跳到主要內容

簡易檢索 / 詳目顯示

研究生: 吳戎富
Jung-fu Wu
論文名稱: 雲簇海氣環境參數差異分析在西北太平洋熱帶氣旋生成機制之研究
指導教授: 劉振榮
Gin-rong Liu
口試委員:
學位類別: 碩士
Master
系所名稱: 太空及遙測研究中心 - 遙測科技碩士學位學程
Master of Science Program in Remote Sensing Science and Technology
論文出版年: 2013
畢業學年度: 101
語文別: 中文
論文頁數: 91
中文關鍵詞: 熱帶氣旋生成海氣參數BDI權重分數氣旋發展機率
外文關鍵詞: Tropical cyclone formation, Air-sea parameter, Weight score, BDI, Tropical cyclone development possibility
相關次數: 點閱:15下載:0
分享至:
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報
  • 廣大的熱帶洋面上有些雲簇會發展成熱帶氣旋,有些卻不會形成,為了
    分析熱帶氣旋的發展與否,需藉由客觀的方法來分析發展與非發展系統間
    的特性差異。本研究主要的目的為探討發展與非發展雲簇的海氣環境參數
    進行系統性的分類,進而全面且完整的歸納兩者間環境條件差異,提供熱
    帶氣旋生成預報之參考。
    本研究利用西北太平洋2000~2009 年間的JTWC 颱風最佳路徑和
    ECMWF 再分析資料,計算七項海氣環境參數的發展與非發展差異指數
    (BDI),使用參數包括:1)850hPa 相對渦度、2)850hPa-200hPa 垂直風切、
    3)900hPa 輻合度、4)總降水量、5)850hPa 相對溼度、6)可感熱通量與
    潛熱通量相加值、7)海表面溫度,計算並結合各熱帶氣旋生成閾值,計算
    權重總分後轉換成熱帶氣旋發展機率形式呈現。
    研究結果以2010~2012 年的獨立個案進行驗證,結果顯示發展個案有命
    中率(Hit rate)達0.95 的高分表現,能夠準確判斷生成位置且平均提早JTWC
    發布警報前49.9 小時達系統判斷發展機率超過60%,系統達到90%發展機
    率時也有提早37.1 小時的表現;而若以60%發展機率為誤報門檻值,系統
    的假警報率(False Alarm Ratio;FAR)為0.24。


    In order to analyze the development of tropical cyclone, it is necessary to
    investigate the difference characteristic between the development and
    non-development systems by using objective methods. The main objective of
    this study is to discuss the environment parameters between the development
    and non-development cloud clusters which can be further processed systematic
    classification. Furthermore, it can fully and completely generalizes the
    differences between environmental conditions and provides as a reference to the
    tropical cyclone forecast.
    In this study, we analyzed the typhoon cases over the Northwest Pacific
    Ocean from 2000 to 2009 by the JTWC best track and ECMWF Interim
    Reanalysis Data. And we determine the environmental air-sea parameters’
    thresholds by Box Difference Index (BDI). The environmental air-sea
    parameters include: 1) 850hPa relative vorticity, 2) Sea surface temperature, 3)
    850hPa relative humidity, 4) 900hPa divergence, 5) 850-200hPa Vertical wind
    shear, 6) Thermal energy, 7) Total precipitation. The results adopt the weights
    method and show as probability of tropical cyclone development.
    This study results are verified by using the independent cases from 2010 to
    2012 and show the good performance of the Hit rate up to 0.95. Moreover, these
    results can determine precisely the prediction accuracy reached above 60% and
    averagely 49.9 hours ahead of warning form JTWC. If the system set the
    development possibility about 60% as false alarm threshold, the False Alarm
    Ratio (FAR) of the systems are 0.24.

