海表面風場與通量於熱帶氣旋發展影響之探討

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賴佑晟(You-Cheng Lai) 查詢紙本館藏

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大氣科學學系

論文名稱

海表面風場與通量於熱帶氣旋發展影響之探討
(Investigation of the Sea Surface Wind and Flux for the Development of Tropical Cyclone)

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摘要(中)

熱帶氣旋的生成與強度增減演變，往往位於資料匱乏的洋面，因此衛星資料的使用，對於颱風與這些階段的模擬或預報，具有不可或缺的角色，進而更可研析與探討其發展及增強機制。過往已有研究揭示，颱風的能量有部分是透過海氣通量形式由海表面獲得。而這海氣間交互作用的媒介，海面風場扮演著重要的角色。因此本研究除了將同化使用傳統觀測資料外，也運用了由歐洲衛星中心(ESA) Metop-A衛星所籌載Advanced Scatterometer (ASCAT)的海面風場反演資料，藉由數值預報模式探討海面風場資料、海氣可感熱通量、海氣潛熱通量等，對於熱帶氣旋預報的影響，並分析前述通量於颱風增強階段之重要性。
本研究主要針對2008年西北太平洋上的如麗颱風(Typhoon Nuri)進行資料同化模擬實驗與敏感度測試實驗。於資料同化模擬實驗方面，將測試了三種資料同化方式，在颱風模擬的表現上，各實驗組的路徑模擬均無明顯差異，然而在颱風強度模擬方面，有使用ASCAT資料的實驗組，能有最佳的強度模擬，此乃肇因於ASCAT風場資料有助於改善初始場中的的海面風場結構。緊接著利用不同實驗組的海氣通量來評估通量與強度的關係，發現海氣通量的最大值出現的時間點通常是提早於颱風強度最強的時間點，且潛熱通量與颱風整體強度具有明顯正相關，而可感熱通量則與颱風強度的演變較有關係。另外，海表面風場是影響海氣通量的關鍵因子，在颱風附近更是明顯。可感熱通量的部分與海氣溫差及海表面風場皆有一定程度的相關性，而潛熱通量則是只跟海表面風場有很強的相關性，且颱風強度愈強，海表面風速與海氣通量的相關性就愈高。敏感度實驗組中發現海溫愈高導致海氣間溫度差距愈大，於此將連帶增加海氣通量，進而使得後續所模擬之颱風強度愈強，間接證實前述之可感熱通量對於颱風強度演變的關係。另外亦發現海表面風場在海氣通量中扮演重要關鍵角色，亦即若海氣間有很大的溫度或溼度梯度能量，也會因為較弱的海表面風速而造成轉換效率不佳，颱風獲取不到來自海洋的能量，其強度就不會演變太強。交叉分析以上實驗組的模擬結果，發現於若如麗颱風初期的通量愈大，代表從此颱風可由海洋所獲得的能量就愈多，也使得讓如麗颱風在其後也發展的愈強，所以颱風生成及其初期的通量研究，將是未來重要的科學研究方向。

摘要(英)

The genesis and intensification of tropical cyclone(TC) are usually occurring in the ocean where is lacking those traditional observations like surface in-situ data or radiosounde for upper atmosphere. Therefore, satellite data plays a critical role in the purpose of simulation and/or forecast of TC in these stages, and the further investigation of the evolution and intensity intensification. According to the earlier studies, part of the energy for TC intensification is associated with the planetary boundary processes, which might be through the air-sea interaction like latent heat flux and sensible heat flux. Furthermore, sea surface wind could be an important role between sea and air when gradient is presented. Therefore, sea surface wind data from the Advanced Scatterometer (ASCAT) which is aboard on ESA Metop-A satellite are used to address this issue in this study through the data assimilation technique and the use of regional Weather Research and Forecasting (WRF) model. The main focus is placed on the investigation of the impacts from sea surface wind, sensible heat flux, and latent heat flux for the TC forecast. The discussion on the relative importance of those above fluxes during the TC intensification stage.
This study is divided into two parts: data assimilation experiment and sensitivity experiment. Typhoon Nuri (2008) in the northwestern Pacific Ocean is chosen to elaborate those fluxes and roles as described. In first part of experiment, the best forecast skill is from the use of ASCAT and traditional observation data sets, by examination of the TC’s intensity and track forecasts. This is due to the ASCAT data can improve the structure of surface wind in the initial time.

