English  |  正體中文  |  简体中文  |  Items with full text/Total items : 65231/98744 (66%)
Visitors : 31980109      Online Users : 2015
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/129208


    Title: Monitoring Global Tropical Cyclone Activities on Subseasonal Timescale Using the CWB TC Tracking System
    Authors: Tsai, Hsiao-Chung;Lo, Tzu-Ting;Chen, Meng-Shih;Chen, Yun-Jing;Kuo, Jui-Ling;Hsu, Han-Yu
    Keywords: tropical cyclone;subseasonal forecast;global ensemble model
    Date: 2023-07-03
    Issue Date: 2026-04-20 12:05:23 (UTC+8)
    Abstract: A real-time tropical cyclone (TC) activity monitoring system has been developed at Central Weather Bureau (CWB) to objectively detect TCs in the 16-day NCEP GEFS (Global Ensemble Forecast System) since 2008. This system has been upgraded in 2020 by extending the forecast lead-time to four weeks. The new system, CWB TC Tracker 2.0, has integrated the forecasts from multiple global ensemble models. In addition to the NCEP GEFSv12, the real-time forecasts from the 46-day ECMWF ensemble (ENS), NCEP Climate Forecast System (CFSv2), and the CWB 1-tier climate forecast model (CWB1T1) are included. The forecasters from multiple forecast agencies are jointly using the CWB TC Tracker 2.0 as their TC forecasting tool in weeks 1-4.
    The development of the CWB TC Tracker 2.0 will be introduced. The weeks 1-4 TC forecast skills in the western North Pacific are also evaluated using the ENS and the GEFSv12. As shown in the preliminary verifications using the 20-year reforecasts, promising forecast skills can be found in both ensemble models, especially in the week-1 and week-2 forecasts. The impacts of large-scale environments on TC activity forecasts are further investigated (i.e., summer monsoon, MJO, and ENSO). A spatial-temporal ensemble track clustering algorithm (Tsai et al. 2019) is implemented to group similar ensemble vortex tracks for the track verifications and the false alarm detections. More details about the subseasonal TC forecast applications and verifications using the CWB TC Tracker 2.0 will be presented in the meeting.
    Appears in Collections:[水資源及環境工程學系暨研究所] 會議論文

    Files in This Item:

    There are no files associated with this item.

    All items in 機構典藏 are protected by copyright, with all rights reserved.


    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - Feedback