
第四章 研究方法與過程 24
4.1 SSM/I衛星資料之前期處理 24
4.2 海氣參數反演方法 24
4.3 客觀指數(Object Potential Index, OPI)計算方法 27
4.4 海氣參數與OPI之月平均與空間範圍平均 29
4.4.1 南海地區 29
4.4.2 西北太平洋地區 30
4.5 FFT處理方式 31
4.6 EMD處理方式 31
4.7 HDP計算方式 32
第五章 結果分析與討論 33
5.1 JTWC歷年南海與西北太平洋地區颱風生成個數與HDP 33
5.1.1 南海地區 33
5.1.2 西北太平洋地區 34
5.2 歷年南海與西北太平洋HDP之FFT頻譜與EMD分析 35
5.2.1南海地區 35
5.2.2 西北太平洋地區 36
5.3 1997.02~2004年南海、西北太平洋地區海氣參數之EMD分析結果 39
5.3.1南海地區 39
5.3.2西北太平洋地區 40
5.4 1997.02~2004年南海、西北太平洋地區客觀指數之EMD分析結果 40
5.4.1南海地區 40
5.4.2西北太平洋地區 41
5.5 OPI、海氣參數、HDP之EMD分析結論 41
5.6 1997.02~2005.07各年南海、西北太平洋地區海氣參數及OPI之年變化 42
5.6.1南海地區 42
5.6.2西北太平洋地區 45
5.7各月OPI年變化與南海、西北太平洋地區 HDP及HDP均值趨勢線性回歸分析結果 45
5.7.1 南海地區 45
5.7.2 西北太平洋地區 47
5.7.3 颱風季過後各月客觀指數平均與HDP線性回歸分析結果 48
5.8 OPI之EMD分析各IMF與HDP原始訊號線性回歸分析 49
5.9 OPI-IMF4之大氣物理特性分析 50
第六章 結論與未來展望 52
參考文獻 57
附表 62
附圖 71
參考文獻 曾忠一, 1988:大氣衛星遙測學。渤海堂出版社,630頁。
黃曉薇, 2000:應用SSM/I衛星資料於西太平洋颱風特性之分析。國立中央大學大氣物理研究所碩士論文,95頁。
郭家利, 2001:應用衛星資料於熱帶氣旋之環境場分析。國立中央大學大氣物理研究所碩士論文,62頁。
何姿儀, 2005:應用SSM/I衛星觀測資料估算颱風定量降水。國立中央大學大氣物理研究所碩士論文,92頁。
徐敏彰, 2004:應用衛星資料分析海氣參數與颱風強度變化之關係。國立中央大學大氣物理研究所碩士論文,104頁。
畢德成, 2000:希伯特頻譜於地震資料之應用。國立中央大學土木工程學系碩士論文,155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。
Bankert, R. L., and P. M. Tag, 2002: An Automated Method to Estimate Tropical Cyclone Intensity Using SSM/I Imagery. J. Appl. Meteor., 41, 461–472.
Bove, J. Elsner, C. W. Landsea, X. Niu, and J. J. O’Brien, 1998: Effect of El Niño on U.S. Landfalling Hurricanes, Revisited. Bull. Amer. Meteor. Soc., 79, 2477–2482.
Chan, Johnny C. L., and K. S. Liu, 2004: Global Warming and Western North Pacific Typhoon Activity from an Observational Perspective. J. Climate, 17, 4590-4602.
Chia, H. H., and C. F. Ropelewski, 2002: The Interannual Variability in the Genesis Location of Tropical Cyclones in the Northwest Pacific. J. Climate, 15, 2934-2944.
Chou, S. H., R. M. Atlas, C. L. Shie, and J. Ardizzone, 1995: Estimates of Surface Humidity and Latent Heat Fluxes over Ocean from SSM/I data. Mon. Wea. Rev., 123, 2405-2425.
Chou, S. H., C. L. Shie, R. M. Atlas, and J. Ardizzone, 1997: Air Sea Fluxes Retrieved from Special Sensor Microwave Imager Data. J. Geophys. Res., 102, 12705-12726.
Chu, P. S., and J. D. Clark, 1999: Decadal Variations of Tropical Cyclone Activity over the Central North Pacific. Bull. Amer. Meteor. Soc., 80, 1875-1881.
Cione, J. J., and E. W. Uhlhorn, 2003: Sea Surface Temperature Variability in Hurricanes: Implications with Respect to Intensity Change. Mon. Wea. Rev., 131, 1783-1796.
Cooley, J. W, and Tukey, O. W, 1965: An Algorithm for the Machine Calculation of Complex Fourier Series. Math. Comput., 19, 297-301.
