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Volume 28 Issue 5

Sep.  2011

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Article >  ADVANCES IN ATMOSPHERIC SCIENCES  > 2011 >  28(5): 1049-1055

A GCM-Based Forecasting Model for the Landfall of Tropical Cyclones in China

  • 1.

    Nansen-Zhu International Research Centre, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, Division of Earth Environmental System, Atmospheric Sciences, Pusan National University, Pusan 609735, Korea,Division of Earth Environmental System, Atmospheric Sciences, Pusan National University, Pusan 609735, Korea


doi: 10.1007/s00376-011-0122-8

  • A statistical dynamic model for forecasting Chinese landfall of tropical cyclones (CLTCs) was developed based on the empirical relationship between the observed CLTC variability and the hindcast atmospheric circulations from the Pusan National University coupled general circulation model (PNU-CGCM). In the last 31 years, CLTCs have shown strong year-to-year variability, with a maximum frequency in 1994 and a minimum frequency in 1987. Such features were well forecasted by the model. A cross-validation test showed that the correlation between the observed index and the forecasted CLTC index was high, with a coefficient of 0.71. The relative error percentage (16.3%) and root-mean-square error (1.07) were low. Therefore the coupled model performs well in terms of forecasting CLTCs; the model has potential for dynamic forecasting of landfall of tropical cyclones.
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    [2] MA Zhanhong, FEI Jianfang, HUANG Xiaogang, CHENG Xiaoping, 2014: Impacts of the Lowest Model Level Height on Tropical Cyclone Intensity and Structure, ADVANCES IN ATMOSPHERIC SCIENCES, 31, 421-434.  doi: 10.1007/s00376-013-3044-9
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    [5] QIN Xiaohao, MU Mu, 2014: Can Adaptive Observations Improve Tropical Cyclone Intensity Forecasts?, ADVANCES IN ATMOSPHERIC SCIENCES, 31, 252-262.  doi: 10.1007/s00376-013-3008-0
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    [8] Feifan ZHOU, Wansuo DUAN, He ZHANG, Munehiko YAMAGUCHI, 2018: Possible Sources of Forecast Errors Generated by the Global/Regional Assimilation and Prediction System for Landfalling Tropical Cyclones. Part II: Model Uncertainty, ADVANCES IN ATMOSPHERIC SCIENCES, 35, 1277-1290.  doi: 10.1007/s00376-018-7095-9
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    • Manuscript History

    Manuscript received: 10 September 2011
    Manuscript revised: 10 September 2011
    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

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    A GCM-Based Forecasting Model for the Landfall of Tropical Cyclones in China

    • 1. Nansen-Zhu International Research Centre, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, Division of Earth Environmental System, Atmospheric Sciences, Pusan National University, Pusan 609735, Korea,Division of Earth Environmental System, Atmospheric Sciences, Pusan National University, Pusan 609735, Korea
    • Manuscript received: 2011-09-10
    • Manuscript revised: 2011-09-10

    Abstract: A statistical dynamic model for forecasting Chinese landfall of tropical cyclones (CLTCs) was developed based on the empirical relationship between the observed CLTC variability and the hindcast atmospheric circulations from the Pusan National University coupled general circulation model (PNU-CGCM). In the last 31 years, CLTCs have shown strong year-to-year variability, with a maximum frequency in 1994 and a minimum frequency in 1987. Such features were well forecasted by the model. A cross-validation test showed that the correlation between the observed index and the forecasted CLTC index was high, with a coefficient of 0.71. The relative error percentage (16.3%) and root-mean-square error (1.07) were low. Therefore the coupled model performs well in terms of forecasting CLTCs; the model has potential for dynamic forecasting of landfall of tropical cyclones.

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