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：135

、訪客IP：18.225.195.163

姓名	蔡沛蓉(Pei-Jung Tsai)  查詢紙本館藏	畢業系所	大氣科學學系
論文名稱	(Extreme Heavy Rainfall Event on 01-02 June 2017 over Northern Taiwan Area: Analysis of Radar Observation and Ensemble Simulations)
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)	本研究主要探討2017年6月1日至02日台灣北部梅雨鋒面個案。此鋒面於清晨滯留於台灣北部並在8小時內降下超過300毫米之累積雨量，本研究透過觀測資訊和數值模擬結果進而探討此極端降雨事件的主要肇始原因，依雷達資料和紅外線色調強化衛星圖，可將鋒面系統按生命期分為三個階段，分別為南移階段、MCS合併階段與MCS重建階段，由多都卜勒風場合成系統(Wind Synthesis System using Doppler Measurements, WISSDOM) 反演得水平解析為1 km及高度解析為0.5 km之三維風場，除作為鋒面移動動力及結構探討的工具外，後續也作為與模式模擬比較時的動力參考及真實場。為了了解鋒面強降雨事件形成之條件及特徵，本研究利用美國國家海洋和大氣管理局之全球預報模式 (National Centers for Environmental Prediction, NCEP) 提供之全球最終再分析場資料 (Final operational global analysis, FNL) 進而擾動、積分取得 128 支系集模擬成員，並透過 K-means 群集分析設8小時內累積降水100 毫米為閾值，最終可將128 支系集分為五群，分布於台灣北部外海、北部沿海以及內陸地區，藉由反演風場及群集分析結果探討此個案中影響鋒面滯留、至災主要之中尺度-α和中尺度-β關鍵動力因素，結果顯示地形噴流對於極端降水為重要的前導因素，近一步利用模式環境場檢視發現槽與雨帶間存在著一定的相關性，隨著北方短波槽東移接近台灣，台灣西側氣壓梯度力增加，進而影響西南季風之增強，而在風場與地形交互作用下形成更強之噴流，並控制著鋒面強度及雨帶位置，使得短波槽移出之時間間接影響強降雨位置。總結來說，利用觀測及反演場除了能分析梅雨動力結構，更可進一步檢視模式模擬的表現，而在系集綜觀環境場的輔助下，有助於了解鋒面表現及其不同尺度之動力特徵。
摘要(英)	During 01-02 June 2017, a Mei-Yu front with accumulated rainfall over 550 mm in 8 hours occurred and stagnated at northern Taiwan in the early morning. The study examined the main features of extreme rainfall event through both observational data and numerical model simulations. Based on the observations of radar data and infrared satellite images, the lifetime of the frontal system is divided into three stages when investigating the characteristic of this event, and they are southward moving stage, MCS merging stage, and back-building stage. Three-dimensional wind fields are retrieved at 1-km horizontal resolution by the Wind Synthesis System using Doppler Measurements (WISSDOM) through two radar sites, and the synthetic winds are used as reference when comparing to model simulations. To fully comprehend the characteristics caused this event, the 128-member ensemble simulations, which were obtained and perturbed from National Centers for Environmental Prediction (NCEP) Final operational global analysis (FNL), are generated. The K-means clustering analysis is applied to classify the 128-ensemble into five groups by a threshold of 100 mm/8-hr. These five clusters illustrated different locations of extreme rainfall: some were over the ocean, and some were inland near west coast or northeast of Taiwan. Through retrieved wind field and cluster analysis, the dynamic features in both meso-α and meso-β scales are discussed to identify the key factors that can make the front stagnate and produce such heavy rainfall in northern Taiwan. The result shows that the barrier jet stands as a significant lead in the extreme rainfall process. Further inspection of large-scale simulations reveals a connection between the trough and the spatial distribution of rainbands. When the short-wave trough at north gets close to Taiwan, the intensification of pressure gradient force at west would strengthen the southwesterly flow and result in a stronger jet which could control the strength and position of the frontal system. The movement of the trough would affect the rainband position indirectly. In conclusion, the observations not only can help us analyze the dynamic structure of Mei-Yu front but also to inspect the performance of model simulations. Further, the overview of the Mei-Yu process in different scales is revealed through the clustered ensemble simulations.
