利用耦合模式探討颱風Bavi (2020)在東海的增強過程

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藍鼎鈞(Din-Jyun Lan) 查詢紙本館藏

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水文與海洋科學研究所

論文名稱

利用耦合模式探討颱風Bavi (2020)在東海的增強過程
(Coupled Model Simulations of the Intensification of Typhoon Bavi (2020) in the East China Sea)

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摘要(中)

本研究旨在探討東海與黃海的鹽度分層是否導致了2020年8月颱風Bavi在該區域異常增強。鹽度分層是由長江淡水輸入造成的，它可以形成一個阻隔層(Barrier Layer)，減少垂直混合造成的海表冷卻，有利於颱風的發展。本研究使用COAWST耦合模式，結合大氣模式 (WRF)和海洋模式 (ROMS)，對颱風Bavi通過東海與黃海的過程進行了三維模擬，並比較了有無鹽度分層的情況下，颱風強度會如何變化。
本研究分成三個部分，首先對耦合模式中的大氣模式(WRF)及海洋模式(ROMS)的初始場與邊界條件進行測試。大氣模式在模擬的颱風路徑和強度具有良好的效果，路徑平均誤差為39.6km，強度平均誤差為6kts，顯示模式能夠準確模擬颱風與環境風場的互動。在海洋模式中，使用HYCOM、GLORYS和ORAS5三種全球海洋模式進行初始場測試。結果顯示，GLORYS在模擬東海與黃海區域海洋特性方面有較好的表現，因此將其選為後續耦合模式的海洋模式初始場。
第二部份在東海與黃海區域測試了三種垂直混合參數化方案(LMD、MY2.5、GLS)，對於颱風造成的海表溫度冷卻(SSTC)的模擬效果。實驗結果顯示，颱風通過後，海表溫度在颱風路徑下方和右側出現明顯的冷卻，垂直上經歷了強烈的垂直混合，三種方案中，LMD方案呈現最強的冷卻效應，而MY2.5方案最弱。儘管模擬與衛星觀測之間存在一定的差異，但整體來看，LMD方案在模擬SSTC方面與觀測最為接近，因此選擇LMD方案作為耦合模式中的垂直混合參數化方案。
第三部分進行了兩項模擬，一個是模擬具有鹽度分層的真實海洋，另一個則是將海洋鹽度替換成相同數值，不具有鹽度分層的海洋環境。在有和沒有鹽度分層的對比實驗結果顯示，無鹽度分層實驗中，颱風造成最大冷卻比鹽度分層實驗少了約3°C，海洋表面冷卻較弱，颱風獲得的潛熱通量多了9.5％，潛熱通量較高，使得颱風強度較強。存在鹽度分層的情況下，颱風通過時海表冷卻較強，潛熱通量較少，從而使颱風強度相對較弱。

摘要(英)

This study aims to investigate whether the salinity stratification in the East China Sea and the Yellow Sea caused the abnormal intensification of Typhoon Bavi in August 2020. The salinity stratification is caused by the freshwater input from the Changjiang River, which can form a barrier layer (BL) that reduces the sea surface cooling due to vertical mixing, favoring the development of typhoons. This study uses the COAWST coupled model, combining the atmospheric model (WRF) and the ocean model (ROMS), to simulate the three-dimensional process of Typhoon Bavi passing through the East China Sea and the Yellow Sea, and compares how the typhoon intensity changes with and without salinity stratification.
This study is divided into three parts. First, the initial fields and boundary conditions of the atmospheric model (WRF) and the ocean model (ROMS) in the coupled model are tested. The atmospheric model has good performance in simulating the typhoon track and intensity, the average track error is 39.6 km, and the average intensity error is 6 kts, indicating that the model can accurately simulate the interaction between the typhoon and the environmental wind field. In the ocean model, three global ocean models, HYCOM, GLORYS, and ORAS5, are used for initial field testing. The results show that GLORYS has a better performance in simulating the ocean characteristics in the East China Sea and Yellow Sea regions, and therefore is selected as the initial field of the ocean model for the subsequent coupled model.
The second part of the study tests the simulation effects of three vertical mixing parameterization schemes (LMD, MY2.5, GLS) on the sea surface temperature cooling (SSTC) caused by typhoons in the East China Sea and Yellow Sea regions. The experimental results show that after the typhoon passes, the sea surface temperature under and to the right of the typhoon path experiences significant cooling and intense vertical mixing. Among the three schemes, the LMD scheme presents the strongest cooling effect, while the MY2.5 scheme is the weakest. Although there are certain differences between the simulation and satellite observations, overall, the LMD scheme is closest to the observations in simulating SSTC, so the LMD scheme is chosen as the vertical mixing parameterization scheme in the coupled model.
The third part conducted two simulations, one simulating a real ocean with salinity stratification, and the other replacing the ocean salinity with the same value, an ocean environment without salinity stratification. The comparative experimental results of having and not having salinity stratification show that in the experiment without salinity stratification, the maximum SSTC caused by the typhoon is about 3°C less than the salinity stratification experiment, the ocean surface cooling is weaker, the latent heat flux obtained by the typhoon is 9.5% more, the latent heat flux is higher, making the typhoon stronger. In the case of salinity stratification, when the typhoon passes, the sea surface cools more strongly, the latent heat flux is less, thereby making the typhoon relatively weaker.

