請用此 Handle URI 來引用此文件：
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/83765完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 吳俊傑(Chun-Chieh Wu) | |
| dc.contributor.author | Yi-Chen Li | en |
| dc.contributor.author | 李宜臻 | zh_TW |
| dc.date.accessioned | 2023-03-19T21:17:08Z | - |
| dc.date.copyright | 2022-08-10 | |
| dc.date.issued | 2022 | |
| dc.date.submitted | 2022-08-05 | |
| dc.identifier.citation | Arakane, S. and H. Hsu, 2021: Tropical Cyclone Footprints in Long-Term Mean State and Multiscale Climate Variability in the Western North Pacific as Seen in the JRA-55 Reanalysis. J. Clim., 34(18), 7443-7460. Balaguru K., G. R. Foltz, L. R. Leung, E. D’Asaro, K. A. Emanuel, H. Liu, and S. E. Zedler, 2015: Dynamic potential intensity: An improved representation of the ocean’s impact on tropical cyclones. Geophys. Res. Lett., 42, 6739-6746. Bell, S. S., S. S. Chand, and C. Turville, 2020: Projected changes in ENSO-driven regional tropical cyclone tracks. Clim. Dyn., 54, 2533-2559. ____, S. S. Chand, S. J. Camargo, K. J. Tory, C. Turville, and H. Ye, 2019: Western North Pacific tropical cyclone tracks in CMIP5 models: Statistical assessment using a model-independent detection and tracking scheme. J. Clim., 32(21), 7191-7208. Bengtsson, L., M. Botzet, and M. Esch, 1996: Will greenhouse gas-induced warming over the next 50 years lead to higher frequency and greater intensity of hurricanes? Tellus, 48A, 57-73. Bister, M., and K. A. Emanuel, 1998: Dissipative heating and hurricane intensity. Meteorol. Atmospheric Phys., 65, 233-240. ____, and ____, 2002: Low frequency variability of tropical cyclone potential intensity, 1, Interannual to interdecadal variability. J. Geophys. Res., 107(D24), 4801. Boudreault, M., L.-P. Caron, and S. J. Camargo, 2017: Reanalysis of climate influences on Atlantic tropical cyclone activity using cluster analysis. J. Geophys. Res. Atmos., 122, 4258-4280. Broccoli, A. J., and S. Manabe, 1990: Can existing climate models be used to study anthropogenic changes in tropical cyclone climate? Geophys Res. Lett., 17, 1917-1920. Camargo, S. J., A. H. Sobel, A. G. Barnston, and K. A. Emanuel, 2007a: Tropical cyclone genesis potential index in climate models. Tellus A, 59, 428-443. ____, A. W. Robertson, A. G. Barnston, and M. Ghil, 2008: Clustering of eastern North Pacific tropical cyclone tracks: ENSO and MJO effects. Geochem. Geophys. Geosyst., 9, Q06V05, ____, ____, S. J. Gaffney, P. Smyth, and M. Ghil, 2007b: Cluster analysis of typhoon tracks. Part I: General properties. J. Clim., 20(14), 3635-3653. ____, ____, ____, ____, and ____, 2007c: Cluster analysis of typhoon tracks. Part II: Large-scale circulation and ENSO. J. Clim., 20(14), 3654-3676. ____, and A. H. Sobel, 2005: Western North Pacific tropical cyclone intensity and ENSO. J. Climate, 18(15), 2996-3006. Chan, J. C. L., 2007: Interannual variations of intense typhoon activity. Tellus, 59, 455-460. ____, and K. S. Liu, 2004: Global warming and western North Pacific typhoon activity from an observational perspective. J. Clim., 17(23), 4590-4602. Charney, J., 1955: The use of the primitive equations of motion in numerical prediction. Tellus, 7, 22-26. Chen, C.-A., H.-H. Hsu, C.-C. Hong, P.-G. Chiu, C.-Y. Tu, S.-J. Lin, and A. Kitoh, 2019: Seasonal precipitation change in the Western North Pacific and East Asia under global warming in two high-resolution AGCMs. Clim. Dyn., 53, 5583-5605. Chen, J.-H. and S.