This study investigates the sensitivity of physical parameterization schemes in two regional dynamic models clWRF (the climate Weather Research and Forecasting) and RegCM (the Regional Climate Model) in the simulation of tropical cyclones (TCs) over Western Pacific Ocean and East Sea. The experiments include 12-cases for clWRF model and 6-cases for RegCM model were conducted to run the simulation, with the same domain parameters, resolution 25 km. Results show that the clWRF can simulate TCs well with the Betts-Miller-Janjic convection scheme and WSM6 microphysics, in which convection schemes are more influential, and the RegCM is with the Kain-Fritsch convection scheme and Zeng oceanic flux. Regarding the number of TCs simulation, most of them are higher than observed and CFSnl (Climate Forecast System analysis) data, therein the RegCM is higher than the clWRF.
In this paper, the relationship between Tropical Cyclone (TC) Genesis Potential Index (GPI) and the number of TC (NTC) associated with ENSO over the Vietnam East Sea (VES) was investigated. Observed TC data of the Regional Specialized Meteorological Center (RSMC) Tokyo Typhoon Center and ERA Interim reanalysis data for the period 1985-2015 were used. The results show a good agreement between GPI and NTC over the VES with the correlation coefficient is 0.84. There were more TCs formed over the VES during La Nina years and less TCs during El Nino years. There were positive anomalies of GPI, environmental factors (relative humidity, sea surface temperature, absolute vorticity, potential intensity)over the region where the highest densityof TCs genesis locatedduring La Nina years while there were negative anomalies found during El Nino years. Relative humidity has the largest contribution to the positive difference GPI between La Nina years and El Nino years, the less contribution comes from the potential intensity, absolute vorticity, and wind shear. 92Khảo sát mối quan hệ giữa sự hình thành bão và chỉ số tiềm năng hình thành xoáy thuận nhiệt đới trên khu vực Biển Đông Nhận ngày 17 tháng 4 năm 2019 Chỉnh sửa ngày 03 tháng 6 năm 2019; Chấp nhận đăng ngày 16 tháng 6 năm 2019Tóm tắt: Trong nghiên cứu này mối liên hệ giữa chỉ số tiềm năng hình thành (GPI) và sự hình thành bão trên khu vực biển Đông cũng như vai trò của ENSO đã được khảo sát. Dữ liệu được sử dụng là bão quan trắc từ trung tâm cảnh báo bão RSMC Typhoon Center và số liệu tái phân tích ERA_Interim của Trung tâm Dự báo thời tiết hạn vừa Châu Âu giai đoạn 1985-2015. Kết quả cho thấy GPI và số lượng bão hình thành trung bình tháng trên khu vực có sự liên hệ chặt chẽ với với nhau, với hệ số tương quan cao (0.84). Số lượng bão hình thành trong năm La Nina cao hơn so với năm El Nino, dị thường GPI và các nhân tố môi trường (độ ẩm tương đối, nhiệt độ mặt nước biển, xoáy tuyệt đối, cường độ tiềm năng) trong năm La Nina dương và có tâm dương lớn phù hợp với phân bố bão tập trung trong năm La Nina. Dị thường GPI và các nhân tố môi trường có xu thế âm trong năm El Nino. Độ ẩm tương đối có đóng góp lớn nhất đến độ lệch GPI dương giữa năm La Nina và El Nino, tiếp đến là tốc độ tiềm năng trong khi đóng góp ít nhất là xoáy tuyệt đối và độ đứt gió. Từ khóa: GPI, sự hình thành bão, ENSO, Biển Đông. hoàn lưu qui mô lớn (nhân tố môi trường) [1]. Năm 2004, Emanuel và Nolan [1] đã đưa ra chỉ số tiềm năng hình thành đối với bão khi sử dụng kết hợp các nhân tố môi trường qui mô lớn. Theo
This study has selected a vortex tracking algorithm scheme for simulating the activity of tropical cyclone in the Vietnam East Sea by CCAM model. The results show that the CCAM model is able to simulate well the large scale in each month through a reasonable description of the movement rules of the tropical cyclone in the study area. Then, this vortex tracking algorithm scheme was applied to test the seasonal forecast with the outputs of the CCAM model with a resolution of 20km for September 2018 and October 2018. The obtaining results are forecasted quite closely in terms of both quantity and high potential occurrence areas of the tropical cyclone when compared with reality. In particular, for October 2018, although the activity area of the tropical cyclone - YUTU is significantly different from the multi-year average activity position, the seasonal forecast results are obtained from the 120 members of the CCAM model captured this difference. 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