關鍵字(中)

★ 颱風
★ 鹽度分層
★ 垂直混合
★ 颱風發展過程

關鍵字(英)

★ Typhoon
★ Salinity Stratification
★ Vertical Mixing
★ Typhoon Development Process

論文目次

中文摘要 i
英文摘要 iii
目錄 v
圖目錄 viii
表目錄 xv
詞彙表 xvi
第一章前言 1
1.1研究背景 1
1.2文獻回顧 2
1.2.1颱風引起的海表溫度冷卻 2
1.2.2颱風發展與增強 4
1.2.3近岸颱風海洋交互作用 5
1.2.4 海洋混合層 6
1.2.5颱風Bavi 7
1.3研究動機與科學目的 7
第二章資料與研究方法 10
2.1 資料來源 10
2.1.1 大氣再分析資料 10
2.1.2 海洋再分析資料 10
2.1.3 最佳路徑 12
2.1.4 Argo浮標資料 13
2.1.5 韓國Ieodo海洋研究站 (Ieodo ORS) 13
2.2.模式介紹與設定 14
2.2.1 耦合模式 14
2.2.2大氣模式 15
2.2.3 海洋模式 15
2.2.4 模式設定 16
2.3 實驗設計 17
2.3.1 大氣模式實驗 17
2.3.2 耦合模式初始場實驗 18
2.3.3垂直混合參數實驗 18
2.3.4鹽度分層與無鹽度分層對颱風影響 18
2.4 颱風尺度特徵與海洋垂直結構定義 19
2.4.1 颱風中心位置與強度 19
2.4.2 海洋混合層與阻隔層 19
第三章海氣耦合模式實驗 21
3.1 大氣模式(WRF)實驗結果 21
3.1.1 颱風路徑與強度校驗 21
3.1.2 海洋環境變數校驗 22
3.2、海洋模式(ROMS)實驗結果 25
3.2.1表面鹽度校驗 25
3.2.2表面溫度校驗 26
3.2.3海洋垂直結構校驗 27
第四章垂直混合參數化方案實驗 31
4.1垂直混合參數化方案 32
4.1.1 Large, McWilliams, and Doney Parameterization (LMD) 32
4.1.2 Mellor and Yamada level 2.5 closure scheme (MY2.5) 32
4.1.3 Generic Length Scale (GLS) 33
4.2海表溫度冷卻校驗 33
第五章鹽度分層實驗 37
5.1 海表溫度與鹽度變化 37
5.2 颱風強度與潛熱通量變化 39
第六章結論與未來工作 43
6.1 結論 43
6.2 未來工作 46
參考文獻 49
附表 61
附圖 67

