在颱風資料同化預報議題中，觀測資料除了本身的品質之外，其位置亦是對於能
否獲得有效分析修正量的重要因素之一。本研究透過一系列觀測系統模擬實驗(OSSE)
模擬2008 年颱風辛樂克，並使用Local ensemble transform Kalman filter (LETKF)，
Weather Research and Forecasting (WRF) model 及系集預報敏感度工具來探討對於颱風
路徑及結構的影響。本研究利用真實場建立出五組不同位置之探空資料，分別包含海
洋及陸地(ALL)、陸地(LAND)、海洋(OCEAN)、陸地加飛機穿越(LAND_PF)，海陸加
飛機穿越(ALL_PF)。同化預報實驗結果顯示，在海洋上有觀測的實驗組可成功掌握改
善颱風北側及東側高度場因此其系集平均路徑都較與真實場較接近。而含有穿越颱風
之觀測資訊的實驗則是能夠使得颱風的環流結構更加準確，但若僅使用飛機穿越資料
則仍會因對環境場掌握度不佳而無法提高預報路徑準確度。
此外，本研究使用Kalnay et al.(2012)提出之系集預報敏感度計算觀測影響，並以
ALL_PF 實驗結果討論同化哪些位置的觀測有助於減少預報誤差，並進一步以系集路
徑預報誤差來印證此方法之結果是否合理。結果顯示，大部分在颱風環流範圍以外的
海洋觀測在24hr 預報中能夠發揮其最大效益，其修正量亦多位於有效修正區(颱風北側
及東側)。因此透過此敏感度工具可確認同化這個區域的觀測能夠有效改善路徑預報。
而穿越中心的飛機投落送觀測則是在短期預報中就能提供正面貢獻，尤其是靠近颱風
中心點的幾個觀測。
本研究另外使用兩組敏感度測試實驗亦驗證外圍環境場的掌握度對於路徑預報的
影響，其結果與利用系集敏感度工具評估而得的觀測影響相呼應。

For typhoon assimilation and prediction, the quality of observations and its location
plays an important role in the problem of acquiring useful analysis increment. To discuss the
impact of observation location on typhoon track and structure, a series of OSSEs were carried
out with the Weather Research and Forecasting (WRF) Local ensemble transform Kalman
filter (LETKF) system and the ensemble based forecast sensitivity method is used to estimate
the observation impact. In this study, five different sets of observation locations were
constructed based on the natural run, including ALL (on ocean and land), LAND (on land),
OCEAN (on ocean), LAND_PF (on land and dropsonde of penetrated flight) and ALL_PF (on
ocean and land and dropsonde of penetrated flight). The experiment results show that the
ensemble mean track forecasts are closer to the natural run when there are observations over
ocean. Mainly, the effective corrections for improving the track prediction are over the
northern and eastern side of typhoon. In this case, we also found that assimilating the
penetrating flight dropsonde is helpful for establishing reliable typhoon circulation, but is not
useful enough for improving the overall track prediction, due to the lack of environment
information.
Based on the results of ALL_PF, we use the ensemble-based forecast sensitivity to
observation (EFSO) method (Kalnay et al., 2012) to estimate the observation impact, and
investigate which location of observations can significantly reduce the forecast error. The
result indicates that most of observations outside the typhoon circulation and over the ocean
region can bring out best benefit within the 24hr forecast. Results also confirm that
observations with positive corrections are mainly located near north and east region of
typhoon, as we expected that assimilating these observations can improve the track forecast.
In addition, assimilating dropsondes provides positive contribution to the short forecast,
iii
especially with the observations in the typhoon inner core.
In addition, two sensitivity experiments were carried out to test the effectiveness of the
environment observations on improving the track forecast. Results are able to echoed the
observation impact calculated by EFSO.

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