![]() |
|
以作者查詢圖書館館藏 、以作者查詢臺灣博碩士 、以作者查詢全國書目 、勘誤回報 、線上人數:80 、訪客IP:3.145.68.182
姓名 鄭丞衡(Cheng-Heng Cheng) 查詢紙本館藏 畢業系所 遙測科技碩士學位學程 論文名稱 旋轉與強度變化效應於估算熱帶氣旋登陸後之降雨潛勢 相關論文 檔案 [Endnote RIS 格式]
[Bibtex 格式]
[相關文章]
[文章引用]
[完整記錄]
[館藏目錄]
[檢視]
[下載]
- 本電子論文使用權限為同意立即開放。
- 已達開放權限電子全文僅授權使用者為學術研究之目的,進行個人非營利性質之檢索、閱讀、列印。
- 請遵守中華民國著作權法之相關規定,切勿任意重製、散佈、改作、轉貼、播送,以免觸法。
摘要(中) 颱風所帶來的豪大雨往往對我們生命以及經濟造成極大傷害,因此準確的颱風降水預測對於防洪減災任務相當重要。Kidder et al. (2005)提出熱帶氣旋降雨潛勢(Tropical Rainfall Potential Technique, TRaP)的估算方法,可用來快速的估算颱風累積降水分佈。由於其TRaP方法並未考慮颱風旋轉效應以及降雨率隨時間變化關係,因此以TRaP方法估算降雨時往往造成可觀誤差。本研究引用Kaplan et al. (1995)方法,建立估算大陸華南沿海地區熱帶氣旋登陸後強度遞減模式,並嘗試利用氣旋登陸時初始強度、季節、及強度加季節等三種分類,分別建立強度變化估算模式,結果顯示,以強度分類建立的估算模式所估算的強度變化結果最佳。
降雨估算方面,本研究使用TRaP方法,搭配本研究所建立的氣旋強度遞減估算模式來預測氣旋登陸後降雨率變化,以及使用Liu et al. (2008)所提出颱風旋轉角度估算方法,以估算氣旋登陸後累積降雨潛勢。因受到測站資料時間解析度限制,本研究只分析6、24小時累積降雨。估算得之的6小時累積降雨結果顯示僅考慮平移時其估算結果與測站相關係數為0.74,而同時考慮旋轉加強度變化的相關係數則提升為0.78;而24小時累積雨量估算結果顯示僅考慮平移時其相關係數為0.51,但加入了旋轉以及強度變化因素後其相關係數提升至0.60,且RMSE也從37.1 mm/24hr大幅降低至13.8 mm/24hr。整體而言,其結果顯示當考慮旋轉及強度變化因素後可有效提升估算降雨的準確度。
摘要(英) Typhoons usually pose a serious threat to the livelihood of people. Therefore, making accurate rainfall predictions has been a key focus in weather forecasting. Kidder et al. (2005) introduced a method called the Tropical Rainfall Potential Technique (TRaP) to predict the accumulated rainfall. However, the method didn’t consider the cyclone intensity variations and rotation, which may cause significant errors when estimating the rainfall potential. The intensity decay model (Kaplan et al., 1995) is used in this study to estimate the landing cyclone intensity variations. The different landing typhoon intensity, seasons, and intensity plus seasons, were categorized and tested in this model, the results show that the consideration of intensity had the best result.
Based on the TRaP method, the study considered the cyclone rotations (Liu et al., 2008) and intensity variations in estimating the rainfall potential in the southern China coastal area. Due to the limitation of the rain gauge temporal resolution, only 6 and 24 hours accumulated rainfall were analyzed in this study. For the 6 hrs rainfall potential, results revealed that the correlation was 0.74 when only the shift-motion was considered. Yet, the correlation rose to 0.78 when the tropical cyclones’ intensity and rotation changes were also taken into account. In terms of the 24 hrs rainfall potential prediction, the correlation increased from 0.51 to 0.60 and the RMSE decreased from 37.1 to 13.8 mm/24hr when intensity variations and rotation change were factored in. In general, the results showed that the additional considerations in this study could notably improve the TRaP method accuracy.