參考文獻

Argo Science Team (1998). On the design and implementation of argo - a global array of profiling floats. International CLIVAR Project Office. (1998).
Balaguru, K., Patricola, C. M., Hagos, S. M., Leung, L. R., & Dong, L. (2020). Enhanced predictability of eastern North Pacific tropical cyclone activity using the ENSO Longitude Index. Geophysical Research Letters, 47, https://doi.org/ 10.1029/2020GL088849
Balaguru, K.; Chang, P.; Saravanan, R.; Leung, L.R.; Xu, Z.; Li, M.; Hsieh, J.S. Ocean barrier layers’ effect on tropical cyclone intensification. Proc. Natl. Acad. Sci. USA 2012, 109, 14343–14347.
Bao, J.-W. , J.M. Wilczak, J.M., Choi, J.-K., L.H. Kantha, L.H., Numerical simulations of air–sea interaction under high wind conditions using a coupled model: A study of hurricane development, Mon. Wea. Rev., 128 (2000), pp. 2190-2210
Barker, D. M., Huang, W., Guo, Y.-R., Bourgeois, A. J., & Xiao, Q. N. (2004). A three-dimensional variational data assimilation system for MM5: Implementation and initial results. Monthly Weather Review, 132(4), 897–914. https://doi.org/10.1175/1520-0493(2004)132<0897:atvdas>2.0.co;2
Barker, D. M., Huang, X. Y., Liu, Z., Auligné, T., Zhang, X., Rugg, S., et al. (2012). The weather research and forecasting model′s community variational/ensemble data assimilation system: WRFDA. Bulletin of the American Meteorological Society, 93(6), 831–843. https://doi.org/10.1175/BAMS-D-11-00167.1
Beardsley, R. C., Limeburner, R., Yu, H., and Cannon, G. A. (1985). Discharge of the Changjiang (Yangtze river) into the East China sea. Cont. Shelf Res. 4, 57–76. doi: 10.1016/0278-4343(85)90022-6
Belcher, S., Grant, A., Hanley, K., Fox-Kemper, B., Van Roekel, L., Sullivan, P., and Polton, J.: A global perspective on Langmuir turbulence in the ocean surface boundary layer, Geophys. Res. Lett., 39, L18605, https://doi.org/10.1029/2012GL052932, 2012.
Bender, M. A., I. Ginis and Y. Kurihara, 1993. Numerical simulations of tropical cyclone-ocean interaction with a high-resolution coupled model. J. Geophys. Res. 98: 23 245–23 262.
Betts, A. K. (1982). Saturation point analysis of moist convective overturning. Journal of the Atmospheric Sciences, 39(7), 1484-1505.
Biswas, M.; Bernardet, L.; Dudhia, J. Sensitivity of hurricane forecasts to cumulus parameterizations in the Hurricane Weather Research and Forecasting (HWRF) model. Geophys. Res. Lett. 2014, 41.
Booij, N., Ris, M., R.C., Holthuijsen, R.C., L.H., A third-generation wave model for coastal regions: 1. Model description and validation, J. Geophys. Res. Oceans, 104 (C4) (1999), pp. 7649-7666
Brainerd, K.E., Gregg, M.C., Surface mixed and mixing layer depths, Deep-Sea Res., 42 (9) (1995), pp. 1521-1543
Brand, S., 1971: The effects on a tropical cyclone of cooler surface, waters due to upwelling and mixing produced by a prior, tropical cyclone. J. Appl. Meteor., 10, 865–874.
Brasseur, P., Verron, J. The SEEK filter method for data assimilation in oceanography: a synthesis. Ocean Dynamics 56, 650–661 (2006). https://doi.org/10.1007/s10236-006-0080-3
Bryan, G. H. (2012). Effects of surface exchange coefficients and turbulence length scales on the intensity and structure of numerically simulated hurricanes. Monthly Weather Review, 140(4), 1125-1143, DOI: 10.1175/MWR-D-11-00231.1
Byun, D.-S., Kim, Y. W., Lee, J. Y., Lee, E. I., Park, K.-A., and Woo, H.-J. (2018). Converting Ieodo Ocean Research Station wind speed observations to reference height data for real-time operational use. J. Korean Soc. Oceanogr. 23, 153–178.
Byun D-S, Jeong J-Y, Kim D-J, Hong S, Lee K-T and Lee K (2021) Ocean and Atmospheric Observations at the Remote Ieodo Ocean Research Station in the Northern East China Sea. Front. Mar. Sci. 8:618500. doi: 10.3389/fmars.2021.618500
Chandrasekar, R., Balaji, C., Sensitivity of tropical cyclone Jal simulations to physics parameterizations, J. Ear. Syst. Sci., 121 (4) (2012), pp. 923-946
Charney, J. G., & Eliassen, A. (1964). On the growth of the hurricane depression. Journal of Atmospheric Sciences, 21(1), 68-75.
Chassignet, E.P., H.E. Hurlburt, E.J. Metzger, … , R. Bleck (2007). The HYCOM (HYbrid Coordinate Ocean Model) data assimilative system, Journal of Marine Systems , 65(2007) 60-83
Chen, F., & Dudhia, J. (2001). Coupling an advanced land surface–hydrology model with the Penn State–NCAR MM5 modeling system. Part I: Model implementation and sensitivity. Monthly Weather Review, 129(4), 569–585.
Chu, J-H. , C. R. Sampson , A. S. Levine , and E. Fukada , 2002: The Joint Typhoon Warning Center tropical cyclone best-tracks, 1945-2000. U.S. Naval Research Laboratory Rep. NRL/MR/7540-02-16, 22 pp
Cione, J. J. and Uhlhorn, E. W. (2003). Sea Surface Temperature Variability in Hurricanes: Implications with Respect to Intensity Change, Monthly Weather Review, 131(8), 1783-1796, DOI: 10.1175/1520-0493(2003)131<1783:SSTVIH>2.0.CO;2
