Typhoon Track, Intensity, and Structure: From Theory to Prediction

被引:0
|
作者
Zhe-Min Tan
Lili Lei
Yuqing Wang
Yinglong Xu
Yi Zhang
机构
[1] Nanjing University,Key Laboratory of Mesoscale Severe Weather, Ministry of Education, and School of Atmospheric Sciences
[2] University of Hawaii at Manoa,International Pacific Research Center, and Department of Atmospheric Sciences, School of Ocean and Earth Science and Technology
[3] National Meteorological Center of CMA,undefined
来源
Advances in Atmospheric Sciences | 2022年 / 39卷
关键词
typhoons; track; intensity; structure; theories; predictions; 台风; 路径; 强度; 结构; 理论; 预报;
D O I
暂无
中图分类号
学科分类号
摘要
To improve understanding of essential aspects that influence forecasting of tropical cyclones (TCs), the National Key Research and Development Program, Ministry of Science and Technology of the People’s Republic of China conducted a five-year project titled “Key Dynamic and Thermodynamic Processes and Prediction for the Evolution of Typhoon Intensity and Structure” (KPPT). Through this project, new understandings of TC intensification, including outer rainband-driven secondary eyewall formation and the roles of boundary layer dynamics and vertical wind shear, and improvements to TC data assimilation with integrated algorithms and adaptive localizations are achieved. To promote a breakthrough in TC intensity and structure forecasting, a new paradigm for TC evolution dynamics (i.e., the correlations, interactions, and error propagation among the triangle of TC track, intensity, and structure) is proposed; and an era of dynamic-constrained, big-data driven, and strongly coupled data assimilation at the subkilometer scale and seamless prediction is expected.
引用
收藏
页码:1789 / 1799
页数:10
相关论文
共 50 条
  • [21] Bayesian Typhoon Track Prediction Using Wind Vector Data
    Han, Minkyu
    Lee, Jaeyong
    COMMUNICATIONS FOR STATISTICAL APPLICATIONS AND METHODS, 2015, 22 (03) : 241 - 253
  • [22] Applications of the Mean Recentering Scheme to Improve Typhoon Track Prediction: A Case Study of Typhoon Nanmadol (2011)
    Chang, Chih-Chien
    Yang, Shu-Chih
    Keppenne, Christian
    JOURNAL OF THE METEOROLOGICAL SOCIETY OF JAPAN, 2014, 92 (06) : 559 - 584
  • [23] Prediction of a typhoon track using a generative adversarial network and satellite images
    Mario Rüttgers
    Sangseung Lee
    Soohwan Jeon
    Donghyun You
    Scientific Reports, 9
  • [24] Application of Direct Assimilation of ATOVS Microwave Radiances to Typhoon Track Prediction
    张华
    薛纪善
    朱国富
    庄世宇
    吴雪宝
    张风英
    Advances in Atmospheric Sciences, 2004, (02) : 283 - 290
  • [25] Application of direct assimilation of ATOVS microwave radiances to typhoon track prediction
    Hua Zhang
    Jishan Xue
    Guofu Zhu
    Shiyu Zhuang
    Xuebao Wu
    Fengying Zhang
    Advances in Atmospheric Sciences, 2004, 21 : 283 - 290
  • [26] Application of direct assimilation of ATOVS microwave radiances to typhoon track prediction
    Zhang, H
    Xue, JS
    Zhu, GF
    Zhuang, SY
    Wu, XB
    Zhang, FY
    ADVANCES IN ATMOSPHERIC SCIENCES, 2004, 21 (02) : 283 - 290
  • [27] Skillful Seasonal Prediction of Typhoon Track Density Using Deep Learning
    Feng, Zhihao
    Lv, Shuo
    Sun, Yuan
    Feng, Xiangbo
    Zhai, Panmao
    Lin, Yanluan
    Shen, Yixuan
    Zhong, Wei
    REMOTE SENSING, 2023, 15 (07)
  • [28] Distributed Typhoon Track Prediction Based on Complex Features and Multitask Learning
    Sun, Yongjiao
    Song, Yaning
    Qiao, Baiyou
    Li, Boyang
    COMPLEXITY, 2021, 2021
  • [29] Prediction of a typhoon track using a generative adversarial network and satellite images
    Ruttgers, Mario
    Lee, Sangseung
    Jeon, Soohwan
    You, Donghyun
    SCIENTIFIC REPORTS, 2019, 9 (1)
  • [30] A Nonlinear Artificial Intelligence Ensemble Prediction Model for Typhoon Intensity
    Jin, Long
    Yao, Cai
    Huang, Xiao-Yan
    MONTHLY WEATHER REVIEW, 2008, 136 (12) : 4541 - 4554