-J. Lin, 2011: The remarkable predictability of inter-annual variability of Atlantic hurricanes during the past decade. Geophys. Res. Lett., 38, L11804. Colbert, A. J., B. J. Soden, and B. P. Kirtman, 2015: The impact of natural and anthropogenic climate change on western North Pacific tropical cyclone tracks. J. Clim., 28(5), 1806-1823. ____, ____, G. A. Vecchi, and B. P. Kirtman, 2013: The impact of anthropogenic climate change on North Atlantic tropical cyclone tracks. J. Clim., 26(12), 4088-4095. DeMaria, M. 1996: The effect of vertical shear on tropical cyclone intensity change. J. Atmos. Sci., 53(14), 2076-2088. Donner, L. J., and Coauthors, 2011: The dynamical core, physical parameterizations, and basic simulation characteristics of the atmospheric component AM3 of the GFDL global coupled model CM3. J. Clim., 24, 3484-3519. Dwyer, J. G., S. J. Camargo, A. H. Sobel, M. Biasutti, K. A. Emanuel, G. A. Vecchi, M. Zhao, and M. K. Tippett, 2015: Projected twenty-first-century changes in the length of the tropical cyclone season. J. Clim., 28(15), 6181-6192. Elsner, J. B., and K.-B. Liu, 2003: Examining the ENSO-typhoon hypothesis. Clim. Res., 25, 43-54. Emanuel, K. A., 1986: An air–sea interaction theory for tropical cyclones. Part 1: Steady-state maintenance. J. Atmos. Sci., 43, 585-604. ____, 1987: The dependence of hurricane intensity on climate. Nature, 326, 483-485. ____, 1991: The theory of hurricanes. Annu. Rev. Fluid. Mech., 23, 179-196. ____, 1999: Thermodynamic control of hurricane intensity. Nature, 401(6754), 665-669. ____, 2000: A statistical analysis of tropical cyclone intensity. Mon. Weather Rev., 128, 1139-1152. ____, 2005: Increasing destructiveness of tropical cyclones over the past 30?years. Nature, 436, 686-688. ____, 2013: Downscaling CMIP5 climate models shows increased tropical cyclone activity over the 21st century. Proc. Natl. Acad. Sci. U.S.A., 110(30), 12219-12224. ____, 2021: Response of global tropical cyclone activity to increasing CO2: Results from downscaling CMIP6 models. J. Clim., 34(1), 57-70. Gaffney, S. J., 2004: Probabilistic curve-aligned clustering and prediction with regression mixture models. Ph.D. thesis, University of California, Irvine, CA, 281 pp. ____, A. W. Robertson, P. Smyth, S. J. Camargo, and M. Ghil, 2007: Probabilistic clustering of extratropical cyclones using regression mixture models. Clim. Dyn., 29, 423-440. Gilford, D. M. 2021: pyPI (v1.3): Tropical cyclone potential intensity calculations in Python. Geosci. Model Dev., 14, 2351-2369. ____, S. Solomon, and K. A. Emanuel, 2019: Seasonal cycles of along-track tropical cyclone maximum intensity. Mon. Weather Rev., 147(7), 2417-2432. Gray, W. M., 1968: Global view of the origin of tropical disturbances and storms. Mon. Weather Rev., 96(10), 669-700. ____, 1979: Hurricanes: their formation, structure and likely role in the tropical circulation. Meteorology Over the Tropical Oceans, D. B. Shaw, Ed., Royal Meteorological Society, 155-218. Gutmann, E. D., R. M. Rasmussen, C. Liu, K. Ikeda, C. L. Bruyere, J. M. Done, L. Garr?, P. Friis-Hansen, and V. Veldore, 2018: Changes in hurricanes from a 13-yr convection-permitting pseudo–global warming simulation. J. Clim., 31(9), 3643-3657. Hannachi, A., and A. O’Neill, 2001: Atmospheric multiple equilibria and non-Gaussian behaviour in model simulations. Q. J. R. Meteorol. Soc., 127, 939-958. Harris, L. M. and S.