    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…………………………………………………………….3 1.3 研究目的…………………………………………………………….6 第二章 資料介紹…………………………………………………………….8 2.1 ECMWF ERA-interim 再分析資料………………………………..8 2.2 JTWC 最佳路徑資料………………………………………………..9 2.3 全球熱帶雲簇資料庫……………………………………………...10 2.4 紅外線衛星影像………………………………………………...…11 2.5 研究範圍介紹……………………………………………………...12 第三章 研究方法………………………………………………………...…14 3.1 發展與未發展氣旋個案篩選……………………………………...15 3.1.1 發展氣旋定義……………………………………………….15 3.1.2 非發展氣旋定義…………………………………………….15 3.2 環境參數處理……………………………………………………...16 3.2.1 垂直風切計算……………………………………………….17 3.3 BDI 值計算…………………………………………………………18 3.4 建立各環境參數之權重分數……………………………………...19 3.4.1 各參數監測方框大小……………………………………….21 3.4.2 權重分數………………………………………………….…23 3.4.3 各參數閾值及得分方法………………………………….…24 3.5 權重總分換算氣旋發展機率…………………………………...…25 第四章 結果與討論……………………………………………………...…27 4.1 BDI 數值結果討論…………………………………………………28 4.2 2010 年至2012 年發展個案監測結果驗證……………………..…29 4.2.1 監測個案顯示60%情形…………………………………..…29 4.2.2 監測個案顯示70、80%情形…………………………………30 4.2.3 監測個案顯示90、100%情形………………………………..31 4.3 發展熱帶氣旋個案分析……………………………………...……31 4.3.1 失誤個案檢討…………………………………………….…32 4.3.2 系統完整呈現之個案討論………………………………….34 4.4 誤報情況討論…………………………………………………….…38 第五章 結論與未來展望………………………………………………….40 參考文獻……………………………………………………………………...43 參考網站…………………………………………………………………...…49

    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。
    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
    西北太平洋熱帶氣旋生成,國立中央大學大氣物理研究所碩士論文,94頁,台灣中壢。
    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.
    Corbosiero, K. L., John Molinari, 2002: The Effects of Vertical Wind Shear on
    the Distribution of Convection in Tropical Cyclones. Mon. Wea. Rev., 130,
    2110–2123.
    Dare, Richard A., John L. McBride, 2011: The threshold sea surface temperature
    condition for tropical cyclogenesis. J. Climate, 24, 4570–4576.
    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.
    Goni, G. J., J. A. Trinanes, 2003: Ocean thermal structure monitoring could aid
    in the intensity forecast of tropical cyclones. EOS Trans Am Geophys
    Union., 84, 573–580
    Gray, W. M., 1968: Global view of the origin of the tropical disturbances and
    storm. Mon. Wea. Rev., 96, 669-700.
    Hanley, D. E., J. Molinari, and D. Keyser, 2001: A composite study of the
    interactions between tropical cyclones and upper tropospheric troughs. Mon. Wea. Rev., 129, 2570-2584.

    Hennon, Christopher C., C. N. Helms, K. R. Knapp, 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.
    Hennon, Christopher C., and Coauthors, 2013: Tropical Cloud Cluster
    Climatology, Variability, and Genesis Productivity. J. Climate, 26,
    3046–3066.
    Kerns, Brandon W., Shuyi 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., and Coauthors, 2011: Globally gridded satellite (GridSat)
    observations for climate studies. Bull. Amer. Meteor. Soc., 92, 893-907.
    Krayer, W. R., and Marshall, R. D., 1992: Gust factors applied to hurricane
    winds. Bull. Am. Meteorol. Soc., 73, 613–617.
    Kurihara, Y., and R. E. Tuleya, 1974: Structure of a tropical cyclone developed in a three-dimensional numerical simulation model. J. Atmos. Sci., 31,
    893-919.

    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.
    Lin, I. I., P. Black, J. F. Price, C. Y. Yang, S. S. Chen, C. C. Lien, P. A. Harr, N.
    H. Chi, C. C. Wu, and E. A. D'Asaro 2012: An ocean cooling potential
    Intensity index for tropical cyclones, Geophys. Res. Lett., in press.
    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.

    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.
    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.
    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.
    Simmons, A., S. Uppala, D. Dee, and S. Kobayashi, 2006: Era-interim: New
    ecmwf reanalysis products from 1989 onwards. ECMWF Newsletter, 25-35.
    Wilks, D. S., 2006: Statistical Methods in the Atmospheric Sciences.2nd ed.
    Academic Press, 467 pp.

    QR CODE
    :::