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Ensemble Forecasting of Tropical Cyclone Motion Using a Baroclinic Model


doi: 10.1007/s00376-006-0342-5

  • The purpose of this study is to investigate the effectiveness of two different ensemble forecasting (EF) techniques–the lagged-averaged forecast (LAF) and the breeding of growing modes (BGM). In the BGM experiments, the vortex and the environment are perturbed separately (named BGMV and BGME). Tropical cyclone (TC) motions in two difficult situations are studied: a large vortex interacting with its environment, and an apparent binary interaction. The former is Typhoon Yancy and the latter involves Typhoon Ed and super Typhoon Flo, all occurring during the Tropical Cyclone Motion Experiment TCM- 90. The model used is the baroclinic model of the University of New South Wales. The lateral boundary tendencies are computed from atmospheric analysis data. Only the relative skill of the ensemble forecast mean over the control run is used to evaluate the effectiveness of the EF methods, although the EF technique is also used to quantify forecast uncertainty in some studies. In the case of Yancy, the ensemble mean forecasts of each of the three methodologies are better than that of the control, with LAF being the best. The mean track of the LAF is close to the best track, and it predicts landfall over Taiwan. The improvements in LAF and the full BGM where both the environment and vortex are perturbed suggest the importance of combining the perturbation of the vortex and environment when the interaction between the two is appreciable. In the binary interaction case of Ed and Flo, the forecasts of Ed appear to be insensitive to perturbations of the environment and/or the vortex, which apparently results from erroneous forecasts by the model of the interaction between the subtropical ridge and Ed, as well as from the interaction between the two typhoons, thus reducing the effectiveness of the EF technique. This conclusion is reached through sensitivity experiments on the domain of the model and by adding or eliminating certain features in the model atmosphere. Nevertheless, the forecast tracks in some of the cases are improved over that of the control. On the other hand, the EF technique has little impact on the forecasts of Flo because the control forecast is already very close to the best track. The study provides a basis for the future development of the EF technique. The limitations of this study are also addressed. For example, the above results are based on a small sample, and the study is actually a simulation, which is different than operational forecasting. Further tests of these EF techniques are proposed.
  • [1] Xubin ZHANG, 2022: Impacts of New Implementing Strategies for Surface and Model Physics Perturbations in TREPS on Forecasts of Landfalling Tropical Cyclones, ADVANCES IN ATMOSPHERIC SCIENCES, 39, 1833-1858.  doi: 10.1007/s00376-021-1222-8
    [2] Ruiqiang DING, Baojia LIU, Bin GU, Jianping LI, Xuan LI, 2019: Predictability of Ensemble Forecasting Estimated Using the Kullback-Leibler Divergence in the Lorenz Model, ADVANCES IN ATMOSPHERIC SCIENCES, , 837-846.  doi: 10.1007/s00376-019-9034-9
    [3] Jie FENG, Ruiqiang DING, Jianping LI, Deqiang LIU, 2016: Comparison of Nonlinear Local Lyapunov Vectors with Bred Vectors, Random Perturbations and Ensemble Transform Kalman Filter Strategies in a Barotropic Model, ADVANCES IN ATMOSPHERIC SCIENCES, 33, 1036-1046.  doi: 10.1007/s00376-016-6003-4
    [4] Jie FENG, Jianping LI, Jing ZHANG, Deqiang LIU, Ruiqiang DING, 2019: The Relationship between Deterministic and Ensemble Mean Forecast Errors Revealed by Global and Local Attractor Radii, ADVANCES IN ATMOSPHERIC SCIENCES, 36, 271-278.  doi: 10.1007/s00376-018-8123-5
    [5] Wansuo DUAN, Lichao YANG, Mu MU, Bin WANG, Xueshun SHEN, Zhiyong MENG, Ruiqiang DING, 2023: Recent Advances in China on the Predictability of Weather and Climate, ADVANCES IN ATMOSPHERIC SCIENCES, 40, 1521-1547.  doi: 10.1007/s00376-023-2334-0
    [6] Jihang LI, Zhiyan ZHANG, Lu LIU, Xubin ZHANG, Jingxuan QU, Qilin WAN, 2021: The Simulation of Five Tropical Cyclones by Sample Optimization of Ensemble Forecasting Based on the Observed Track and Intensity, ADVANCES IN ATMOSPHERIC SCIENCES, 38, 1763-1777.  doi: 10.1007/s00376-021-0353-2
    [7] LI Shan, RONG Xingyao, LIU Yun, LIU Zhengyu, Klaus FRAEDRICH, 2013: Dynamic Analogue Initialization for Ensemble Forecasting, ADVANCES IN ATMOSPHERIC SCIENCES, 30, 1406-1420.  doi: 10.1007/s00376-012-2244-z
    [8] Zhenhua HUO, Wansuo DUAN, Feifan ZHOU, 2019: Ensemble Forecasts of Tropical Cyclone Track with Orthogonal Conditional Nonlinear Optimal Perturbations, ADVANCES IN ATMOSPHERIC SCIENCES, 36, 231-247.  doi: 10.1007/s00376-018-8001-1
    [9] Tian Yongxiang, Luo Zhexian, 1994: Vertical Structure of Beta Gyres and Its Effect on Tropical Cyclone Motion, ADVANCES IN ATMOSPHERIC SCIENCES, 11, 43-50.  doi: 10.1007/BF02656992
    [10] LUO Zhexian, PING Fan, 2012: Simulations of the Motion of Tropical Cyclone-like Vortices in the Presence of Synoptic and Mesoscale Circulations, ADVANCES IN ATMOSPHERIC SCIENCES, 29, 519-528.  doi: 10.1007/s00376-011-1199-9
    [11] Jorge A. REVELLI, Miguel A. RODR, Horacio S. WIO, 2010: The Use of Rank Histograms and MVL Diagrams to Characterize Ensemble Evolution in Weather Forecasting, ADVANCES IN ATMOSPHERIC SCIENCES, 27, 1425-1437.  doi: 10.1007/s00376-009-9153-6
    [12] Shibo GAO, Haiqiu YU, Chuanyou REN, Limin LIU, Jinzhong MIN, 2021: Assimilation of Doppler Radar Data with an Ensemble 3DEnVar Approach to Improve Convective Forecasting, ADVANCES IN ATMOSPHERIC SCIENCES, 38, 132-146.  doi: 10.1007/s00376-020-0081-z
    [13] CHEN Lianshou, LI Ying, CHENG Zhengquan, 2010: An Overview of Research and Forecasting on Rainfall Associated with Landfalling Tropical Cyclones, ADVANCES IN ATMOSPHERIC SCIENCES, 27, 967-976.  doi: 10.1007/s00376-010-8171-y
    [14] SUN Jianqi, Joong Bae AHN, 2011: A GCM-Based Forecasting Model for the Landfall of Tropical Cyclones in China, ADVANCES IN ATMOSPHERIC SCIENCES, 28, 1049-1055.  doi: 10.1007/s00376-011-0122-8
    [15] Li Maicun, 1987: EQUATORIAL SOLITARY WAVES OF TROPICAL ATMOSPHERIC MOTION IN SHEAR FLOW, ADVANCES IN ATMOSPHERIC SCIENCES, 4, 125-136.  doi: 10.1007/BF02677059
    [16] Li Maicun, 1987: ON THE LOW-FREQUENCY, PLANETARY-SCALE MOTION IN THE TROPICAL ATMOSPHERE AND OCEANS, ADVANCES IN ATMOSPHERIC SCIENCES, 4, 249-263.  doi: 10.1007/BF02663596
    [17] CHEN Lianshou, 2004: An Overview of Tropical Cyclone and Tropical Meteorology Research Progress, ADVANCES IN ATMOSPHERIC SCIENCES, 21, 505-514.  doi: 10.1007/BF02915577
    [18] GAO Feng*, Peter P. CHILDS, Xiang-Yu HUANG, Neil A. JACOBS, and Jinzhong MIN, 2014: A Relocation-based Initialization Scheme to Improve Track-forecasting of Tropical Cyclones, ADVANCES IN ATMOSPHERIC SCIENCES, 31, 27-36.  doi: 10.1007/s00376-013-2254-5
    [19] Yan ZHENG, Liguang WU, Haikun ZHAO, Xingyang ZHOU, Qingyuan LIU, 2020: Simulation of Extreme Updrafts in the Tropical Cyclone Eyewall, ADVANCES IN ATMOSPHERIC SCIENCES, 37, 781-792.  doi: 10.1007/s00376-020-9197-4
    [20] DUAN Yihong, WU Rongsheng, YU Hui, LIANG Xudong, Johnny C L CHAN, 2004: The Role of -effect and a Uniform Current on Tropical Cyclone Intensity, ADVANCES IN ATMOSPHERIC SCIENCES, 21, 75-86.  doi: 10.1007/BF02915681