-J. Lin, 2013: A two-way nested global regional dynamical core on the cubed-sphere grid. Mon. Weather Rev., 141, 283-306. Hassanzadeh, P., C-Y. Lee, E. Nabizadeh, S. J. Camargo, D. Ma, and L. Y. Yeung, 2020: Effects of climate change on the movement of future landfalling Texas tropical cyclones. Nat. Commun., 11, 3319. Hill, K. A., and G. M. Lackmann, 2011: The impact of future climate change on TC intensity and structure: A downscaling approach. J. Clim., 24, 4644-4661. Hong, C.-C., C.-H. Tsou, P.-C. Hsu, K.-C. Chen, H.-C. Liang, H.-H. Hsu, C.-Y. Tu, and A. Kitoh, 2021: Future changes in tropical cyclone intensity and frequency over the western North Pacific based on 20-km HiRAM and MRI models. J. Clim., 34(6), 2235-2251. Hong, S., and J. Lim, 2006: The WRF single-moment 6-class microphysics scheme (WSM6). J. Korean Astron. Soc., 42, 129-151. ____., Y. Noh, and J. Dudhia, 2006: A new vertical diffusion package with an explicit treatment of entrainment processes. Mon. Weather Rev., 134, 2318-2314. Hoogewind, K. A., D. R. Chavas, B. A. Schenkel, and M. E. O’Neill, 2020: Exploring controls on tropical cyclone count through the geography of environmental favorability. J. Clim., 33(5), 1725-1745. IPCC, 2007: Climate change 2007: The physical science basis. Contribution of working group I to the fourth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA. IPCC, 2021: Climate Change 2021: The Physical Science Basis. Contribution of working group I to the sixth assessment report of the intergovernmental panel on climate change. Cambridge University Press, In Press. Jim?nez, P. A., J. Dudhia, J. F. Gonz?lez-Rouco, J. Navarro, J. P. Mont?vez, and E. Garc?a-Bustamante, 2012: A revised scheme for the WRF surface layer formulation. Mon. Weather Rev., 140(3), 898-918. Kain, J. S., 2004: The Kain–Fritsch convective parameterization: an update. J. Appl. Meteorol. Climatol., 43(1), 170-181. Kanada, S., T. Takemi, M. Kato, S. Yamasaki, H. Fudeyasu, K. Tsuboki, O. Arakawa, and I. Takayabu, 2017: A multimodel intercomparison of an intense typhoon in future, warmer climates by four 5-km-mesh models. J. Clim., 30(15), 6017-6036. Kim, H.-M., P. J. Webster, and J. A. Curry, 2009: Impact of shifting patterns of Pacific Ocean warming on North Atlantic tropical cyclones. Science, 325, 77-80. Knutson, T. R., J. J. Sirutis, M. Zhao, R. E. Tuleya, M. Bender, G. A. Vecchi, G. Villarini, and D. Chavas, 2015: Global projections of intense tropical cyclone activity for the late twenty-first century from dynamical downscaling of CMIP5/RCP4.5 Scenarios. J. Clim., 28(18), 7203-7224. ____, and Coauthors, 2010: Tropical cyclones and climate change. Nature Geosci., 3, 157-163. ____., S. J. Camargo, J. C. L. Chan, K. Emanuel, C. Ho, J. Kossin, M. Mohapatra, M. Satoh, M. Sugi, K. Walsh, and L. Wu, 2020: Tropical cyclones and climate change assessment: Part II: Projected response to anthropogenic warming. Proc. Natl. Acad. Sci. U.S.A., 101(3), E303-E322. Kossin, J. P., K. A. Emanuel, and G. A. Vecchi, 2014: The poleward migration of the location of tropical cyclone maximum intensity. Nature, 509, 349-352. ____, K. R. Knapp, T. L. Olander, and C. S. Velden, 2020: Global increase in major tropical cyclone exceedance probability over the past four decades. Proc. Natl. Acad. Sci., 117, 11975-11980. Lackmann, G. M., 2015: Hurricane Sandy before 1900 and after 2100. Bull. Am. Meteorol. Soc., 96(4), 547-560. Landsea, C. W., B. A. Harper, K. Hoarau, and J. A. Knaff, 2006: Can we detect trends in extreme tropical cyclones? Science, 313, 452-454. Lee, C., S. J. Camargo, A. H. Sobel, and M. K. Tippett, 2020: Statistical–dynamical downscaling projections of tropical cyclone activity in a warming climate: Two diverging genesis scenarios. J. Clim., 33(11), 4815-4834. Lin, I.