Advanced Search
Impact Factor: 5.8

Volume 20 Issue 3

May  2003

Article Contents
Article >  ADVANCES IN ATMOSPHERIC SCIENCES  > 2003 >  20(3): 379-384

Prediction of Typhoon Tracks Using Dynamic Linear Models

  • 1.

    Pusan National University, Pusan, 609-735, Korea,Kongju National University, Konju, 314-701, Korea,Meteorological Research Institute/KMA, Seoul, 156-010, Korea


doi: 10.1007/BF02690796

  • This paper presents a study on the statistical forecasts of typhoon tracks. Numerical models havetheir own systematic errors, like a bias. In order to improve the accuracy of track forecasting, a statisticalmodel called DLM (dynamic linear model) is applied to remove the systematic error. In the analysis oftyphoons occurring over the western North Pacific in 1997 and 2000, DLM is useful as an adaptive modelfor the prediction of typhoon tracks.
  • [1] Keon-Tae SOHN, Deuk-Kyun RHA, Young-Kyung SEO, 2003: The 3-Hour-Interval Prediction of Ground-Level Temperature in South Korea Using Dynamic Linear Models, ADVANCES IN ATMOSPHERIC SCIENCES, 20, 575-582.  doi: 10.1007/BF02915500
    [2] XUE Haile, SHEN Xueshun, CHOU Jifan, 2015: An Online Model Correction Method Based on an Inverse Problem: Part II——Systematic Model Error Correction, ADVANCES IN ATMOSPHERIC SCIENCES, 32, 1493-1503.  doi: 10.1007/s00376-015-4262-0
    [3] Runhua YANG, Jing GUO, Lars Peter RIISH?JGAARD, 2006: Application of an Error Statistics Estimation Method to the PSAS Forecast Error Covariance Model, ADVANCES IN ATMOSPHERIC SCIENCES, 23, 33-44.  doi: 10.1007/s00376-006-0004-7
    [4] Daosheng XU, Jeremy Cheuk-Hin LEUNG, Banglin ZHANG, 2023: A Time Neighborhood Method for the Verification of Landfalling Typhoon Track Forecast, ADVANCES IN ATMOSPHERIC SCIENCES, 40, 273-284.  doi: 10.1007/s00376-022-1398-6
    [5] Isidora JANKOV, Scott GREGORY, Sai RAVELA, Zoltan TOTH, Malaquías PEÑA, 2021: Partition of Forecast Error into Positional and Structural Components, ADVANCES IN ATMOSPHERIC SCIENCES, 38, 1012-1019.  doi: 10.1007/s00376-021-0251-7
    [6] Jian YUE, Zhiyong MENG, Cheng-Ku YU, Lin-Wen CHENG, 2017: Impact of Coastal Radar Observability on the Forecast of the Track and Rainfall of Typhoon Morakot (2009) Using WRF-based Ensemble Kalman Filter Data Assimilation, ADVANCES IN ATMOSPHERIC SCIENCES, 34, 66-78.  doi: 10.1007/s00376-016-6028-8
    [7] Xiaogu ZHENG, 2009: An Adaptive Estimation of Forecast Error Covariance Parameters for Kalman Filtering Data Assimilation, ADVANCES IN ATMOSPHERIC SCIENCES, 26, 154-160.  doi: 10.1007/s00376-009-0154-5
    [8] Jingjing LIANG, Zongliang YANG, Peirong LIN, 2019: Systematic Hydrological Evaluation of the Noah-MP Land Surface Model over China, ADVANCES IN ATMOSPHERIC SCIENCES, 36, 1171-1187.  doi: 10.1007/s00376-019-9016-y
    [9] Zhe-Min TAN, Lili LEI, Yuqing WANG, Yinglong XU, Yi ZHANG, 2022: Typhoon Track, Intensity, and Structure: From Theory to Prediction, ADVANCES IN ATMOSPHERIC SCIENCES, 39, 1789-1799.  doi: 10.1007/s00376-022-2212-1
    [10] XUE Hai-Le, SHEN Xue-Shun, CHOU Ji-Fan, 2013: A Forecast Error Correction Method in Numerical Weather Prediction by Using Recent Multiple-time Evolution Data, ADVANCES IN ATMOSPHERIC SCIENCES, 30, 1249-1259.  doi: 10.1007/s00376-013-2274-1
    [11] ZHENG Xiaogu, WU Guocan, ZHANG Shupeng, LIANG Xiao, DAI Yongjiu, LI Yong, , 2013: Using Analysis State to Construct a Forecast Error Covariance Matrix in Ensemble Kalman Filter Assimilation, ADVANCES IN ATMOSPHERIC SCIENCES, 30, 1303-1312.  doi: 10.1007/s00376-012-2133-5
    [12] Bohua Huang, James L. Kinter III, Paul S. Schopf, 2002: Ocean Data Assimilation Using Intermittent Analyses and Continuous Model Error Correction, ADVANCES IN ATMOSPHERIC SCIENCES, 19, 965-992.  doi: 10.1007/s00376-002-0059-z
    [13] Chen Jiabin, Ji Liren, Wu Wanli, 1987: DESIGN AND TEST OF AN IMPROVED SCHEME FOR GLOBAL SPECTRAL MODEL WITH REDUCED TRUNCATION ERROR, ADVANCES IN ATMOSPHERIC SCIENCES, 4, 156-168.  doi: 10.1007/BF02677062
    [14] ZHANG Hua, XUE Jishan, ZHU Guofu, ZHUANG Shiyu, WU Xuebao, ZHANG Fengying, 2004: Application of Direct Assimilation of ATOVS Microwave Radiances to Typhoon Track Prediction, ADVANCES IN ATMOSPHERIC SCIENCES, 21, 283-290.  doi: 10.1007/BF02915715
    [15] XUE Haile, SHEN Xueshun, CHOU Jifan, 2015: An Online Model Correction Method Based on an Inverse Problem: Part I——Model Error Estimation by Iteration, ADVANCES IN ATMOSPHERIC SCIENCES, 32, 1329-1340.  doi: 10.1007/s00376-015-4261-1
    [16] DUAN Wansuo, ZHANG Rui, 2010: Is Model Parameter Error Related to a Significant Spring Predictability Barrier for El Nino events? Results from a Theoretical Model, ADVANCES IN ATMOSPHERIC SCIENCES, 27, 1003-1013.  doi: 10.1007/s00376-009-9166-4
    [17] Ling-Jiang TAO, Rong-Hua ZHANG, Chuan GAO, 2017: Initial Error-induced Optimal Perturbations in ENSO Predictions, as Derived from an Intermediate Coupled Model, ADVANCES IN ATMOSPHERIC SCIENCES, 34, 791-803.  doi: 10.1007/s00376-017-6266-4
    [18] Xia LIU, Qiang WANG, Mu MU, 2018: Optimal Initial Error Growth in the Prediction of the Kuroshio Large Meander Based on a High-resolution Regional Ocean Model, ADVANCES IN ATMOSPHERIC SCIENCES, 35, 1362-1371.  doi: 10.1007/s00376-018-8003-z
    [19] P. L. S. Rao, 2000: The Influence of Systematic Errors on the Asian Summer Monsoon Circulation, ADVANCES IN ATMOSPHERIC SCIENCES, 17, 576-586.  doi: 10.1007/s00376-000-0021-x
    [20] Dongmei XU, Feifei SHEN, Jinzhong MIN, Aiqing SHU, 2021: Assimilation of GPM Microwave Imager Radiance for Track Prediction of Typhoon Cases with the WRF Hybrid En3DVAR System, ADVANCES IN ATMOSPHERIC SCIENCES, 38, 983-993.  doi: 10.1007/s00376-021-0252-6
PDF