Cummings, J.A. Operational Multivariate Ocean Data Assimilation. Q. J. R. Meteorol. Soc. 2005, 131, 3583–3604.
Cummings, J.A.; Smedstad, O.M. Variational Data Assimilation for the Global Ocean. In Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol. II); Springer: Berlin/Heidelberg, Germany, 2013; pp. 303–343.
Dai, A., Qian, T., Trenberth, K. E., and Milliman, J. D. (2009). Changes in continental freshwater discharge from 1948 to 2004. J. Clim. 22, 2773–2792. doi: 10.1175/2008JCLI2592.1
de Boyer Montégut, C., Mignot, J., Lazar, A., and Cravatte, S. (2007). Control of salinity on the mixed layer depth in the world ocean: 1. General description. J. Geophys. Res. 112:C06011. doi: 10.1029/2006JC003953
deBoyer Montégut, C., G. Madec, A. S. Fischer, A. Lazar, and D. Iudicone (2004), Mixed layer depth over the global ocean: An examination of profile data and a profile-based climatology, J. Geophys. Res., 109, C12003, doi:10.1029/2004JC002378.
Defant, A. “Physical Oceanography,” Pergamon Press, Oxford, 1961.
Durden, S. L. (2013). Observed tropical cyclone eye thermal anomaly profiles extending above 300 hPa. Monthly weather review, 141(12), 4256-4268.
Durski S, Glenn SM, Haidvogel DB (2004) Vertical mixing schemes in the coastal ocean: comparison of the level 2.5 Mellor-Yamada scheme with an enhanced version of the K proﬁle parameterization. J Geophys Res Oceans 109:C01015.
Dzwonkowski, B. et al. Compounding impact of severe weather events fuels marine heatwave in the coastal ocean. Nat. Commun. 11, 4623 (2020).
Emanuel, K. (1986). An Air-Sea Interaction Theory for Tropical Cyclones. Part I: Steady-State Maintenance, Journal of the Atmospheric Sciences, 43(6), 585-605, DOI: 10.1175/1520-0469(1986)043<0585:AASITF>2.0.CO;2
Emanuel, K. (1995). The behavior of a simple hurricane model using a convective scheme based on subcloud-layer entropy equilibrium. Journal of the Atmospheric Sciences, 52(22), 3960–3968, DOI: 10.1175/1520-0469(1995)052<3960:TBOASH>2.0.CO;2
Emanuel, K. (2016), Zhang, F.. On the Role of Surface Fluxes and WISHE in Tropical Cyclone Intensiﬁcation, Journal of the Atmospheric Sciences, 3739-3747, DOI: https://doi.org/10.1175/JAS-D-16-0100.1
Emanuel, K. A. (1988). The maximum intensity of hurricanes. J. Atmos. Sci, 45(7), 1143-1155.
Emanuel, K. A. (1999). Thermodynamic control of hurricane intensity. Nature, 401(6754), 665-669.
Emanuel, K., Bister, M., and Rotunno, R. (1999). On the Mechanisms of Genesis of Tropical Cyclones, Journal of the Atmospheric Sciences, 56(3), 479-497, DOI: 10.1175/1520-0469(1999)056<0479:OTMOGO>2.0.CO;2
Emanuel, K., Desautels, C., Holloway, C., … Korty, R. (2004). Environmental Control of Tropical Cyclone Intensity, Journal of the Atmospheric Sciences, 61(7), 843-858, DOI: 10.1175/1520-0469(2004)061<0843:ECOTCI>2.0.CO;2
Foltz, G. R. and Mcphaden, M. J. (2009). Impact of Barrier Layer Thickness on SST in the Central Tropical North Atlantic, Journal of Climate, 22(2), 285-299, DOI: 10.1175/2008JCLI2308.1
Gallacher, P. C., R. Rotunno, and K. A. Emanuel, 1989: Tropical cyclogenesis in a coupled ocean–atmosphere model. Preprints, 18th Conf. on Hurricanes and Tropical Meteorology, San Diego, CA, Amer. Meteor. Soc., 121–122.
Galperin, B. , L.H. Kantha, L.H., S. Hassid, S., A. Rosati, A. A quasi-equilibrium turbulent energy model for geophysical flows, Journal of Atmospheric Sciences, 45 (1988), pp. 55-62
Gentemann, C.L., Meissner, T., Wentz, F.J., Accuracy of satellite sea surface temperatures at 7 and 11 GHz, IEEE Trans. Geosci. Remote Sens., 48 (2010), pp. 1009-1018, 10.1109/TGRS.2009.2030322
Gentry, M.S., Lackmann, G.M., Sensitivity of simulated tropical cyclone structure and intensity to horizontal resolution, Mon. Weather Rev., 138 (2010), pp. 688-704
Gray, W. M. (1968). Global view of the origin of tropical disturbances and storms, Mon. Wea. Rev., 96, 669–700
Ha, K. J., Nam, S., Jeong, J. Y., Moon, I. J., Lee, M., Yun, J., Jang, C. J., Kim, Y. S., Byun, D. S., Heo, K. Y., & Shim, J. S. (2019). Observations utilizing Korea ocean research stations and their applications for process studies. Bulletin of the American Meteorological Society, 100(10), 2061-2075. https://doi.org/10.1175/BAMS-D-18-0305.1
Hawkins, H. F., & Imbembo, S. M. (1976). The structure of a small, intense hurricane—Inez 1966. Monthly weather review, 104(4), 418-442.
Hernández G, Vaquero C, González P, Subira C, Frutos-Vivar F, Rialp G, Laborda C, Colinas L, Cuena R, Fernández R. Effect of Postextubation High-Flow Nasal Cannula vs Conventional Oxygen Therapy on Reintubation in Low-Risk Patients: A Randomized Clinical Trial. JAMA. 2016 Apr 5;315(13):1354-61. doi: 10.1001/jama.2016.2711. PMID: 26975498.
Hill, K.A., Lackmann, G.M., Influence of environmental humidity on tropical cyclone size, Mon. Wea. Rev., 137 (10) (2009), pp. 3294-3315, 10.1175/2009MWR2679.1