-I., P. Black, J. F. Price, C.-Y. Yang, S. S. Chen, C.-C. Lien, P. Harr, N.-H. Chi, C.-C. Wu, and D'Asaro, 2013: An ocean coupling potential intensity index for tropical cyclones. Geophys. Res. Lett., 40, 1878-1882. ____, and J. C. L. Chan, 2015: Recent decrease in typhoon destructive potential and global warming implications. Nat. Commun., 6, 7182. Liu, K. S., and J. C. L. Chan, 2020: Recent increase in extreme intensity of tropical cyclones making landfall in South China. Clim. Dyn., 55, 1059-1074. Mei, W., and S. P. Xie, 2016: Intensification of landfalling typhoons over the northwest Pacific since the late 1970s. Nat. Geosci., 9, 753-757. Mizuta, R., O. Arakawa, T. Ose, S. Kusunoki, H. Endo, and A. Kitoh, 2014: Classification of CMIP5 future climate responses by the tropical sea surface temperature changes. SOLA, 10, 167-171. Murakami, H., and Sugi M., 2010: Effect of model resolution on tropical cyclone climate projections. SOLA, 6, 73-76. ____, B. Wang, and A. Kitoh, 2011: Future change of western North Pacific typhoons: Projections by a 20-km-mesh global atmospheric model. J. Clim., 24(4), 1154-1169. ____, ____, T. Li, and A. Kitoh, 2013: Projected increase in tropical cyclones near Hawaii. Nat. Clim. Chang., 3, 749-754. ____, G. A. Vecchi, S. Underwood, T. L. Delworth, A. T. Wittenberg, W. G. Anderson, J. Chen, R. G. Gudgel, L. M. Harris, S.-J. Lin, and F. Zeng, 2015: Simulation and prediction of category 4 and 5 hurricanes in the high-resolution GFDL HiFLOR coupled climate model. J. Clim., 28(23), 9058-9079. ____, R. Mizuta, and E. Shindo, 2012: Future changes in tropical cyclone activity projected by multi-physics and multi-SST ensemble experiments using the 60-km-mesh MRI-AGCM. Clim. Dyn., 39, 2569-2584. Nakamura, J., and Coauthors, 2017: Western North Pacific tropical cyclone model tracks in present and future climates. J. Geophys. Res., 122, 9721-9744. Ogata, T., R. Mizuta, Y. Adachi, H. Murakami, and T. Ose, 2016: Atmosphere-ocean coupling effect on intense tropical cyclone distribution and its future change with 60?km-AOGCM. Sci. Rep., 6, 29800. O'Neill, B. C., and Coauthors, 2016: The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6. Geosci. Model Dev., 9(9), 3461-3482. Patricola, C. M., and M. F. Wehner, 2018: Anthropogenic influences on major tropical cyclone events. Nature, 563, 339-346. Rahman, M. S., R. Yang, and L. Di, 2018: Clustering Indian Ocean tropical cyclone tracks by the standard deviational ellipse. Climate, 6(2), 39. Rayner, N., D. Parker, E. Horton, C. Folland, L. Alexander, D. Rowell, E. Kent, and A. Kaplan, 2003: Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century. J. Geophys. Res., 108, 4407. Roberts, M. J., and Coathers, 2020: Projected future changes in tropical cyclones using the CMIP6 HighResMIP multimodel ensemble. Geophys. Res. Lett., 47, e2020GL088662 Rotunno, R., and K. A. Emanuel, 1987: An air-sea interaction theory for tropical cyclones. Part II: Evolutionary study using a nonhydrostatic axisymmetric numerical model. J. Atmos. Sci., 44, 542-561. Simpson, R., and R. Riehl, 1958: Mid-tropospheric ventilation as a constraint on hurricane development and maintenance. Preprints, Tech. Conf. on Hurricanes, Miami Beach, FL, Amer. Meteor. Soc., D4-1–D4-10. Sobel, A. H., S. J. Camargo, T. M. Hall, C.