Track of Super Typhoon Haiyan Predicted by a Typhoon Model for the South China Sea

+ Author Affiliations + Find other works by these authors
Funds: 

Supported by the China Meteorological Administration Special Public Welfare Research Fund (GYHY201206010) and Guangdong Science and Technology Research Plan (2012A061400012 and 2011A032100006).

PDF

  • Super Typhoon Haiyan was the most notable typhoon in 2013. In this study, results from the operational prediction of Haiyan by a tropical regional typhoon model for the South China Sea are analyzed. It is shown that the model has successfully reproduced Haiyan's rapid passage through the Philippines and its northward deflection after its second landfall in Vietnam. However, the predicted intensity of Haiyan is weaker than the observed. An analysis of higher-resolution model simulations indicates that the storm is characterized by an upper-level warm core during its mature stage and a deep layer of easterly flow. Sensitivity experiments are conducted to study the impact of certain physical processes such as the interaction between stratus and cumulus clouds on the improvement of the typhoon intensity forecast. It is found that appropriate boundary layer and cumulus convective parameterizations, and orographic gravity-wave parameterization, as well as improved initial conditions and increased horizontal grid resolution, all help to improve the intensity forecast of Haiyan.
  • Related Articles

  • Cited by

    Periodical cited type(9)

    1. Yanyan Huang, Yanxia Zhang, Chengzhong Zhang, et al. An assessment of model capability on rapid intensification prediction of tropical cyclones in the South China Sea. Dynamics of Atmospheres and Oceans, 2024, 106: 101431. DOI:10.1016/j.dynatmoce.2023.101431
    2. Jiawen Zheng, Pengfei Ren, Binghong Chen, et al. Research on a Clustering Forecasting Method for Short-Term Precipitation in Guangdong Based on the CMA-TRAMS Ensemble Model. Atmosphere, 2023, 14(10): 1488. DOI:10.3390/atmos14101488
    3. Xubin Zhang. Impacts of New Implementing Strategies for Surface and Model Physics Perturbations in TREPS on Forecasts of Landfalling Tropical Cyclones. Advances in Atmospheric Sciences, 2022, 39(11): 1833. DOI:10.1007/s00376-021-1222-8
    4. Junkyung Kay, Xuguang Wang, Masaya Yamamoto. An Observing System Simulation Experiment (OSSE) to Study the Impact of Ocean Surface Observation from the Micro Unmanned Robot Observation Network (MURON) on Tropical Cyclone Forecast. Atmosphere, 2022, 13(5): 779. DOI:10.3390/atmos13050779
    5. Yanyan Huang, Yerong Feng, Guangfeng Dai, et al. An initialisation scheme for tropical cyclones in the South China Sea. Quarterly Journal of the Royal Meteorological Society, 2021, 147(739): 3096. DOI:10.1002/qj.4118
    6. Rong Zhang, Wenjuan Zhang, Yijun Zhang, et al. Application of Lightning Data Assimilation to Numerical Forecast of Super Typhoon Haiyan (2013). Journal of Meteorological Research, 2020, 34(5): 1052. DOI:10.1007/s13351-020-9145-3
    7. Xubin Zhang, Meiling Chen. Assimilation of Data Derived from Optimal-member Products of TREPS for Convection-Permitting TC Forecasting over Southern China. Atmosphere, 2019, 10(2): 84. DOI:10.3390/atmos10020084
    8. Xubin Zhang. A GRAPES‐based mesoscale ensemble prediction system for tropical cyclone forecasting: configuration and performance. Quarterly Journal of the Royal Meteorological Society, 2018, 144(711): 478. DOI:10.1002/qj.3220
    9. Shen En Chen, Mark E. Leeman, Brandon J. English, et al. Basic Structure System Rating of Post–Super Typhoon Haiyan Structures in Tacloban and East Guiuan, Philippines. Journal of Performance of Constructed Facilities, 2016, 30(5) DOI:10.1061/(ASCE)CF.1943-5509.0000872

    Other cited types(0)

Catalog

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return