Holland, G. J. (1997). The Maximum Potential Intensity of Tropical Cyclones, Journal of the Atmospheric Sciences, 54, 2519–2541, DOI: https://doi.org/10.1175/1520-0469(1997)054<2519:TMPIOT>2.0.CO;2
Hong J-S, Moon J-H, Kim T, You SH, Byun K-Y and Eom H (2022) Role of Salinity-Induced Barrier Layer in Air-Sea Interaction During the Intensification of a Typhoon. Front. Mar. Sci. 9:844003. doi: 10.3389/fmars.2022.844003
Hong, S.Y., Lim, J.O.J., The wrf single-moment 6-class microphysics scheme (wsm6), Asia-Pac. J. Atmos. Sci., 42 (2006), pp. 129-151
Iacono, M., Delamere, J., Mlawer, E., Shephard, M., Clough, S., Collins, D., Radiative forcing by long-lived greenhouse gases: calculations with the AER radiative transfer models, J. Geophys. Res. Atmos., 113 (2008), p. D13, 10.1029/2008JD009944
Jacob, R., Larson, J., and Ong, E.: MxN Communication and Parallel Interpolation in CCSM3 Using the Model Coupling Toolkit, Int. J. High Perf. Comp. App., 19, 293–307, https://doi.org/10.1177/1094342005056116, 2005.
Jin, FF., Boucharel, J. & Lin, II. Eastern Pacific tropical cyclones intensified by El Niño delivery of subsurface ocean heat. Nature 516, 82–85 (2014). https://doi.org/10.1038/nature13958
Jordan, C., Charles, C., & Cleary, A. (2017). Enhancing the Impact of Research: Experimenting with Network Leadership Strategies to Grow a Vibrant Nature-Based Learning Research Network. Interdisciplinary Journal of Partnership Studies, 4(3). https://doi.org/10.24926/ijps.v4i3.175
Julian T. Heming, Fernando Prates, Morris A. Bender, …, Yi Xiao, Review of Recent Progress in Tropical Cyclone Track Forecasting and Expression of Uncertainties, Tropical Cyclone Research and Review, 8(4), 2019, 181-218, https://doi.org/10.1016/j.tcrr.2020.01.001.
Kilic, C. and Raible, C.C. (2013) Investigating the Sensitivity of Hurricane Intensity and Trajectory to Sea Surface Temperatures Using the Regional Model WRF. MeteorologischeZeitschrift,22,685-698.http://dx.doi.org/10.1127/0941-948/2013/0472
Killick R., Fearnhead P., Eckley I.A., Optimal detection of changepoints with a linear computational cost, J. Amer. Statist. Assoc., 107 (500) (2012), pp. 1590-1598, 10.1080/01621459.2012.737745
Kim, Y. S., Jang, C. J., Noh, J. H., Kim, K., Kwon, J., Min, Y., et al. (2019). A Yellow Sea monitoring platform and its scientific applications. Front. Mar. Sci. 6:601. doi: 10.3389/fmars.2019.00601
Kumar, S., Amor, S. N., Chanrion, O., … Neubert, T. (2017). Perturbations to the Lower Ionosphere by Tropical Cyclone Evan in the South Pacific Region, Journal of Geophysical Research: Space Physics, 122(8), 8720-8732, DOI: 10.1002/2017JA024023
Large, W., McWilliams, J., and Doney, S.: Oceanic vertical mixing: A review and a model with nonlocal boundary layer parameterization, Rev. Geophys., 32, 363–403, https://doi.org/10.1029/94RG01872, 1994.
Large, W.G., Yeager, S.G. The global climatology of an interannually varying air–sea flux data set. Clim Dyn 33, 341–364 (2009). https://doi.org/10.1007/s00382-008-0441-3
Larson, J., Jacob, R., and Ong, E.: The Model Coupling Toolkit: A New Fortran90 Toolkit for Building Multiphysics Parallel, Coupled Models, Int. J. High Perf. Comp. App., 19, 277–292, https://doi.org/10.1177/1094342005056116, 2005.
Lee S-K, Park W, van Sebille E, Baringer MO, Wang C, Enfield DB (2011) What caused the significant increase in Atlantic Ocean heat content since the mid-20th century? Geophys Res Lett, 38:L17607.
Lee, C.-Y., & Chen, S. S. (2012). Symmetric and asymmetric structures of hurricane boundary layer in coupled atmosphere–wave–ocean models and observations. J. Atmos. Sci., 69, 3576-3594.
Lee, C.-Y., & Chen, S. S. (2014). Stable Boundary Layer and Its Impact on Tropical Cyclone Structure in a Coupled Atmosphere–Ocean Model. Monthly weather review, 142(5), 1927-1944. doi:https://doi.org/10.1175/MWR-D-13-00122.1
Lee, J. H., Pang, I. C. & Moon, J. H. Contribution of the Yellow Sea bottom cold water to the abnormal cooling of sea surface temperature in the summer of 2011. J. Geophys. Res. Oceans 121, 3777–3789 (2016).
Leipper, D.F.(1967): Observed ocean conditions and hurricane Hilda, 1964, J. Atmos. Sci., 24,182-196.
Lellouche, J.M., Greiner, E., Le Galloudec, O., … , Le Traon, P.Y. (2018). Recent updates to the Copernicus Marine Service global ocean monitoring and forecasting real-time 1/12° high-resolution system, Ocean Sci., 14, 1093–1126, 2018, https://doi.org/10.5194/os-14-1093-2018
Lie, H. J., Cho, C. H., Lee, J. H., and Lee, S. (2003). Structure and eastward extension of the Changjiang River plume in the East China Sea. J. Geophys. Res. 108:3077. doi: 10.1029/2001JC001194
Lin, I. I., Liu, W. T., Wu, C. C., Chiang, J., & Sui, C. H. (2003). Satellite observations of modulation of surface winds by typhoon‐induced upper ocean cooling. Geophysical Research Letters, 30(3).
Lin, I. I., Pun, I. F., & Lien, C. C. (2014). “Category‐6” supertyphoon Haiyan in global warming hiatus: Contribution from subsurface ocean warming. Geophysical Research Letters, 41(23), 8547-8553.