-Y. Lee, M. K. Tippett, and A. A. Wing, 2016: Human influence on tropical cyclone intensity. Science, 353, 242-246. Tang, B., and K. A. Emanuel, 2010: Midlevel ventilation’s constraint on tropical cyclone intensity. J. Atmos. Sci., 67(6), 1817-1830. ____, and ____, 2012: A ventilation index for tropical cyclones. Bull. Am. Meteorol. Soc., 93, 1901-1912. ____, and S. J. Camargo, 2014: Environmental control of tropical cyclones in CMIP5: A ventilation perspective, J. Adv. Model. Earth Syst., 6, 115-128. Teng, H.-F., C.-S. Lee, and, H.-H. Hsu, 2014: Influence of ENSO on formation of tropical cloud clusters and their development into tropical cyclones in the western North Pacific. Geophys. Res. Lett., 41, 9120-9126. Tippett, M. K., S. J. Camargo, and A. H. Sobel, 2011.: A poisson regression index for tropical cyclone genesis and the role of large-scale vorticity in genesis. J. Clim, 24, 2335-2357. Tory, K. J., S. S. Chand, J. L. McBride, H. Ye, and R. A. Dare, 2013: Projected changes in late-twenty-first-century tropical cyclone frequency in 13 coupled climate models from phase 5 of the Coupled Model Intercomparison Project, J. Clim., 26(24), 9946-9959. Tsou, C.-H., P.-Y. Huang, C.-Y. Tu, C.-T. Chen, T.-P. Tzeng, and C.-T. Cheng, 2016: Present simulation and future typhoon activity projection over western North Pacific and Taiwan/East Coast of China in 20-km HiRAM climate model. Terr. Atmos. Ocean. Sci., 27, 687-703. ____, H.-H. Hsu, and P.-C. Hsu, 2014: The role of multiscale interaction in synoptic-scale eddy kinetic energy over the western North Pacific in autumn. J. Clim., 27(10), 3750-3766. Tsuboki, K., M. K. Yoshioka, T. Shinoda, M. Kato, S. Kanada, and A. Kitoh, 2015: Future increase of supertyphoon intensity associated with climate change. Geophys. Res. Lett., 42, 646-652. Tu, S., J. Xu, J. C. L. Chan, K. Huang, F. Xu, and L. S. Chiu, 2021: Recent global decrease in the inner-core rain rate of tropical cyclones. Nat. Commun., 12, 1948. Tuleya, R. E., M. Bender, T. R. Knutson, J. J. Sirutis, B. Thomas, and I. Ginis, 2016: Impact of upper-tropospheric temperature anomalies and vertical wind shear on tropical cyclone evolution using an idealized version of the operational GFDL hurricane model. J. Atmos. Sci., 73, 3803-3820. van Vuuren, D. P., and Coauthors, 2011: The representative concentration pathways: An overview. Clim. Change, 109, 5-31. Vecchi, G., and B. Soden, 2007: Effect of remote sea surface temperature change on tropical cyclone potential intensity. Nature, 450, 1066-1070. ____., and Coauthors, 2019: Tropical cyclone sensitivities to CO2 doubling: roles of atmospheric resolution, synoptic variability and background climate changes. Clim. Dyn., 53, 5999-6033. Walsh, K. J. E., and Coauthors, 2015: Hurricanes and climate: The U.S. CLIVAR working group on hurricanes. Bull. Amer. Meteorol. Soc., 96, no. 6, 997-1017. Wang, Y., and C.