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Manuscript History

Manuscript received: 10 May 2006
Manuscript revised: 10 May 2006
通讯作者: 陈斌, bchen63@163.com
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Ensemble Forecasting of Tropical Cyclone Motion Using a Baroclinic Model

  • 1. Laboratory for Atmospheric Research, Department of Physics and Material Science, City University of Hong Kong, Hong Kong,Laboratory for Atmospheric Research, Department of Physics and Material Science, City University of Hong Kong, Hong Kong

Abstract: The purpose of this study is to investigate the effectiveness of two different ensemble forecasting (EF) techniques–the lagged-averaged forecast (LAF) and the breeding of growing modes (BGM). In the BGM experiments, the vortex and the environment are perturbed separately (named BGMV and BGME). Tropical cyclone (TC) motions in two difficult situations are studied: a large vortex interacting with its environment, and an apparent binary interaction. The former is Typhoon Yancy and the latter involves Typhoon Ed and super Typhoon Flo, all occurring during the Tropical Cyclone Motion Experiment TCM- 90. The model used is the baroclinic model of the University of New South Wales. The lateral boundary tendencies are computed from atmospheric analysis data. Only the relative skill of the ensemble forecast mean over the control run is used to evaluate the effectiveness of the EF methods, although the EF technique is also used to quantify forecast uncertainty in some studies. In the case of Yancy, the ensemble mean forecasts of each of the three methodologies are better than that of the control, with LAF being the best. The mean track of the LAF is close to the best track, and it predicts landfall over Taiwan. The improvements in LAF and the full BGM where both the environment and vortex are perturbed suggest the importance of combining the perturbation of the vortex and environment when the interaction between the two is appreciable. In the binary interaction case of Ed and Flo, the forecasts of Ed appear to be insensitive to perturbations of the environment and/or the vortex, which apparently results from erroneous forecasts by the model of the interaction between the subtropical ridge and Ed, as well as from the interaction between the two typhoons, thus reducing the effectiveness of the EF technique. This conclusion is reached through sensitivity experiments on the domain of the model and by adding or eliminating certain features in the model atmosphere. Nevertheless, the forecast tracks in some of the cases are improved over that of the control. On the other hand, the EF technique has little impact on the forecasts of Flo because the control forecast is already very close to the best track. The study provides a basis for the future development of the EF technique. The limitations of this study are also addressed. For example, the above results are based on a small sample, and the study is actually a simulation, which is different than operational forecasting. Further tests of these EF techniques are proposed.

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