Lin, J., & Qian, T. (2019). Rapid intensification of tropical cyclones observed by AMSU satellites. Geophysical Research Letters, 46(12), 7054-7062.
Liu, B., and L. Xie, 2012: A scale-selective data assimilation approach to improving tropical cyclone track and intensity forecasts in a limited-area model: A case study of Hurricane Felix (2007). Wea. Forecasting, 27(1), 124–140.
Liu, X., Wei, J., Zhang, D. L., & Miller, W. (2019). Parameterizing sea surface temperature cooling induced by tropical cyclones: 1. Theory and an application to Typhoon Matsa (2005). Journal of Geophysical Research: Oceans, 124(2), 1215-1231.
Lukas, R. and Lindstrom, E. (1991). The Mixed Layer of the Western Equatorial Pacific Ocean, Journal of Geophysical Research, 96(C12), 3343-3357, DOI: 10.1029/91JC00687
Marchesiello, P., J. C. McWilliams, and A. Shchepetkin. 2001. Open boundary conditions forlong-term integration of regional oceanic models. Ocean Model., 3, 1–20.
Marks, F. D., Houze, R. A., Gamache, J. F., … Black, M. L. (2008). Structure and Dynamics of the Inner Core of Hurricane Isabel (2003). Part I: Traditional Diagnostic Analysis. Monthly Weather Review, 136(6), 2227-2247, DOI: 10.1175/2007MWR1858.1
Mei, W., Pasquero, C., Primeau, F. (2012). The effect of translation speed upon the intensity of tropical cyclones over the tropical ocean, Geophys. Res. Lett., 39, L07801, doi:10.1029/2011GL050765
Mellor G.L., Yamada T. Development of a turbulence closure model for geophysical fluid problems. Reviews of Geophysics and Space Physics. 1982, 20(4), 851–875. doi:10.1029/RG020i004p00851
Moon, I.-J. and Kwon, S.-J. (2012) Impact of upper-ocean thermal structure on the intensity of Korean peninsula landfall typhoons. Progress in Oceanography, 105, 61–66.
Moon, I.-J., Kim, S.-H., Chan, J. C. L., 2019: Climate change and tropical cyclone trend. Nature, 570, E3–E5, https://doi.org/10.1038/s41586-019-1222-3.
Moon, I. J., Shim, J.-S., Lee, D. Y., Lee, J. H., Min, I. K., and Lim, K. C. (2010). Typhoon researches using the Ieodo Ocean Research Station: part I. importance and present status of typhoon observation. Atmos 20, 247–260.
Moon, N.N., Salehin, I., Parvin, M., Hasan, M.M., Talha, I.M., Debnath, S.C., Nur, F.N., Saifuzzaman, M., A natural language processing based advanced method of unnecessary video detection and the framework model, Int. J. Electr. Comput. Eng. (IJECE) (2021)
Neetu S, Lengaigne M, Vincent E M, Vialard J, Madec G, Samson G, Ramesh Kumar M R and Durand F 2012 Influence of upper-ocean stratification on tropical cyclone-induced surface cooling in the Bay of Bengal J. Geophys. Res. Oceans 117 C12020
Newinger, C., and R. Toumi, 2015: Potential impact of the colored Amazon and Orinoco plume on tropical cyclone intensity. J. Geophys. Res. Oceans, 120, 1296–1317,
https://doi.org/10.1002/2014JC010533.
Oey, L.-Y., Ezra, T., Wang, D.-P., … Yin, X.-Q. (2007). Hurricane-induced motions and interaction with ocean currents, Continental Shelf Research, 27, 1249–1263, https://doi.org/10.1016/j.csr.2007.01.008
Ooyama, K. (1969). Numerical simulation of the life cycle of tropical cyclones. Journal of the Atmospheric Sciences, 26(1), 3-40.
Ooyama, K. (1969). Numerical simulation of the life cycle of tropical cyclones, Journal of the Atmospheric Sciences, 26, 3-40,
DOI: https://doi.org/10.1175/1520-0469(1969)026<0003: NSOTLC>2.0.CO;2
Palmen, E. (1948). On the formation and structure of tropical hurricanes, Geophysics, The University of Chicago Press, 3, 26-38.
Park, J. H., Yeo, D. E., Lee, K., Lee, H., Lee, S. W., Noh, S., . . . Nam, S. (2019). Rapid decay of slowly moving Typhoon Soulik (2018) due to interactions with the strongly stratified northern East China Sea. Geophysical Research Letters, 46(24), 14595-14603.
Peduzzi, P., Chatenoux, B., Dao, H., … Nordbeck, O. (2012). Global trends in tropical cyclone risk, Nature Climate Change, 2(4), 289-294, DOI: 10.1038/nclimate1410
Potter, H., DiMarco, S. F., & Knap, A. H. (2019). Tropical cyclone heat potential and the rapid intensification of Hurricane Harvey in the Texas Bight. Journal of Geophysical Research: Oceans, 124(4), 2440-2451.
Prakash, K. R., Nigam, T., and Pant, V. (2018). Estimation of oceanic subsurface mixing under a severe cyclonic storm using a coupled atmosphere–ocean–wave model. Ocean Sci. 14, 259–272. doi: 10.5194/os-14-259-2018
Price, J. F. (1981). Upper Ocean Response to a Hurricane, Journal of Physical Oceanography, 11(2), 153-175, DOI: 10.1175/1520-0485(1981)011<0153: UORTAH>2.0.CO;2
Price, J. F., 1981: Upper ocean response to a hurricane. J. Phys. Oceanogr.,11, 153–175.
Pun, I.-F., and Coauthors, 2019: Rapid intensification of Typhoon Hato (2017) over shallow water. Sustainability, 11, 3709, https://doi.org/10.3390/su11133709.