-C. Wu, 2004: Current understanding of tropical cyclone structure and intensity changes – a review. Meteorol Atmos Phys, 87, 257-278. Wing, A. A., K. A. Emanuel, and S. Solomon, 2015: On the factors affecting trends and variability in tropical cyclone potential intensity. Geophys. Res. Lett., 42, 8669- 8677. Wu, M. C., W. L. Chang, and W. M. Leung, 2004: Impacts of El Ni?o–Southern Oscillation events on tropical cyclone landfalling activity in the western North Pacific. J. Clim., 17(6), 1419-1428. Yamaguchi M., and S. Maeda, 2020: Increase in the number of tropical cyclones approaching Tokyo since 1980. J. Meteorol. Soc. Japan, Ser. II, 98, 775-786. ____, J. C. L. Chan, I-J. Moon, K. Yoshida, and R. Mizuta, 2020: Global warming changes tropical cyclone translation speed. Nat. Commun., 11, 47. Yokoi, S., C. Takahashi, K. Yasunaga, and R. Shirooka, 2012: Multi-model projection of tropical cyclone genesis frequency over the western North Pacific: CMIP5 results. SOLA, 8, 137-140. Yoshida, K., M. Sugi, R. Mizuta, H. Murakami, and M. Ishii, 2017: Future changes in tropical cyclone activity in high-resolution large-ensemble simulations. Geophys. Res. Lett., 44, 9910-9917. Zeng, Z., Y. Wang, and C.-C. Wu, 2007: Environmental dynamical control of tropical cyclone intensity—an observational study. Mon. Weather Rev, 135(1), 38-59. Zhao, J. W., R. F. Zhan, Y. Q. Wang, S.-P. Xie, and Q. Wu, 2020: Untangling impacts of global warming and Inter-decadal Pacific Oscillation on long-term variability of North Pacific tropical cyclone track density. Sci. Adv., 6(41), eaba6813. Zhao, M., I. M. Held, S.-J. Lin, and G. A. Vecchi, 2009: Simulations of global hurricane climatology, interannual variability, and response to global warming using a 50-km resolution GCM. J. Clim., 22, 6653-6678. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/83765 | - |
| dc.description.abstract | 本研究中，使用群集分析的方法討論High Resolution Atmospheric Model (HiRAM) 模擬的西北太平洋颱風在氣候暖化下的變化。除了缺少足夠的較強颱風數量，HiRAM的颱風活動模擬表現良好，生成位置與季節性大致與觀測相符，特別是登陸在菲律賓北部、台灣、中國東部沿海及日韓地區的C1颱風，以及在菲律賓或南海生成影響南海附近地區的颱風，兩者數量相當接近觀測。在RCP8.5 (Representative Concentration Pathways 8.5) 的暖化情境下，HiRAM模擬結果顯示未來二十一世紀末的颱風數量明顯減少，且颱風生命期間最大強度的最大值提升，表示更強颱風出現的可能性。透過群集分析將現在與未來的颱風一起分成六類，檢視各類的強度、路徑、生成位置及移動速率等變化，每一類對氣候暖化的反應程度並不相同。其中，C1颱風和生成位置及活動範圍較靠近中太平洋的北轉颱風的平均生命期間最大強度顯著增加，平均增強速率顯著增加與幾乎不變的增強時間為主要原因。 考慮到模式表現以及對人類活動的影響程度，選擇C1颱風的增強速率增加為分析對象，並檢驗其主要增強區域平均環境場的改變。在HiRAM的未來模擬中，因為大氣-海洋的熱力不平衡明顯增加，西北太平洋各處的PI增加，代表颱風可從熱力環境得到更多的能量。但中層大氣的熵減少，使得乾空氣透過風切阻礙颱風發展的影響提升，環境變得不利於颱風發展。為了瞭解颱風的結構變化與其對發展過程的影響，利用WRF (Weather Research and Forecasting) 模式做較高水平解析度的理想實驗。在未來C1颱風主要增強區域的環境條件下，颱風初期的增強速率提高，生命期最大強度中，地表最大風速提升3-5 m s-1，中心氣壓下降5-8 hPa。結構方面出現較垂直的眼牆及較高暖心位置，環流結構也從低層延伸至更高的範圍，眼強活躍的對流活動持續時間增加。雖然垂直風切為中等風切，但颱風雨帶於整個模擬時間並無明顯的不對稱性，風切導致乾冷空氣逸入的不利影響可能因為地表通量較高而抵銷。定性來說，C1颱風於主要的增強區域，未來的氣候環境場相比於當今的氣候環境場，更有可能使颱風發展至更強的強度。 | zh_TW |
| dc.description.abstract | The responses of tropical cyclones (TCs) in the western North Pacific (WNP) to changing climate are investigated based on clustering analysis of TC tracks simulated with a modified High Resolution Atmospheric Model (HiRAM). TC activities in the present climate are well simulated, except for a lack of intense TCs. Under the Representative Concentration Pathways 8.5 (RCP8.5) scenario, HiRAM projects that the number of TC declines significantly and their lifetime maximum intensity (LMI) distribution extends toward higher intensity in the late 21st century. Furthermore, the mean LMI increases significantly in two TC clusters. In these two clusters, an enhanced mean intensification rate, together with a barely-unchanged mean intensifying duration, account for the elevated mean LMI in the warmer future. One of them (hereafter C1) contains strong TCs affecting a wide range of the coastal regions of East Asia and the northern Philippines. Examinations of a variety of TC metrics show that HiRAM particularly well simulates TCs in C1. Considering