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Student Number 986201012
Author Chen-Chieh Kao(高晟傑)
Author's Email Address 986201012@cc.ncu.edu.tw
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Department Graduate Institute of Atmospheric Physics
Year 2011
Semester 1
Degree Master
Type of Document Master's Thesis
Language zh-TW.Big5 Chinese
Title Impact of Idealized GPS Radio Occultation Refractivity in predicting a Heavy Rainfall Event with the WRF-Local Ensemble Transform Kalman Filter System
Date of Defense 2011-12-23
Page Count 84
Keyword
  • data assimilation
  • EnKF
  • NWP
  • Abstract   In this study, we perform OSSE experiment to evaluate the impact of next-generation satellites GPS radio occultation for regional data assimilation and prediction, particularly focusing on an event with heavy rainfall in Taiwan. The evaluation is based on the accuracy of the analyses derived from the WRF-LETKF system and the following prediction.
      For the OSSE experiment, the natural run is a 3-day simulation with a rainfall distribution similar to a real case (SoWMEX 2008 IOP-8) from the strong convection of the Mei-Yu front. There are three sets of experiments, including the sensitivity for observation density and observation accuracy, and the impact of using a multivariate covariance. Results show that the ensemble forecast can well capture the rainfall distribution similar to truth after spin-up time of LETKF. With the RO refractivity (REF), the wind and water vapor forecasts can be improved with a leadtime from 6 to 24 hours. With more accurate REFs, the advantage of REF data is clearly identified with even a moderate observation density with a resolution of 300km. However, we notice that even though the water vapor can be improved with the accurate observations, the quality of the analysis and forecast for wind and temperature is degraded because of the unbalance between variables. When restricting the impact of REF data to only the water vapor and temperature fields, the wind analysis becomes more accurate at mid to upper troposphere than the one using the full multivariate correlations. But, the effect on improving the heavy rainfall prediction is less clear.
      According to this study, the WRF-LETKF assimilation system needs 1 to 2 days to spin up the impact of the REF data. The localization of the variables for the multivariate covariance can be a useful strategy to accelerate the impact of GPS RO data.
    Table of Content 中文摘要…………………………………………………………………………  i
    英文摘要…………………………………………………………………………  ii
    誌謝………………………………………………………………………………  iii
    目錄………………………………………………………………………………  iv
    圖表說明…………………………………………………………………………  vi
    第一章、前言
      1.1  研究動機與目的…………………………………………………   1
      1.2  文獻回顧…………………………………………………………   2
    第二章、個案介紹
      2.1  真實個案(2008年6月14日~16日LST)綜觀天氣簡介…   4
      2.2  模擬個案介紹……………………………………………………   6
    第三章、模式與同化系統
      3.1  模式系統…………………………………………………………   7
      3.2  同化方法…………………………………………………………   8
      3.3  觀測與觀測算符
        3.3.1  探空………………………………………………………   9
        3.3.2  局地掩星觀測折射率……………………………………  10
    第四章、實驗設計
      4.1  實驗設計…………………………………………………………  11
    4.2  模擬個案簡介……………………………………………………  11
    4.3  同化實驗設定……………………………………………………  12
      4.4  驗證方法…………………………………………………………  13
    第五章、實驗結果與討論
      5.1  觀測數量敏感度測試……………………………………………  15
        5.1.1  折射率觀測數量對於風場、溫度與水氣的影響…………  15
        5.1.2  折射率觀測數量對於降水預報的影響……………………  15
      5.2  觀測誤差敏感度測試………………………………………………  16
        5.2.1  觀測誤差對於風場、溫度與水氣的影響…………………  16
        5.2.2  觀測誤差對於降水預報的影響……………………………  17
      5.3  多變量相關性測試………………………………………………… 18
    5.4  個案分析…………………………………………………………… 19
    第六章、總結與未來展望
      6.1  總結………………………………………………………………… 21
      6.2  未來展望…………………………………………………………… 22
    參考文獻…………………………………………………………………………  23
    附錄………………………………………………………………………………  27
    附表與附圖………………………………………………………………………  31
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    Advisor
  • Shu-Chih Yang(楊舒芝)
  • Files
  • 986201012.pdf
  • approve immediately
    Date of Submission 2012-01-31

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