DSpace 集合:https://scholars.lib.ntu.edu.tw/handle/123456789/318172024-03-28T21:47:59Z2024-03-28T21:47:59ZAn Observational Study on the Rapid Intensification of Typhoon Chanthu (2021) near the Complex Terrain of TaiwanFang, Wei TingChang, Pao LiangMING-JEN YANGhttps://scholars.lib.ntu.edu.tw/handle/123456789/6415742024-03-28T10:23:04Z2024-03-01T00:00:00Z標題: An Observational Study on the Rapid Intensification of Typhoon Chanthu (2021) near the Complex Terrain of Taiwan
作者: Fang, Wei Ting; Chang, Pao Liang; MING-JEN YANG
摘要: Intensification of Typhoon Chanthu (2021) along the eastern coast of Taiwan was accompanied by pronounced asymmetry in eyewall convection dominated by wavenumber-1 features, as observed by a dense radar network in Taiwan. The maximum wind speed at 3-km altitude, retrieved from radar observations, exhibited a rapid increase of approximately 18 m s-1 within an 11-h period during the intensification stage, followed by a significant decrease of approximately 19 m s-1 within 8 h during the weakening stage. Namely, Chanthu underwent both rapid intensification (RI) and rapid weakening (RW) within the 24-h analyzed period, posing challenges for intensity forecasts. During the intensifying stages, the region of maximum eyewall convection asymmetry underwent a sudden cyclonic rotation from the eastern to the northern semicircle immediately after the initiation of terrain-induced boundary inflow from the south of the typhoon, as observed by surface station data. This abrupt rotation of eyewall asymmetry exhibited better agreement with radar-derived vertical wind shear (VWS) than that derived from global reanalysis data. This finding suggests that the mesob-scale VWS is more representative for tropical cyclones than meso-α-scale VWS when the terrain-induced forcing predominates in the environmental conditions. Further examination of the radar-derived VWS indicated that the VWS profile pattern provided a more favorable environment for typhoon intensification. In summary, Chanthu's RI was influenced by the three factors: 1) terrain-induced boundary inflow from the south of the typhoon, observed by surface station data; 2) low-level flow pointing toward the upshear-left direction; and 3) weak upper-level VWS.2024-03-01T00:00:00ZThe subseasoanl predictability of the western North Pacific subtropical high and the 2020 record-breaking eventKAI-CHIH TSENGHo, Yun Hsuanhttps://scholars.lib.ntu.edu.tw/handle/123456789/6415712024-03-28T10:17:24Z2024-12-01T00:00:00Z標題: The subseasoanl predictability of the western North Pacific subtropical high and the 2020 record-breaking event
作者: KAI-CHIH TSENG; Ho, Yun Hsuan
摘要: The western North Pacific subtropical high (WNPSH), a prominent feature in the North Pacific during the boreal summer, exerts significant socioeconomic consequences by influencing hydrological extremes such as tropical cyclones, the Meiyu front, and summer heat waves over East Asia. Accurately forecasting the characteristics of the WNPSH over extended timescales is crucial, but subseasonal prediction in this specific context is still in its early stages due to the complex dynamics involved. In this study, we investigate the optimal predictable pattern of the WNPSH using linear stochastic dynamics. Our findings reveal that convection over the Philippine/South China Sea and Japan serves as key precursors, where a dipole vorticity pattern leads to maximum growth of the WNPSH on subseasonal timescales, providing a potential source of predictability. Additionally, we examine the role of optimal predictable patterns in the record-breaking 2020 WNPSH event, and we find that the cumulative effect of stochastic forcing helps explain the sustained features of this extreme case.2024-12-01T00:00:00ZPrediction of Tropical Cyclogenesis Based on Machine Learning Methods and Its SHAP InterpretationLoi, Chi LokCHUN-CHIEH WULiang, Yu Chiaohttps://scholars.lib.ntu.edu.tw/handle/123456789/6415702024-03-28T10:15:36Z2024-03-01T00:00:00Z標題: Prediction of Tropical Cyclogenesis Based on Machine Learning Methods and Its SHAP Interpretation
作者: Loi, Chi Lok; CHUN-CHIEH WU; Liang, Yu Chiao
摘要: This study trains three machine learning models with varying complexity—Random Forest, Support Vector Machine, and Neural Network—to predict cyclogenesis at a forecast lead time of 24 hr for given tropical disturbances identified by an optimized Kalman Filter algorithm. The overall performance is competent in terms of f1-scores (∼0.8) compared to previous research of the same kind. An assessment by SHapley Additive exPlanations (SHAP) values reveals that mid-level (500 hPa) vorticity is the most influential factor in deciding if a tropical disturbance is developing or non-developing for all three models. Wind shear and tilting are found to hold a certain level of importance as well. These results encourage further experiments that use physical models to explore the dynamical, mid-level pathway to tropical cyclogenesis. Another usage of SHAP values in this work is to explain how a machine learning model decides if an individual tropical disturbance case will develop, by listing the contribution of each feature to the output genesis probability, illustrated by a case study of Typhoon Halong. This increases the reliability of the machine learning models, and forecasters can take advantage of such information to issue tropical cyclone formation warnings more accurately. Several caveats of the current machine learning application in the studies of tropical cyclogenesis are discussed and can be considered for future research. These can benefit the interpretation and emphasis of certain output fields in the operational dynamical prediction system, which can contribute to more timely cyclogenesis forecasts.2024-03-01T00:00:00ZIsland-Induced Eyewall Replacement in a Landfalling Tropical Cyclone: A Model Study of Super Typhoon Mangkhut (2018)Lau, K. H.Tam, C. Y.CHUN-CHIEH WUhttps://scholars.lib.ntu.edu.tw/handle/123456789/6415632024-03-28T09:58:51Z2024-02-28T00:00:00Z標題: Island-Induced Eyewall Replacement in a Landfalling Tropical Cyclone: A Model Study of Super Typhoon Mangkhut (2018)
作者: Lau, K. H.; Tam, C. Y.; CHUN-CHIEH WU
摘要: An unconventional, island-induced eyewall replacement (IER) occurred in Super Typhoon Mangkhut (2018) when it crossed Luzon Island. Upon landfall, its original compact eyewall broke down and dissipated rapidly. As Mangkhut exited Luzon and entered the South China Sea, a much larger new eyewall formed at a radius of 150–200 km from the storm center, three times larger than the original one. Unlike the eyewall replacement cycle in intense tropical cyclones, the breakdown of the original eyewall preceded the formation of the new eyewall (NEF) in Mangkhut. This evolution was reproduced reasonably well in a control experiment using the Weather Research and Forecasting Model. Two sensitivity experiments showed that the IER was triggered by Luzon Island, whose terrain is essential for not only the destruction of the original eyewall but also the NEF. In an axisymmetric framework, it is demonstrated for the first time that the NEF was preceded by the following processes: (a) an increase in the outward-directed agradient force in the boundary layer (BL) inflow region after landfall due to differential rates of weakening between the radial pressure gradient and the tangential wind, (b) creation of a BL deceleration zone, (c) localized reinforcement of BL inflow deceleration within the NEF region when Mangkhut re-entered the ocean, following an exisiting framework of an unbalanced dynamical pathway, and (d) strengthening of the BL convergence and uplift which initiated and sustained the deep convection of the new eyewall.2024-02-28T00:00:00Z