關鍵字(中)	★ 極端強降水 ★ K-means分群 ★ 系集模擬 ★ 雷達觀測	關鍵字(英)	★ extreme heavy rainfall ★ K-means clustering ★ ensemble simulation ★ radar observations
論文目次	摘要 i Abstract ii Acknowledgment iv Chapter 1 Introduction 1 Chapter 2 Data and Methodology 7 2.1 Data 7 2.2 Wind Synthesis System using Doppler Measurements (WISSDOM) 9 2.3 Model configuration 13 2.4 Cluster analysis 15 Chapter 3 Case overview 18 3.1 2017/06/01-02 Mei-Yu case 18 Chapter 4 Result: Part I -WISSDOM 24 4.1 Retrieval of 2017 Mei-Yu case 24 Chapter 5 Result: Part II – Cluster analysis 39 5.1 Performance of ensemble simulations 39 5.2 Dynamic characteristic of clustering result 59 Chapter 6 Summary and future works 75 6.1 Summary 75 6.2 Future works 78 References 82
參考文獻	簡芳菁、柳懿秦、周仲島、林沛練、洪景山、蕭玲鳳，2005：2003年梅雨季MM5系集降水預報 李志昕、洪景山，2014：區域系集預報系統研究：系集成員產生方式之評估 蘇凱翊，2016：使用群集分析分類綜觀尺度天氣型態以探討台灣北部地區午後熱對流系統局部環流結構與系統發展特性，碩士論文，國立中央大學大氣物理研究所 施筱柔，2019：2017年6月2-3日梅雨鋒面個案分析，碩士論文，國立中央大學大氣物理研究所 鄭羽廷，2019：同化雷達觀測與反演變數改善模式對流尺度降雨預報能力：探討OSSE與真實個案，碩士論文，國立中央大學大氣物理研究所 陳奕安，2019：多都卜勒氣象雷達反演之垂直速度的剖風儀驗證及高解析度三維風場反演能力的測試，碩士論文，國立中央大學大氣物理研究所 蔡博安，2020：評估TAHOPE觀測實驗同化S-PolKa徑向風、回波與折射指數對短期降雨預報的影響：觀測系統模擬實驗(OSSE)之測試，碩士論文，國立中央大學大氣物理研究所 莊秉學，2021：使用局地系集轉換卡爾曼濾波器同化雙偏極化參數的全新方法：夏季真實個案中的分析場與預報場，碩士論文，國立中央大學大氣物理研究所 蘇奕叡、賴曉薇等，2021：WEPS降雨情境預報於梅雨預報應用之發展 Chen, C.-H., Chung, K.-S., Yang, S.-C., & Chen, L.-H. (2021). Sensitivity of Forecast Uncertainty to Different Microphysics Schemes within a Convection-Allowing Ensemble during SoWMEX-IOP8. Monthly Weather Review, 149(12), 4145-4166. https://doi.org/10.1175/mwr-d-20-0366.1 Chen, G. T.-J., Wang, C.-C., & Lin, D. D.-W. (2005). Characteristics of Low-Level Jets over Northern Taiwan in Mei-Yu Season and Their Relationship to Heavy Rain Events. Monthly Weather Review, 133, 20-43. https://doi.org/10.1175/MWR-2813.1. Chen, G. T.-J., & Yu, C.-C. (1988). Study of Low-Level Jet and Extremely Heavy Rainfall over Northern Taiwan in the Mei-Yu Season. Monthly Weather Review, 116, 884-891. https://doi.org/10.1175/1520-0493(1988)116<0884:SOLLJA>2.0.CO;2 Chen, Y.-L., Chu, Y.-J., Chen, C.-S., Tu, C.-C., Teng, J.-H., & Lin, P.-L. (2018). Analysis and Simulations of a Heavy Rainfall Event over Northern Taiwan during 11–12 June 2012. Monthly Weather Review, 146(9), 2697-2715. https://doi.org/10.1175/mwr-d-18-0001.1 Chen, Y.-L., & Li, J. (1995). Characteristics of Surface Airflow and Pressure Patterns over the Island of Taiwan during TAMEX. Monthly Weather Review, 123, 695-716. Chen, Y.-L., Tu, C.-C., Hsiao, F., Chen, C.-S., Lin, P.-L., & Lin, P.-H. (2022). An Overview of Low-Level Jets (LLJs) and Their Roles in Heavy Rainfall over the Taiwan Area during the Early Summer Rainy Season. Meteorology, 1(1), 64-112. https://doi.org/10.3390/meteorology1010006 Chung, K.-S., Chiu, H.-J., Liu, C.-Y., & Lin, M.-Y. (2020). Satellite Observation for Evaluating Cloud Properties of the Microphysical Schemes in Weather Research and Forecasting Simulation: A Case Study of the Mei-Yu Front Precipitation System. Remote Sensing, 12(18). https://doi.org/10.3390/rs12183060 Du, Y., & Chen, G. (2018). Heavy Rainfall Associated with Double Low-Level Jets over Southern China. Part I: Ensemble-Based Analysis. Monthly Weather Review, 146(11), 3827-3844. https://doi.org/10.1175/mwr-d-18-0101.1 Dudhia, J. (1989). Numerical Study of Convection Observed during the Winter Monsoon Experiment Using a Mesoscale Two-Dimensional Model. Journal of the Atmospheric Sciences, 46(20), 3077–3107. https://doi.org/https://doi.org/10.1175/1520-0469(1989)046<3077:NSOCOD>2.0.CO;2 Hong, S.