In second part, the sensitivity experiment, we find the higher sea surface temperature might increase the temperature gradient between the sea and the air. It leads an increased air-sea flux and a stronger TC in the later forecast hours. It is also found that the sea surface wind plays an important role in the sea-air flux, that is, if there is a large temperature or humidity gradient between sea and air, the energy conversion efficiency will be poor due to the weak sea surface wind speed. Thus, TC obtains less energy from the ocean and the intensity will not be intensified. Cross-analysis of the above simulations, we conclude that the larger fluxes in the early stage of the Typhoon Nuri, the more energy can be obtained from the ocean and the intensity will become stronger.

關鍵字(中)

★ 海氣通量
★ ASCAT

關鍵字(英)

★ air-sea flux
★ ASCAT

論文目次

目錄
摘要 I
ABSTRACT III
誌謝 V
目錄 VII
表目錄 IX
圖目錄 IX
第一章緒論 1
1.1 前言 1
1.2 文獻回顧 2
1.3研究動機及目的 5
第二章資料來源及個案介紹 7
2.1 傳統觀測資料 7
2.2 ASCAT 7
2.3再分析資料 10
2.4 JTWC最佳路徑 11
2.5個案介紹 12
第三章模式介紹及實驗設計 14
3.1 模式介紹 14
3.1.1 GSI 14
3.1.2 WRF 16
3.1.3 模式設定 17
3.2 實驗設計 18
3.2.1 颱風個案同化資料實驗 18
3.2.2 表面通量敏感度實驗 18
3.3 海氣通量 19
第四章實驗結果與討論 21
4.1 如麗颱風的路徑及強度模擬 21
4.2 同化階段及初始場 22
4.3颱風強度與海氣通量的關係 25
第五章敏感度實驗 31
第六章總結及未來展望 34
6.1 結論 34
6.2 未來展望 36
參考文獻 38
附表 42
附圖 45

參考文獻

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，1-92。
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，1-108。

Black, P. G., and L. K. Shay, 1998: Air–sea interaction processes relevant to tropical cyclone intensity change. Preprints, Symp. on Tropical Cyclone Intensity Change, Phoenix, AZ, Amer. Meteor. Soc., 161–168.

Bender, M. A. and I. Ginis, 2000: Real-case simulations of hurricane–ocean interaction using a high-resolution coupled model: Effects on hurricane intensity. Mon. Weather Rev., vol. 128, no. 4, pp. 917–946.

Bi, L., J. Jung, M. Morgan, and J. Le Marshall, 2010: A two-season impact study of the WindSat surface wind retrievals in the NCEP Global Data Assimilation System. Wea. Forecasting, 25, 931–949.

Bi, L., J. Jung, M. Morgan, and J. L. Marshall, 2011: Assessment of Assimilating ASCAT Surface Wind Retrievals in the NCEP Global Data Assimilation System. Monthly Weather Review, 139, 3405-3421.

Charney, J. G., 1948: On the scale of atmospheric motions. Geofys. Publ.,17, No.2, 17pp.

Chou, K.H., Wu, C.C., Lin, S.Z., 2013: Assessment of the ASCAT wind error characteristics by global dropwindsonde observations. Journal of Geophysical Research: Atmospheres, 118 ,9011-9021.

Emanuel, K. A., 1986: An air–sea interaction theory for tropical cyclones. Part I: Steady-state maintenance. J. Atmos. Sci., 43, 585–604.

Emanuel, K. A. 1999: Thermodynamic control of hurricane intensity. Nature, vol. 401, no. 6754, pp. 665–669.

Emanuel, K. A., C. DesAutels, C. Holloway, and R. Korty, 2004: Environmental control of tropical cyclone intensity. J. Atmos. Sci., vol. 61, no. 7, pp. 843–858.

Gray, W. M., 1968: Global view of the origin of the tropical disturbances and storm. Mon. Wea. Rev.,140, 1067-1080.

Green, B. W. Green and F. Zhang, 2013: Impacts of Air–Sea Flux Parameterizations on the Intensity and Structure of Tropical Cyclones. Mon. Wea. Rev., 141, 2308–2324.