the model performance and the great impact to human activity, we investigate the physical links between the TC responses in C1 (e.g., the increased mean intensification rate) and the environmental changes in the main intensifying region of C1 TCs. In the future projections, TC’s potential intensity becomes higher all over the WNP, due to the increase in thermodynamic air-sea disequilibrium. However, lower entropy air in the mid-levels provides more detrimental conditions for TC intensification. To investigate how the TC vortex structure changes, numerical experiments in specific idealized settings are conducted by using the Weather Research and Forecasting (WRF) Model. With future environmental conditions, TC experiences enhanced intensification and reaches stronger maximum 10-m wind speed by 3-5 m s-1 and lower minimum central pressure by 5-8 hPa. As for the structure, straighter eyewall, higher altitude of warm core and great vertical extent of the cyclonic circulation help the vortex maintain its intensity, accompanied by consistent active convection. Stronger vertical wind shear doesn’t cause obvious asymmetric rainband, given that its ventilation effect may be counteracted by more surface heat flux. In conclusion, the environmental conditions in the main intensifying region of C1 under warmer climate facilitates TCs development and stronger intensity. | en |
| dc.description.provenance | Made available in DSpace on 2023-03-19T21:17:08Z (GMT). No. of bitstreams: 1 U0001-0308202220103800.pdf: 12708653 bytes, checksum: b5315410ce592479f815ae00ebbc105b (MD5) Previous issue date: 2022 | en |
| dc.description.tableofcontents | 致謝 I 摘要 II Abstract III 表目錄 VII 圖目錄 VIII 第一章 前言 1 1.1研究背景 1 1.2文獻回顧 2 1.2.1氣候變遷下颱風活動變化 2 1.2.2群集分析(cluster analysis) 6 1.3研究動機及目的 9 第二章 資料與方法 10 2.1 全球模式-HiRAM 10 2.2 颱風觀測路徑資料 11 2.3 群集方法(cluster technique) 11 第三章 颱風在未來的變化_群集分析 14 3.1 模式表現評估 14 3.2 未來颱風活動的變化 17 第四章 未來環境的變化 21 4.1 濾除颱風 21 4.2 綜觀環境 23 第五章 理想實驗模擬 28 5.1 模式介紹與設定 28 5.2 實驗設計 29 5.2 實驗結果 31 第六章 結論與未來工作 34 6.1 HiRAM 模擬及推估 34 6.2 WRF理想實驗 37 6.3未來工作 38 參考文獻 39 表格 48 圖片 51 | |
| dc.language.iso | zh-TW | |
| dc.subject | 理想模擬 | zh_TW |
| dc.subject | 颱風活動 | zh_TW |
| dc.subject | 氣候變遷 | zh_TW |
| dc.subject | 群集分析 | zh_TW |
| dc.subject | 增強速率 | zh_TW |
| dc.subject | Tropical cyclone activity | en |
| dc.subject | Idealized simulation | en |
| dc.subject | Intensification rate | en |
| dc.subject | Cluster analysis | en |
| dc.subject | Climate change | en |
| dc.title | 氣候變遷下颱風活動的變化 – HiRAM模式模擬路徑群集分析以及理想實驗模擬 | zh_TW |
| dc.title | Typhoon Activities under the Changing Climate – Track-Cluster Analysis of HiRAM Projections and Mechanism Study based on Idealized WRF Model Simulations | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 110-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 許晃雄(Huang-Hsiung Hsu),連國淵(Guo-Yuan Lien) | |
| dc.subject.keyword | 颱風活動,氣候變遷,群集分析,增強速率,理想模擬, | zh_TW |
| dc.subject.keyword | Tropical cyclone activity,Climate change,Cluster analysis,Intensification rate,Idealized simulation, | en |
| dc.relation.page | 101 | |
| dc.identifier.doi | 10.6342/NTU202202029 | |
| dc.rights.note | 未授權 | |
| dc.date.accepted | 2022-08-05 | |
| dc.contributor.author-college | 理學院 | zh_TW |
| dc.contributor.author-dept | 大氣科學研究所 | zh_TW |
| 顯示於系所單位： | 大氣科學系 | |
文件中的檔案：
| 檔案 | 大小 | 格式 | |
|---|---|---|---|
| U0001-0308202220103800.pdf 未授權公開取用 | 12.41 MB | Adobe PDF |
系統中的文件，除了特別指名其著作權條款之外，均受到著作權保護，並且保留所有的權利。