Duffy, D. G., 2004: The Application of Hilbert-Huang Transforms to Meteorological Datasets. J. Atmos. Oceanic Technol., 21, 599-611.
Dunion, J. P., and C. S. Velden, 2004: The Impact of the Saharan Air Layer on Atlantic Tropical Cyclone Activity. Bull. Amer. Meteor. Soc., 85, 353-365.
Dvorak, V. F., 1975: Tropical Cyclone Intensity Analysis and Forecasting from Satellite Imagery. Mon. Wea. Rev., 103, 909–918.
Emanuel, K., 2005: Increasing Destructiveness of Tropical Cyclones Over the Past 30 Years. Nature, 436, 686-688.
Frank, W. M., 1987: Tropical cyclone formation. In A Global View of Tropical Cyclones, R. L. Elsberry, W. M. Frank, G. J. Holland, J. D. Jarrell, and R. L. Southern, Eds., Naval Postgraduate School, 53–90.
Franklin, J. L., C. J. Mcadie, and M. B. Lawrence, 2003: Trends In Track Forecasting for Tropical Cyclones Threatening the United States, 1970-2001. Bull. Amer. Meteor. Soc., 84, 1197-1203.
Gloersen, P., and N. Huang, 2003: Comparison of Interannual Intrinsic Modes in Hemispheric Sea Ice Covers and Other Geophysical Parameters. IEEE Trans. Geosci. Remote Sensing, 41, 1062-1074.
Goodberlet, M. A., C. T. Swift, and J. C. Wilkerson, 1989: Remote Sensing of Ocean Surface Winds with the Special Sensor Microwave/Imager. J. Geophys. Res., 94, C10, 14547-14555.
Goodberlet, M. A., and C. T. Swift, 1992: Improved Retrievals from the DMSP Wind Speed Algorithm under Adverse Weather Condition. IEEE Trans. Geosci. Remote Sensing, CE30, 1076-1077.
Gray, W. M., 1979: Hurricanes: Their Formation, Structure and Likely Role in the Tropical Circulation. Meteorology over the Tropical Oceans, James Glaisher House, 155-218.
Hollinger, J., R. Lo, G. Poe, R. Savage, and J. Pierce, 1987: Special Sensor Microwave/Imager User’s Guide. Naval Research Laboratory Washington, D.C., 120 pp.
Huang, N. E., and Coauthors, 1998: The Empirical Mode Decomposition and the Hilbert Spectrum for Nonlinear and Non-stationary Time Series Analysis. Proc. Roy. Soc. London, 454A, 903–995.
Lighthill J., G. Holland, W. Gray, C. Landsea, G. Craig, J. Evans, Y. Kurihara, and C. Guard, 1994: Global Warming Change and Tropical Cyclones. Bull. Amer. Meteor. Soc., 75, 2147-2157.
Liou, K. N., 2002: An Introduction to Atmospheric Radiation. Academic Press, Ca., USA, 583 pp.
Liu, G. R., C. C. Liu, and T. H. Kuo, 2001: A Contrast and Comparison of Near-Sea Surface Air Temperature/Humidity Form GMS and SSM/I Data With an Improved Algorithm. IEEE Trans. Geosci. Remote Sensing, 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.
Liu, K. S., and J. C. L. Chan, 1999: Size of Tropical Cyclones as Inferred from ERS-1 and ERS-2 Data. Mon. Wea. Rev., 127, 2992-3001.
Liu, K.S. and Johnny C. L. Chan, 2002: Synoptic Flow Patterns Associated with Small and Large Tropical Cyclones over the Western North Pacific. Mon. Wea. Rev., 130, 2134-2142.
Pasch, R. J., L. A. Avila, and J. Jiing, 1997 : Atlantic tropical systems of 1994 and 1995: A Comparison of a Quite Season to a Near Record Breaking one. Mon. Wea. Rev., 126, 1106-1123.
Pasch, R. J., S. R. Stewart, and D. P. Brown, 2003 : Comments on “Early detection of tropical cyclones using SeaWinds-derived vorticity. Bull. Amer. Meteor. Soc., 84, 1415-1416.
Pielke, R. A. Jr., and C. N. Landsea, 1999: La Niña, El Niño, and Atlantic Hurricne Damages in the United States. Bull. Amer. Meteor. Soc., 80, 2027-2033.
Schluessel, P., W. J. Emery, H. Grassl, and T. Mammen, 1990: On the Bulk-Skin Temperature Difference and Its Impact on Satellite Remote Sensing of Sea Surface Temperature. J. Geophys. Res., 95, 13,341-13,356.
Sharp, R. 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.
指導教授 劉振榮(Gin-Rong Liu) 審核日期 2006-6-6
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