Hersbach, H., and P. Janssen, 2007a: Preparation for assimilation of surface-wind data from ASCAT at ECMWF. ECMWF Research Department Memo., ECMWF, Reading, United Kingdom

Hsiao, L.F., Chen, D. S., Kuo, Y. H., Guo, Y. R., Yeh, T. C., Hong, J. S., Fong, C.T., Lee, C. S., 2012: Application of WRF 3DVAR to operational typhoon prediction in Taiwan: impact of outer loop and partial cycling approaches. Weather and Forecasting, 27(5), 1249-1263.

Kaplan, J., and M. DeMaria, 2003: Large-scale characteristics of rapidly intensifying tropical cyclones in the North Atlantic basin, Weather Forecasting, 18, 1093 – 1108.

Kowaleski, A. M. and J. L. Evans, 2015: Thermodynamic Observations and Flux Calculations of the Tropical Cyclone Surface Layer within the Context of Potential Intensity, Weather and Forecasting, 30, 1303-1320.

Liu, W. T., K. B. Katsaros and J. A. Businger, 1979: Bulk parameterization of air-sea exchanges of heat and water vapor including the molecular constraints at the interface. J. Atmos. Sci., 36, 1722–1735.

Liu, C.-Y., J. Li, E. Weisz, T. J. Schmit, S. A. Ackerman, and H.-L. Huang, 2008: Synergistic use of AIRS and MODIS radiance measurements for atmospheric profiling, GEOPHYSICAL RESEARCH LETTERS, 35, L21802, doi:10.1029/2008GL035859

Liu, C.-Y., G.-R. Liu, T.-H. Lin, C.-C. Liu, H. Ren, and C.-C. Young, 2014: Using Surface Stations to Improve Sounding Retrievals from Hyperspectral Infrared Instruments, IEEE Trans. Geosci. Remote Sens, 52, 11, 6957-6963, doi:10.1109/TGRS.2014.2305992

Liu, C.-Y., J. Li, S.-P. Ho, G.-R. Liu, T.-H. Lin, and C.-C. Young, 2016: Retrieval of Atmospheric Thermodynamic State from Synergistic Use of Radio Occultation and Hyperspectral Infrared Radiances Observations, IEEE Journal of Selected Topics in Applied Earth Observation and Remote Sensing, Vol. 9, no. 2, doi:10.1109/JSTARS.2015.2444274

Liu, C.-Y., S.-C. Kuo, A. Lim, S.-C. Hsu, K.-H. Tseng, N.-C. Yeh, and Y.-C. Yang, 2016: Optimal Use of Space-Borne Advanced Infrared and Microwave Soundings for Regional Numerical Weather Prediction, Remote Sens. 8(10), 816, doi:10.3390/rs8100816

Palmen, 1948: On the formation and structure of tropical cyclones, Geophysica, 3, pp. 26-38.

Pun, I-F., I-I Lin, C.-R. Wu, D.-S. Ko, and W.-T. Liu, 2007: Validation and Application of Altimetry-derived Upper Ocean Thermal Structure in the Western North Pacific Ocean for Typhoon Intensity Forecast, IEEE Transactions On Geoscience and Remote Sensing, Vol. 45, No. 6, 1616-1630.

Rappaport, E. N., and Coauthors, 2009: Advances and challenges at the National Hurricane Center. Wea. Forecasting, 24, 395–419.

Shay, L. K., G. J. Goni, and P. G. Black, 2000: Effects of a warm oceanic feature on hurricane Opal. Mon. Wea. Rev., 128, 1366–1383.

Shay, L. K., G. J. Goni, P. G. Black, 2000: Effects of a warm oceanic feature on Hurricane Opal. Mon. Weather Rev., vol. 128, no. 5, pp. 1366–1383.

Shay, L. K., 2009: Upper ocean structure: A Revisit of the response to strong forcing events. Encyclopedia of Ocean Sciences, Eds. R.A. Weller, S.A. Thorpe, J. Steele, Elsevier Press International, Oxford, UK, pp. 4619–4637.

指導教授

劉千義、劉振榮(Chian-Yi Liu Gin-Rong Liu)

審核日期

2017-1-20

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