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研究生: 呂英展
Ing-Jaan Leu
論文名稱: NCEP月平均資料的經驗正交模分析
NCEP
指導教授: 李永安
Yung-An Lee
口試委員:
學位類別: 碩士
Master
系所名稱: 地球科學學院 - 大氣物理研究所
Graduate Institute of Atmospheric Physics
畢業學年度: 92
語文別: 中文
論文頁數: 85
中文關鍵詞: 經驗正交模分析
外文關鍵詞: ENMA
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  • 本篇論文主要是利用經驗正交模分析法(Empirical Normal Mode Analysis;ENMA),分析實際觀測的月平均資料,試圖找出具有物理意義的時空一致性結構,並了解其影響範圍、因子及其時空的演變。
    本文所使用的資料為美國國家環境預報中心重新分析資料(National Centers for Environmental Prediction/NCAR reanalysis),資料時間自1950年1月至2003年12月共計54年的月平均資料,水平解析度為2.5°(lat.)×5°(long.),分別範圍為60°S~60°N。分析所用資料包括溫度場(K)、重力位高度場(gpm)、比濕(kg/kg)、緯向風場(m/s)、流函數(m2/s)、速度位(m2/s)及垂直運動場(Pa/s)等七個變數場。其中除比濕場垂直空間層高度只到300hPa,採用1000、850、500及300hPa四層標準氣壓層外,其餘六個變數場垂直空間層則使用1000、850、500及250hPa四層標準氣壓層。
    本文所使用的方法是李在2004年發展出的經驗正交模分析(ENMA),此方法結合MSSA的線性特徵與POP(Principal Oscillation Pattern)的波動特徵,從觀測資料中獲得動力系統的正交模震盪,並計算其波譜值與確認波動的傳播和變化的分布。
    在熱帶地區最明顯的氣候訊號就是聖嬰現象 (ENSO),週期大約2至7年,其源地和發展機制至今仍是一個謎,因此本文希望藉由ENMA的分析方法,進一步去探討各種氣象因子所造成的影響,分析結果顯示ENSO現象是由兩個明顯的波動所組成,一個波的週期約是59個月,起源於赤道中太平洋並且向東傳播。另一個波是有43個月的週期,產生在南美洲沿岸,有向西傳遞的趨勢。


    ENMA

    摘要………………………………………………………………………i 誌謝……………………………………………………………………ii 目錄……………………………………………………………………iii 圖表說明………………………………………………………………iv 壹、前言…………………………………………………………………1 貳、資料來源與前置處理………………………………………………5 2.1資料來源…………………………………………………………5 2.2前置處理…………………………………………………………5 參、ENMA簡介……………………………………………………………7 肆、ENMA分析結果………………………………………………………9 4.1週期59個月正交模振盪的分析結果……………………………9 4.1.1溫度場……………………………………………………………9 4.1.2重力位高度場……………………………………………………13 4.1.3流函數場…………………………………………………………15 4.1.4速度位場……………………………………………………16 4.1.5比濕場………………………………………………………17 4.1.6緯向風場……………………………………………………17 4.1.7小結………………………………………………………………18 4.2週期43個月正交模振盪的分析結果…………………………19 4.2.1溫度場………………………………………………………19 4.2.2重力位高度場………………………………………………21 4.2.3流函數場……………………………………………………22 4.2.4速度位場……………………………………………………23 4.2.5比濕場………………………………………………………24 4.2.6緯向風場……………………………………………………24 4.2.7小結…………………………………………………………25 伍、結論與展望…………………………………………………………26 5.1結論………………………………………………………………26 5.2展望………………………………………………………………27 參考文獻………………………………………………………………28 附圖……………………………………………………………………31