關鍵字(中) ★ 熱帶氣旋降雨潛勢
★ 強度遞減模式關鍵字(英) ★ tropical rainfall potential
★ intensity decay model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 研究動機與目的............................................................................................. 5
第二章 資料蒐集..................................................................................................... 8
2.1 SSM/I與SSMI/S衛星資料 ........................................................................... 8
2.2地球同步衛星資料........................................................................................ 10
2.3 JTWC最佳路徑資料 .................................................................................... 11
2.4 UCAR全球測站資料 ................................................................................... 11
第三章 基礎理論於研究方法 ........................................................................... 13
3.1 降雨反演式................................................................................................... 13
3.2 TRaP估算降雨潛勢 ..................................................................................... 15
3.3颱風移動方向、移動速度與旋轉角度........................................................ 16
3.3.1估算颱風移動方向與移動速度......................................................... 16
3.3.2估算熱帶氣旋旋轉角度..................................................................... 17
3.4估算熱帶氣旋登陸後強度變化.................................................................... 17
3.4.1 考慮不同初始登陸強度影響............................................................ 20
3.4.2 考慮不同季節影響............................................................................ 21
3.4.3 考慮不同強度及季節影響................................................................ 21
3.4.4 本研究估算強度方法與林(2008)結果比較 ..................................... 23
3.5 熱帶氣旋強度與總降雨量關係................................................................... 23
第四章 結果分析與討論..................................................................................... 25
V
4.1 個案分析....................................................................................................... 25
4.1.1 Jelawat (2000)颱風 ............................................................................. 25
4.1.2 Toraji (2001)颱風 ............................................................................... 27
4.1.3 Sinlaku (2002)颱風 ............................................................................. 28
4.1.4 Dujuan (2003)颱風 ............................................................................. 31
4.1.5 Prapiroon (2006)颱風 ......................................................................... 32
4.1.6 Chanthu (2010)颱風 ........................................................................... 34
4.2 綜合討論....................................................................................................... 35
第五章 結論與未來展望..................................................................................... 37
參考文獻 ................................................................................................................... 39
參考網站 ................................................................................................................... 43
附表 ............................................................................................................................ 44
附圖 ............................................................................................................................ 51
參考文獻 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,臺灣中壢,92頁。
陳嬿如,2007:衛星資料估算颱風旋轉及強度變化在熱帶氣旋定量降雨預測之研究。國立中央大學大氣物理研究所碩士論文,臺灣中壢,90頁。
林東逸,2008:衛星資料估算颱風旋轉與登陸強度衰減在熱帶氣旋降雨潛勢計算之應用。國立中央大學大氣物理研究所碩士論文,臺灣中壢,95頁。
劉崇治、林裕豐、戴世忠、趙俊傑、劉振榮,2007:SSM/I衛星資料在估算侵台颱風降雨之初步研究。大氣科學,第35期,第1號,51-68頁。
Chiu, L. S., G. R. North, D. A. Short and A. McConnell,1990: Rain estimation from satellites: effect of finite field of view. J. Geophys. Res., 95, 2177-2185.
DeMaria, M., J. Knaff and J. Kaplan, 2006: On the decay of tropical cyclone winds crossing narrow landmasses. J. Appl. Meteor., 45, 491-499.
Dvorak, V. F.,1975: Tropical Cyclone intensity analysis and Forecasting form Imagery. Mon. Wea. Rev., 103, 420-430.
Ferraro, R. R., 1997: Special sensor microwave image derived global rainfall estimates for climatological applications. J. Geophys. Res., 102, 16715-16735.
Grody, N. C., 1991: Classification of snow cover and precipitation using the special sensor microwave imager. J. Geophys. Res., 96, 7423-7435.
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.
Ho, F. P., J. C. Su, K. L. Hanevich, R. J. Smith and F. P. Richards, 1987: Hurricane climatology for the Atlantic and Gulf coasts of the United States. NOAA Tech. Rep. NWS 38, NOAA, U.S. Dept. of Commerce, Silver Spring, MD, 195pp.