-Y., Kim, J.-H., Kim, J.-o., & Dudhia, J. (2006). The WRF single moment microphysics scheme (WSM). Journal of the Korean Meteorological Society, 42, 129-151. Ke, C.-Y., Chung, K.-S., Chen Wang, T.-C., & Liou, Y.-C. (2019). Analysis of heavy rainfall and barrier-jet evolution during Mei-Yu season using multiple Doppler radar retrievals: a case study on 11 June 2012. Tellus A: Dynamic Meteorology and Oceanography, 71(1). https://doi.org/10.1080/16000870.2019.1571369 Kohone. (2001). Self-Organizing Maps. Kuo, Y.-H., & Chen, G. T.-J. (1990). The Taiwan Area Mesoscale Experiment(TAMEX): An Overview. Bulletin of the American Meteorological Society, 71(4), 488-503. https://doi.org/10.1175/1520-0477(1990)071<0488:TTAMEA>2.0.CO;2 Lang, S. E., Tao, W.-K., Chern, J.-D., Wu, D., & Li, X. (2014). Benefits of a Fourth Ice Class in the Simulated Radar Reflectivities of Convective Systems Using a Bulk Microphysics Scheme. Journal of the Atmospheric Sciences, 71(10), 3583-3612. https://doi.org/10.1175/jas-d-13-0330.1 Li, J., & Chen, Y.-L. (1998). Barrier Jets during TAMEX. Monthly Weather Review, 126, 959-971. https://doi.org/10.1175/1520-0493(1998)126<0959:BJDT>2.0.CO;2 Li, J., Chen, Y.-L., & Lee, W.-C. (1997). Analysis of a Heavy Rainfall Event during TAMEX. Monthly Weather Review, 125, 1060-1082. https://doi.org/10.1175/1520-0493(1997)125<1060:AOAHRE>2.0.CO;2 Lin, Y.-F., Wu, C.-C., Yen, T.-H., Huang, Y.-H., & Lien, G.-Y. (2020). Typhoon Fanapi (2010) and its Interaction with Taiwan Terrain – Evaluation of the Uncertainty in Track, Intensity and Rainfall Simulations. Journal of the Meteorological Society of Japan. Ser. II, 98(1), 93-113. https://doi.org/10.2151/jmsj.2020-006 Liou, Y.-C., Chang, S.-F., & Sun, J. (2012). An Application of the Immersed Boundary Method for Recovering the Three-Dimensional Wind Fields over Complex Terrain Using Multiple-Doppler Radar Data. Monthly Weather Review, 140(5), 1603-1619. https://doi.org/10.1175/mwr-d-11-00151.1 Liou, Y.-C., & Chang, Y.-J. (2009). A Variational Multiple–Doppler Radar Three-Dimensional Wind Synthesis Method and Its Impacts on Thermodynamic Retrieval. Monthly Weather Review, 137(11), 3992-4010. https://doi.org/10.1175/2009mwr2980.1 Liou, Y.-C., Chiou, J.-L., Chen, W.-H., & Yu, H.-Y. (2014). Improving the Model Convective Storm Quantitative Precipitation Nowcasting by Assimilating State Variables Retrieved from Multiple-Doppler Radar Observations. Monthly Weather Review, 142(11), 4017-4035. https://doi.org/10.1175/mwr-d-13-00315.1 Liou, Y.-C., Yang, P.-C., & Wang, W.-Y. (2019). Thermodynamic Recovery of the Pressure and Temperature Fields over Complex Terrain Using Wind Fields Derived by Multiple-Doppler Radar Synthesis. Monthly Weather Review, 147(10), 3843-3857. https://doi.org/10.1175/mwr-d-19-0059.1 Mlawer, E. J., Taubman, S. J., Brown, P. D., Iacono, M. J., & Clough, S. A. (1997). Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave. Journal of Geophysical Research: Atmospheres, 102(D14), 16663-16682. https://doi.org/10.1029/97jd00237 Raut, B. A., de la Fuente, L., Seed, A. W., Jakob, C., & Reeder, M. J. (2012). Application of a Space-Time Stochastic Model for Downscaling Future Rainfall Projections. Sydney, Australia: Engineers Australia, 579-586. Tao, W.