Get Citation+

shu
Export:  

Share Article

Article Metrics

Article Views: 1549 Times

PDF downloads: 1282 Times

Cited by: Times
  • 加载中

    • Manuscript History

    Manuscript received: 10 May 2003
    Manuscript revised: 10 May 2003
    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

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Prediction of Typhoon Tracks Using Dynamic Linear Models

    • 1. Pusan National University, Pusan, 609-735, Korea,Kongju National University, Konju, 314-701, Korea,Meteorological Research Institute/KMA, Seoul, 156-010, Korea
    • Manuscript received: 2003-05-10
    • Manuscript revised: 2003-05-10

    Abstract: This paper presents a study on the statistical forecasts of typhoon tracks. Numerical models havetheir own systematic errors, like a bias. In order to improve the accuracy of track forecasting, a statisticalmodel called DLM (dynamic linear model) is applied to remove the systematic error. In the analysis oftyphoons occurring over the western North Pacific in 1997 and 2000, DLM is useful as an adaptive modelfor the prediction of typhoon tracks.

      HTML

    Catalog

      Publish with AAS

      Contact us

      Links

      Copyright © 2018-2028 ADVANCES IN ATMOSPHERIC SCIENCES 京ICP备14024088号-7

      Supported by: Beijing Renhe Information Technology Co. Ltd  support: info@rhhz.net  

      /

      DownLoad:  Full-Size Img  PowerPoint
      Return
      Return