English  |  正體中文  |  简体中文  |  全文筆數/總筆數 : 80990/80990 (100%)
造訪人次 : 41636368      線上人數 : 1111
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
搜尋範圍 查詢小技巧:
  • 您可在西文檢索詞彙前後加上"雙引號",以獲取較精準的檢索結果
  • 若欲以作者姓名搜尋,建議至進階搜尋限定作者欄位,可獲得較完整資料
  • 進階搜尋


    請使用永久網址來引用或連結此文件: http://ir.lib.ncu.edu.tw/handle/987654321/88055


    題名: 利用GSI三維混成同化探討GNSS掩星觀測資料對全球模式FV3颱風模擬的影響
    作者: 林辰洋;Lin, Chen-Yang
    貢獻者: 大氣科學學系
    關鍵詞: 颱風;資料同化;偏折角
    日期: 2021-12-21
    上傳時間: 2022-07-13 16:31:55 (UTC+8)
    出版者: 國立中央大學
    摘要: 隨著福爾摩沙衛星七號於2019年6月25日發射升空,透過接收全球定位衛星發射通過大氣層與電離層產生的折射訊號,並利用掩星觀測(Radio Occultation, RO)技術,計算訊號的偏折程度並反演成大氣層與電離層的狀態,其中訊號的偏折程度又稱為偏折角(bending angle),利用資料同化系統將得到之偏折角進行資料同化,增加模式的預報能力,並改善廣大洋面上缺乏觀測資料的問題。本篇研究使用臺灣中央氣象局與美國國家環境預報中心(National Centers for Environment Prediction, NCEP)合作,進一步改善成適合台灣地區預報之CWB FV3GFS,其資料同化系統為NCEP所發展之GSI 3DEnVar,目前使用的版本為尚未正式上線作業的版本。本篇研究使用CWB FV3GFS,並利用資料同化系統於颱風生成前14天開始進行10天未包含福衛七號資料之同化循環,並於颱風生成前四天,再分別進行有無同化福衛七號偏折角之實驗,並於各個00Z及12Z進行五天預報,本篇研究針對西北太平洋三個強度較強且路徑未受地形影響之颱風,哈吉貝(2019)、梅莎(2020)及海神(2020)進行模擬並分析。
    研究結果顯示,兩實驗於此三個颱風路徑模擬結果與日本氣象廳最佳路徑相當接近,整體的路徑誤差都不大,在誤差統計中,有使用福衛七號RO資料之實驗WB分別在梅莎的路徑、海神的最大風速及哈吉貝與梅莎的中心最低氣壓之誤差低於未使用福衛七號RO資料之實驗NB。在三個颱風的平均誤差中,實驗WB於預報時間前24小時最大風速及中心最低氣壓之誤差也小於實驗NB,在誤差分布圖中,實驗WB於預報時間前48小時其最大風速及中心最低氣壓之誤差大多數小於實驗NB。亦選出實驗WB路徑改善最明顯之個案:哈吉貝1009_00Z及梅莎0830_12Z,其中梅莎0830_12Z之強度也有獲得改善,兩個案之分析場與NCEP分析場相當接近,但颱風中心之風速及濕度都有較弱的情況,其中實驗WB之強度較強且結構與NCEP分析場較為相似,而在個案梅莎0830_12Z之預報中實驗WB強度較強於實驗NB且更接近最佳路徑,研究結果顯示,實驗WB之颱風風速較強且發展較高,中心比濕也較大,且在颱風之眼牆區域比濕較大,使得颱風更有利於發展。在兩個個案之渦度收支分析中,皆發現其主要受到水平平流項主導,雖然垂直平流項、輻合輻散項及傾斜項帶來的貢獻較少,但提供的向量皆垂直於水平平流項,因此對於方向上的影響非常大,也使得兩實驗的路徑上產生差異。
    ;The FORMOSAT-7 satellites, which were launched into space on June 25, 2019, provide higher resolution and quality radio occultation data than FORMOSAT-3. The radio signals are transmitted from the satellites of Global Navigation Satellite System (GNSS) and received by low earth orbit (LEO) satellites. The vertical profiles of bending angle are derived by measuring the refraction of the signals. Radio occultation measurements are helpful for numerical weather prediction (NWP), which can improve the analysis and thus further improve the typhoon track and intensity prediction.
    In this study, the global NWP system at CWB (CWB FV3GFS), which utilizes the global model FV3GFS and the GSI 3DEnVar data assimilation system, is used to assimilate observation data. The impacts of bending angle data assimilation on forecasts of typhoons Hagibis, Maysak and Haishen are investigated. Both experiments that assimilate and don’t assimilate bending angle data (denoted by WB and NB, respectively) are performed and they are conducted for 120-h forecast at every 00Z and 12Z. The experiments are initialized at 14 days before the observed cyclogenesis time of each typhoon.
    The model results show that the forecasted tracks of all WB and NB experiments are close to the best tracks from JMA, and the track predictions for Maysak and Haishen are significantly improved in their later forecasts. Further comparisons on the forecasted tracks show that the track errors for WB are slightly larger than NB. The track errors for WB are not improved for all typhoons, however the intensity errors are significantly improved in a statistical manner, particularly for the pressure errors. The experiments that their forecasted tracks are closer to the best track are chosen for detailed analysis. The WB analyses after data assimilation for Maysak and Hagibis are closer to the NCEP GDAS/FNL data compared to NB and thus improve the typhoon intensity and structure. For Maysak, stronger wind near the typhoon center at the initial time is produced in WB than NB and is accompanied by moister updrafts, which is favorable for the development of the typhoon.
    顯示於類別:[大氣物理研究所 ] 博碩士論文

    文件中的檔案:

    檔案 描述 大小格式瀏覽次數
    index.html0KbHTML79檢視/開啟


    在NCUIR中所有的資料項目都受到原著作權保護.

    社群 sharing

    ::: Copyright National Central University. | 國立中央大學圖書館版權所有 | 收藏本站 | 設為首頁 | 最佳瀏覽畫面: 1024*768 | 建站日期:8-24-2009 :::
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - 隱私權政策聲明