Hollinger, J., R. Lo, L. Poe, R. Savage and J. Pierce, 1987: Special sensor microwave/imager user’s Guide. Naval Research Laboratory Washington, D. C., 120pp.
Jiang, H., J. B. Halverson and E. J. Zipser, 2008: Influence of environment moisture TRMM-Derived tropical cyclone precipitation over land and ocean. Gerphys. Res. Lett., 35, L17806.
Joyce, R. J., J. E. Janowiak, P. A. Arkin and P. Xie, 2004: CMORPH: A method that produces global precipitation estimates from passive microwave and infrared data at high spatial and temporal resolution. J. Hydrometeor, 5, 487–503.
Kaplan, J. and M. DeMaria, 2000: On the decay of tropical cyclone winds after landfall in the new England area. J. Appl. Meteor., 40, 280-286.
Kaplan, J. and M. DeMaria, 1995: A simple empirical model for predicting the decay of tropical cyclone winds after landfall. J. Appl. Meteor., 34, 2499–2512.
Kidder, S. Q., J. A. Knaff, S. J. Kusselson, M. Turk, R. R. Ferraro and R. J. Kuligowski, 2005: The tropical rainfall potential (TRaP) technique. Part I: Description and examples. Wea., Forecasting, 20, 456-464.
Liu, C. C., 2008: The influence of terrain on the tropical rainfall potential technique in Taiwan. Wea. Forecasting, 24, 785-799.
Liu, G. R., C. C. Chao and C. Y. Ho, 2008: Applying satellite-estimated storm rotation speed to improve typhoon rainfall potential technique. Wea. Forecasting, 23, 259-269.
Lonfat, M., F. D. Marks and S. S. Cheng, 2004: Precipitation distribution in tropical cyclones using the tropical rainfall measuring mission (TRMM) microwave imager: A Global Perspective. Mon. Weather Rev., 132, 1645-1660.
Lonfat, M., R. Rogers, T. Marchok and F. D. Marks Jr., 2007: A parametric model for predicting hurricane rainfall. Mon. Wea. Rev., 135, 3086-3097.
Olander, T. L., C. S. Velden and M. A. Turk, 2002: Development of the advanced objective Dvorak technique (AODT) – current progress and future directions. 25th Conf. on Hurricanes and Tropical Meteorology, San Diego, CA, 15A.4.
Poe, G., K. St. Germain, J. Bobak, et al. 2001. DMSP calibration/validation plan for the special sensor microwave imager sounder (SSMIS). Naval Research Laboratory: Washington, DC, USA. 2001.
Shen, Y., A. Xiong, Y. Wang and P. Xie, 2010: Performance of high-resolution satellite precipitation products over China. J. Geophys. Res., 115, D02114.
Velden, C. S., T. L. Olander and R. M., Zehr, 1998: Development of an Objective Scheme to Estimate Tropical Cyclone Intensity from Digital Geostationary Satellite Infrared Imagery. Wea. Forecasting, 13,172-183.
Wong, M. L. M., J. C. L. Chan and W. Zhou, 2008: A simple empirical model for estimating the intensity change of tropical cyclones after landfall along the south china coast, Journal of Applied Meteorology and Climatology, 47, 326-338.
Yan, B. and F. Weng, 2009: Assessments of F16 special sensor microwave imager and sounder antenna temperature at lower atmospheric sounding channels. Advances in Meteorology.
Yan, B. and F. Weng, 2008: Intercalibration between special sensor microwave imager/ sounder and special sensor microwave imager. IEEE Trans. Geosci. Remote Sens., 46, 4984-995.
指導教授 劉振榮(Gin-Rong Liu) 審核日期 2012-7-27 推文 plurk
funp
live
udn
HD
myshare
netvibes
friend
youpush
delicious
baidu
網路書籤 Google bookmarks
del.icio.us
hemidemi
myshare