    謝榮傑,1998:重新分析資料對於氣候分析之影響。國立中央大學大氣物理研究所碩士論文,1-51頁。
    Barnett, T. P., 1991: The interaction of multiple time scales in the tropical climate system. J. Climate, 4, 269-285.
    Bourke, W., 1988:Spectral methods in global climate and weather prediction models, Physically-based Modelling and Simulation of Climatic Chang, Part 1, M. E. Schlesinger, Ed., Kluwer Academic, Dordrecht, The Netherlands, pp.169-219.
    Bretherton, C. S., C. Smith, and J. M. Wallace, 1992:An intercomparison of methods for finding coupled patterns in climate data. J. climate, 5, 541-560.
    Fedorov, A. V., S. L. Harper, S. G. Philander, B. Winter, and A. Wittenberg, 2003: How Predictable is El Nino? Bull. Am. Meteorol. Soc., 84, 911-919.
    Fraedrich, K., L. M. John, M. F. William, and W. Risheng, 1997:Extened EOF Analtsis of Tropical Disturbances:TOGA COARE, J. Atmos. Sci., 54, 2363-2372
    Golub, G. H. and C. F. Van Loan, 1996: Matrix Computations. Johns Hopkins Univ. Press, Baltimore, 694 pp.
    Harrison, D. E., and N. K. Larkin, 1998: El Nino-Southern Oscillation sea surface temperature and wind anomalies, 1946-1993. Reviews of Geophysics, 36, 353-399.
    Hasselmann, K., 1988: PIPs and POPs: The reduction of complex dynamical systems using principal interaction and oscillation patterns. Journal of Geophysical Research, 93, 11015-11021.
    Jin, F.-F., J. D. Neelin, and M. Ghil, 1994: El Niño on the devil’s staircase: Annual subharmonic steps to chaos. Science, 264, 70-72.
    Krishnamurthy ,V. and B.N.Goswami,2000:Indian Monsoon-ENSO relationship on interdecadal timescale. J. Climate, 13, 579-595.
    Lee, Y.-A., 2002:A T-EOF based prediction method. J. Climate, 15, 226-234.
    Lee, Y.-A., 2004: Alternative approaches to estimating linear propagator and finite-time growth rates from data. J. Climate (in revision).
    Lee, Y.-A., 2004: An Empirical Normal Mode Analysis of the Global Sea Surface Temperature: The Dominant Normal Mode Characteristics of the El Niño-Southern Oscillation:J. Climate, (revised).
    Penland, C., and T. Magorian, 1993: Prediction of Nino 3 sea surface temperatures using linear inverse modeling. J. Climate, 6, 1067-1076.
    Penland, C., 1989: Random forcing and forecasting using principal oscillation pattern analysis. Mon. Wea. Rev., 117, 2165-2185.
    Penland, C. and P.D.Sardeshmukh,1995:The optimal growth of tropical Sea Surface Temperature Anomalies:J. Climate, 8, 1999-2024.
    Philander, S. G. H., 1990: El Nino, La Nina, and the Southern Oscillation. Academic, New York, 289 pp.
    Preisendorfer, R. W., and C. D. Mobley, 1988:Principal Component Analysis in Meteorology and Oceanography. Elsevier, Amsterdam, 425 pp.
    Rasmusson, E. M., and T. H. Carpenter, 1982: Variations in tropical sea surface temperature and surface wind fields associated with the Southern Oscillation/El Nino. Monthly Weather Review, 110, 354-384.
    von Storch, H., G. Buerger, R. Schnur, and J. von Storch, 1995: Principal oscillation patterns: a review. J. Climate, 8, 377-400.
    Vautard, R., and M.Ghil,1989:Singulr Spectrum Analysis in Nonlinear Dynamics with Applications to Paleoclimatic time series, Physica D, 35, 395-424
    Vautard, R. P. Tiou and M.Ghil,1992:Singulr Spectrum Analysis:A Toolkit for Short, Noisy Chaotic Signals, Physica D, 58, 395-424.
    Wallace, J. M., and D. S. Gutzler, 1981:Teleconnections in the Geopotential Height Field during the Northern Winter. Mon. Wea. Rev., 109, 784-812.
    Wallace, J. M., E. M. Rasmusson, T. P. Mitchell, V. E. Kousky, E. S. Sarachik, and H. von Storch, 1998: On the structure and evolution of ENSO-related climate variability in the tropical Pacific: lessons from TOGA. Journal of Geophysical Research, 103, 14241-14259.
    Yu, J.-Y., C. R. Mechoso, J. C. McWilliams, and A. Arakawa, 2001: Impacts of the Indian Ocean on the ENSO cycle. Geophys. Res. Lett., 29, 10.1029/2001GL014098.

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