Pun, I.-F., Chan, J. C. L., Lin, I.-I., Chan, K. T. F., Price, J. F., Ko, D. S., . . . Huang, H.-C. (2019). Rapid Intensification of Typhoon Hato (2017) over Shallow Water. Sustainability, 11(13), 3709.
Retrieved from https://www.mdpi.com/2071-1050/11/13/3709
Pun, IF., Hsu, HH., Moon, IJ. et al. Marine heatwave as a supercharger for the strongest typhoon in the East China Sea. npj Clim Atmos Sci 6, 128 (2023).
https://doi.org/10.1038/s41612-023-00449-5
Rajeswari, J.J., Blanco, A.M., Unniappan, S. (2020) Phoenixin-20 (PNX-20) Suppresses Food Intake, Modulates Glucoregulatory Enzymes, and Enhances Glycolysis in Zebrafish. American journal of physiology. Regulatory, integrative and comparative physiology. 318(5): R917-R928.
Rappaport, E. N., Franklin, J. L., Avila, L. A., … Tribble, A. S. (2009). Advances and Challenges at the National Hurricane Center, Weather and Forecasting, 24(2), 395-419, DOI: 10.1175/2008WAF2222128.1
Robertson R, Hartlipp P. Surface wind mixing in the Regional Ocean Modeling System (ROMS). Geosci Lett. 2017;4(1):24. doi: 10.1186/s40562-017-0090-7. Epub 2017 Nov 2. PMID: 32215239; PMCID: PMC7067273.
Rodgers, E. B., W. S. Olson, V. M. Karyampudi, and H. F. Pierce, 1998: Satellite-derived latent heating distribution and environmental influences in Hurricane Opal (1995). Mon. Wea. Rev., 126 , 1229–1247.
Roemmich, D., Riser, S., Davis, R., and Desaubies, Y. (2004). Autonomous profiling floats: Workhorse for broad-scale ocean observations. Mar. Technol. Soc. J. 38, 21–29. doi: 10.4031/002533204787522802
Rogers, R., S. S. Chen, J. Tenerelli, and H. Willoughby, 2003: A numerical study of the impact of vertical shear on the distribution of rainfall in Hurricane Bonnie (1998). Mon. Wea. Rev., 131, 1577–1599.
Rudzin, J.E., Wadler, J.B., Jaimes de la Cruz, B., …, Li, Q. (2019). A review of recent research progress on the effect of external influences on tropical cyclone intensity change, Tropical Cyclone Research and Review, 12, 200–215,
https://doi.org/10.1016/j.tcrr.2023.09.001
Rudzin, J.E.; Chen, S.; Sanabia, E.R.; Jayne, S.R. The air-sea response during Hurricane Irma’s (2017) rapid intensification over the Amazon-Orinoco River plume as measured by atmospheric and oceanic observations. J. Geophys. Res. Atmos. 2020, 125,
e2019JD032368
Schade, L.R., Emanuel, K.A., The ocean’s effect on the intensity of tropical cyclones: results from a simple coupled atmosphere-ocean model, J. Atmos. Sci., 56 (4) (1999), pp. 642-651, DOI: https://doi.org/10.1175/1520-0469(1999)056<0642: TOSEOT>2.0.CO;2
Schwartz, C. S., Romine, G. S., Sobash, R. A., Fossell, K. R., & Weisman, M. L. (2015). NCAR’s experimental real-time convection-allowing ensemble prediction system. Weather and Forecasting, 30(6), 1645–1654. https://doi.org/10.1175/WAF-D-15-0103.1
Seroka, G. et al. Hurricane Irene sensitivity to stratified coastal ocean cooling. Mon. Weather Rev. 144, 3507–3530 (2016).
Shay, L. K. (2009). Oceanic Heat Content Variability in the Eastern Pacific Ocean for Hurricane Intensity Forecasting, Monthly Weather Review, 138, 6,
DOI: https://doi.org/10.1175/2010MWR3189.1
Shay, L. K., Goni, G. J., and Black, P. G. (2000). Effects of a Warm Oceanic Feature on Hurricane Opal, Monthly Weather Review, 128(5), 1366-1383, DOI: 10.1175/1520-0493(2000)128<1366: EOAWOF>2.0.CO;2
Shchepetkin, A.F., McWilliams, J.C., The regional oceanic modeling system (ROMS): A split-explicit, free-surface, topography-following-coordinate oceanic model, Ocean Model., 9 (2005), pp. 347-404
Shen, W., & Ginis, I. (2003). Effects of surface heat flux‐induced sea surface temperature changes on tropical cyclone intensity. Geophysical Research Letters, 30(18).
Skamarock, W. C., and Coauthors, 2019: A description of the Advanced Research WRF model version 4. NCAR Tech. Note NCAR/TN-556+STR, 145 pp.,
https://doi.org/10.5065/1dfh-6p97.
Skamarock, W. C., Klemp, J. B., Dudhia, J., Gill, D. O., Barker, D. M., Wang, W., & Powers, J. G. (2005). A Description of the Advanced Research WRF Version 2 (No. NCAR/TN-468+STR). University Corporation for Atmospheric Research. doi:10.5065/D6DZ069T
Sprintall, J. and Tomczak, M.: Evidence of the barrier layer in the surface layer of the tropics, J. Geophys. Res.-Oceans, 97, 7305–7316, https://doi.org/10.1029/92JC00407, 1992
Stella Bourdin, Sébastien Fromang, William Dulac, …, Fabrice Chauvin (2022). Intercomparison of four algorithms for detecting tropical cyclones using ERA5, Geoscientific Model Developmen, Geoscientific Model Development, 15(17), 2022, pp.6759-6786, DOI: 10.5194/gmd-15-6759-2022
Sun, J., Mahrt, L., Nappo, C. and Lenschow, D.H. (2015a) Wind and temperature oscillations generated by wave-turbulence interactions in the stably stratified boundary layer. Journal of Atmospheric Science, 72, 1484–1503.
Sutyrin, G. G., and E. A. Agrenich, 1979: Interaction of the boundary layers of the ocean and atmosphere in a tropical cyclone. Meteor. Gidrol.,2, 45–56.