-K., Simpson, J., Baker, D., Braun, S., Chou, M., Ferrier, B., Johnson, D. E., Khain, A., Lynn, B., Shie, C., Starr, D., Sui, C., Wang, Y., & Wetzel, P. (2003). Microphysics, radiation and surface processes in the Goddard Cumulus Ensemble (GCE) model. Meteorology and Atmospheric Physics, 82, 97-137. https://doi.org/10.1007/s00703-001-0594-7 Tao, W.-K., Simpson, J., & McCumber, M. (1989). An Ice-Water Saturation Adjustment. Tao, W. K., Wu, D., Lang, S., Chern, J. D., Peters-Lidard, C., Fridlind, A., & Matsui, T. (2016, Feb 16). High-resolution NU-WRF simulations of a deep convective-precipitation system during MC3E: Further improvements and comparisons between Goddard microphysics schemes and observations. J Geophys Res Atmos, 121(3), 1278-1305. https://doi.org/10.1002/2015JD023986 Teng, H.-F., Lee, C.-S., Hsu, H.-H., Done, J. M., & Holland, G. J. (2019). Tropical Cloud Cluster Environments and Their Importance for Tropical Cyclone Formation. Journal of Climate, 32(13), 4069-4088. https://doi.org/10.1175/jcli-d-18-0679.1 Tu, C.-C., Chen, Y.-L., Chen, C.-S., Lin, P.-L., & Lin, P.-H. (2014). A Comparison of Two Heavy Rainfall Events during the Terrain-Influenced Monsoon Rainfall Experiment (TiMREX) 2008. Monthly Weather Review, 142(7), 2436-2463. https://doi.org/10.1175/mwr-d-13-00293.1 Tu, C.-C., Chen, Y.-L., Chen, S.-Y., Kuo, Y.-H., & Lin, P.-L. (2017). Impacts of Including Rain-Evaporative Cooling in the Initial Conditions on the Prediction of a Coastal Heavy Rainfall Event during TiMREX. Monthly Weather Review, 145(1), 253-277. https://doi.org/10.1175/mwr-d-16-0224.1 Tu, C.-C., Chen, Y.-L., Lin, P.-L., & Huang, M.-Q. (2022). Analysis and Simulations of a Heavy Rainfall Event Associated with the Passage of a Shallow Front over Northern Taiwan on 2 June 2017. Monthly Weather Review, 150(3), 505-528. https://doi.org/10.1175/MWR-D-21-0113.1 Turgu, E., & Kömüşcü, A. Ü. (2019). Using K-Means Methodology for Reclassifying Rainfall Regions of Turkey. Wang, C.-C., Chiou, B.-K., Chen, G. T.-J., Kuo, H.-C., & Liu, C.-H. (2016). A numerical study of back-building process in a quasistationary rainband with extreme rainfall over northern Taiwan during 11–12 June 2012. Atmospheric Chemistry and Physics, 16(18), 12359-12382. https://doi.org/10.5194/acp-16-12359-2016 Wang, C.-C., Li, M.-S., Chang, C.-S., Chuang, P.-Y., Chen, S.-H., & Tsuboki, K. (2021). Ensemble-based sensitivity analysis and predictability of an extreme rainfall event over northern Taiwan in the Mei-yu season: The 2 June 2017 case. Atmospheric Research, 259. https://doi.org/10.1016/j.atmosres.2021.105684 Yeh, H.-C., & Chen, Y.-L. (2003). Numerical Simulations of the Barrier Jet over Northwestern Taiwan during the Mei-Yu Season. Monthly Weather Review, 131, 1396-1407. https://doi.org/10.1175/1520-0493(2003)131<1396:NSOTBJ>2.0.CO;2 Zhang, Q., Du, Y., Chen, Y.-l., Zhao, Y., & Wang, X. (2014). Numerical Simulations of Spatial Distributions and Diurnal Variations of Low-Level Jets in China during Early Summer. Journal of Climate, 27(15), 5747-5767. https://doi.org/10.1175/jcli-d-13-00571.1
指導教授	鍾高陞 廖宇慶(Kao-Shen Chung Yu-Chieng Liou)	審核日期	2022-8-12
推文	facebook   plurk   twitter   funp   google   live   udn   HD   myshare   reddit   netvibes   friend   youpush   delicious   baidu
網路書籤	Google bookmarks   del.icio.us   hemidemi   myshare