Tang, J., Zhang, J. A., Kieu, C., & Marks, F. D. (2018). Sensitivity of hurricane intensity and structure to two types of planetary boundary layer parameterization schemes in idealized HWRF simulations. Tropical Cyclone Research and Review, 7(4), 201-211.
Troen, I. and L. Mahrt, 1986: A simple model of the atmospheric boundary layer; sensitivity to surface evaporation. Boundary-Layer Meteorol., 37, 129-148.
Umlauf, L., Burchard, H., Hutter, K., Extending the k–ω turbulence model towards oceanic applications, Ocean Modelling, 5(3), 2003, 195-218, https://doi.org/10.1016/S1463-5003(02)00039-2.
Vialard, J., & Delecluse, P. (1998a). An OGCM study for the TOGA decade. Part I: Role of salinity in the physics of the western Pacific fresh pool. Journal of Physical Oceanography, 28(6), 1071–1088. https://doi.org/10.1175/1520-0485(1998)028<1071: aosftt>2.0.co;2
Wallace, J. M., Mitchell, T. P., & Deser, C. (1989). The Influence of Sea-Surface Temperature on Surface Wind in the Eastern Equatorial Pacific: Seasonal and Interannual Variability. Journal of Climate, 2(12), 1492-1499. doi:https://doi.org/10.1175/1520-0442(1989)002<1492:TIOSST>2.0.CO;2
Wallcraft, A.J., Kara, A.B., Hurlburt, H.E., Metzger, J.E., Chassignet, E.P., Halliwell, G.H., 2008. Value of bulk heat flux parameterizations for ocean SST prediction. J. Mar. Syst. 74, doi:10.1016/j.marsys.2008.01.009
Wang B, Kim HJ, Kikuchi K, Kitoh A (2011) Diagnostic metrics for evaluation of annual and diurnal cycles. Clim Dyn 37:941–955
Wang P., Yang Y., Xue D., … , Liao H. (2023). Increasing Compound Hazards of Tropical Cyclones and Heatwaves over Southeastern Coast of China under Climate Warming. Journal of Climate, 36(7), 2243-2257, DOI: https://doi.org/10.1175/JCLI-D-22-0279.1
Wang, W., D. Barker, C. Bruy`ere, M. Duda, J. Dudhia, D. Gill, J. Michalakes, and S. Rizvi, 2008: WRF Version 3 Modeling System User’s Guide.
Wang, Y.-q., & Wu, C.-C. (2004). Current understanding of tropical cyclone structure and intensity changes–a review. Meteorology and Atmospheric Physics, 87(4), 257-278.
Warner, J.C., et al. Development of a Coupled Ocean–Atmosphere–Wave–Sediment Transport (COAWST) Modeling System. Ocean Modell. (2010),
doi: 10.1016/j.ocemod.2010.07.010
Weatherford, C. L., and W. M. Gray (1988a), Typhoon structure as revealed by aircraft reconnaissance. Part I: Data analysis and climatology, Mon. Weather Rev., 116, 1032–1043
Wei, N., Zhang, X.- H., Chen, L.- S., and Hu, H. (2018). Comparison of the effect of easterly and westerly vertical wind shear on tropical cyclone intensity change over the western North Pacific. Environ. Res. Lett. 13 (3), 034020. doi:10.1088/1748-9326/aaa496
Wong Annie P. S., Wijffels Susan E., Riser Stephen C., …, Park Hyuk-Min (2020). Argo Data 1999–2019: Two Million Temperature-Salinity Profiles and Subsurface Velocity Observations from a Global Array of Profiling Floats. Frontiers in Marine Science, 7(700), 23p. Publisher′s official version: https://doi.org/10.3389/fmars.2020.00700
Wu, C.C., Zhan, R., Lu Y., and Wang Y. (2012). Internal variability of the dynamically downscaled tropical cyclone activity over the western North Pacific by the IPRC Regional Climate Model. Journal of Climate, 2104–2122, DOI: https://doi.org/10.1175/JCLI-D-11-00143.1
Wu, L., B. Wang, and S. Geng, 2005: Growing typhoon influence on East Asia. Geophys. Res. Lett., 32, L18703, https://doi.org/10.1029/2005GL022937.
Yamada Y, Satoh M, Sugi M, Kodama C, Noda AT, Nakano M, Nasuno T (2017) Response of tropical cyclone activity and structure to global warming in a high-resolution global nonhydrostatic model. J Clim 30:9703–9724. https://doi.org/10.1175/JCLI-D-17-0068.1
Zhang, F. and Sippel, J. A. (2009). Effects of Initial Condition Errors on Tropical Cyclone Prediction, Journal of the Atmospheric Sciences, 66(1), 40-62,
DOI: 10.1175/2008JAS2730.1
Zhang, H., H. Shu, H., G. Coatrieux, G., J. Zhu, J., Q.J. Wu, Q.J., Y. Zhang, Y., H. Zhu, H., L. Luo, L., Affine legendre moment invariants for image watermarking robust to geometric distortions, IEEE Trans. Image Process., 20 (2011), pp. 2189-2199
Zhong, Q. J., Zhang, L. F., Li, J. P., … , Feng, J. (2018). Estimating the Predictability Limit of Tropical Cyclone Tracks over the Western North Pacific Using Observational Data. Advances in Atmospheric Sciences, 35(12), 1491–1504, DOI: 10.1007/s00376-018-8008-7
ZLloyd, I. D. and Vecchi, G. A. (2011). Observational evidence for oceanic controls on hurricane intensity, Journal of Climate, 24(4), 1138-1153,
DOI: 10.1175/2010JCLI3763.1
Zuo, H., Balmaseda, M. A., Tietsche, S., Mogensen, K., and Mayer, M. (2019). The ECMWF operational ensemble reanalysis–analysis system for ocean and sea ice: a description of the system and assessment, Ocean Sci., 15, 779–808, 7

指導教授

潘任飛(Iam-Fei Pun)

審核日期

2024-1-18

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