本研究使用MM5（The Fifth-Generation PSU∕NCAR Mesoscale Model ）
模式第3.7 版模擬2009 年8 月莫拉克颱風個案，探討台灣西南部地區極端降
雨之原因。控制實驗模擬的72 小時累積降雨量在台灣中央山脈南部約
2200mm，接近觀測但降雨分布稍微偏南。利用四維變分同化方法(4DVAR)，
同化虛擬渦旋，加強颱風初始場結構。經過同化虛擬渦旋之結果顯示，不管
是颱風強度、最大風速、路徑方面皆得到明顯改善，而降雨分布從原本
台灣南部山區，移至台灣中部地區。為了進一步了解極端降雨機制，也分別
對西南季風之水平風場增量、移除柯尼颱風以及降低西南季風之水氣含量做
敏感度測試。
由西南季風增量實驗得知，西南季風增量對台灣影響時間主要在8
月8日，而西南季風強度對降雨量影響並不顯著，但對降雨位置有明顯
差異，增強西南季風實驗降雨量分布在台灣中部山區；反之，減弱西南
季風實驗降雨量仍維持在台灣南部地區。另一方面，當莫拉克颱風登陸台
灣後，移動速度減慢，而台灣西南方位於海南島附近的柯尼颱風，正逐漸減
弱為熱帶性低氣壓，所以移除海南島附近的柯尼颱風當作初始場，模擬結果
發現台灣西南方的平均水平風速明顯減少，且台灣西南部山區8月8日最大累
積降雨量減少約三分之一，表示柯尼颱風引導暖濕的西南氣流在台灣西南部
與莫拉克外圍環流輻合，進而導致台灣地區極端降雨。最後，降低西南季風
區域之水氣含量敏感度測試，當台灣西南方大尺度的水氣含量減少後，透過
水氣場隨時間變化可知，西南區域水氣傳送至台灣西南部和莫拉克颱風外圍
環流，進而導致減少台灣西南部地區之累積降雨，由此顯示西南氣流區域之
水氣含量亦是造成莫拉克颱風劇烈降水的原因之一。

This study used the PSU/NCAR MM5 Model to simulate Typhoon Morakot
(2009), and investigated the mechanisms of the torrential rainfall in southwest
Taiwan and the role of the southwest monsoon flow. The results indicated that the
model is able to capture the observed 72-h accumulated rainfall over 2000 mm
after applying bogus vortex data assimilation (BDA) based on 4DVAR that helps
to improve the initial intensity of the typhoon. The simulated track near and after
landfall is close to the best track, resulting in a good agreement of accumulated
rainfall with the observations.
In the sensitivity experiments for monsoon intensity, the 72-h accumulated
rainfall shows only some differences but have significant changes in rainfall
patterns with respect to the intensity of southwest monsoon. For stronger monsoon,
the 72-h accumulated rainfall tends to be enhanced in central Taiwan, while
weaker monsoon induces more rainfall in south Taiwan. In the experiment with the
initial field where Goni vortex is deactivated by BDA, rainfall maximum is
reduced by about one third on 8 August in southwest Taiwan. When the Goni
circulation and strong moisture-laden southwesterly flow converge to the
southwest of Taiwan, it causes extreme rainfall in southwest Taiwan. On the other
hand, as the relative humidity of southwest flow is reduced, the rainfall intensity
also decreases. It appears that the water vapor transmission from southwest flow is
also an important factor for heavy rainfall in this event. Consequently, southwest
monsoon intensity, Goni Typhoon, and southwesterly moisture are integrated to
produce the tremendous rainfall in Taiwan.

吳俊澤，2007：利用MM5 4DVAR模式同化掩星折射率資料及虛擬渦旋探討颱風
樹植模擬之影響。國立中央大學大氣物理研究所，碩士論文，70頁。
麥翠珊，2008：利用MM5 4DVAR同化虛擬渦旋探討其對WRF模式預報颱風之影
響。國立中央大學大氣物理研究所，碩士論文，103頁。
蔡金成，2009：衛星資料與虛擬渦旋四維變分同化對颱風數值模擬的影響。
國立中央大學大氣物理研究所，碩士論文，87頁。
李志昕，2009：西北向侵台颱風登陸前中心路徑打轉之模擬研究。國立中央
大學大氣物理研究所，碩士論文，82頁。
林欽國，2011：利用高解析度模試探討地形高度與西南氣流水氣傳送對莫拉
克(2009)颱風模擬之影響。國立中央大學大氣物理研究所，碩士論文，
76頁。
吳乙昕，2012：凡那比颱風(2010)降雨機制探討。國立中央大學大氣物理所，
碩士論文，78頁。
Chien, F.-C., Y.-C. Liu, and C.-S. Lee, 2008: Heavy rainfall and southwesterly
flow after the leaving of Typhoon Mindulle (2004) from Taiwan. J. Meteor.
Soc. Japan, 86, 17–41.
––––, and H. -C. Kuo, 2011：On the extreme rainfall of Typhoon Morakot (2009),
J. Geophys. Res., 116, D05104, doi:10.1029/2010JD015092.
Fujita, T., 1952: Pressure distribution within a typhoon. Geophys. Mag.,
23,437-451.
Guo, Y.-R., Y.-H.,Kuo, J. Dudhia, D. Parsons, and C., Rocken,
2000:Four-dimensional variational data assimilation of heterogeneous
mesoscaleobservations for a strong convective case. Mon. Wea. Rev., 128,
619-643.
Hendricks, E. A., J. R. Moskaitis, Y. Jin, R. M. Hodur, J. D. Doyle, and M. S.
Peng, 2011: Prediction and diagnosis of Typhoon Morakot (2009) using the
Naval Research ：Laboratory’s mesoscale tropical cyclone model. Terr.
Atmos. Oceanic Sci. (TAO).
Huang, C.-Y., C.-S. Wong, and T.-C. Yeh, 2011: Extreme rainfall mechanisms
exhibited by typhoon Morakot (2009). Terr. Atmos. Oceanic Sci., 22,
613-632, doi: .3319/TAO.2011.07.01.01(TM).
Jain, G. –J., and C. –C., Wu, 2008：A Numerical study of the track deflection of
super-typhoon Haitang(2005) prior to its landfall in Taiwan. Mon. Wea. Rev.,
136 598-615.
Liang, J., L. Wu, X. Ge, and C.-C. Wu, 2011: Monsoonal influence on Typhoon
Morakot 11 (2009). Part II: Numerical study. J. Atmos. Sci., 68, 2222-2235.
Neumann, C. J., 1993: Global overview. Chapter 1, Global Guide to Tropical
Cyclone Forecasting. WMO, 1.1-1.56.
Park K. amd X. Zou, 2004: Toward developing an objective 4DVAR BDA
scheme for hurricane initialization based on TPC observed parameters. Mon.
Wea. Rev., 132, 2054-2069.
Wu, C.-C., K.-H. Chou, Y. Wang and Y.-H. Kuo, 2006: Tropical cyclone
initialization and prediction based on four-dimensional variational data
assimilation. J. Atmos. Sci., 63, 2383–2395.
––––, K. K. W. Cheung, and Y.-Y. Lo, 2009:Numerical study of the rainfall event
due to the interaction of Typhoon Babs(1998) and the Northeasterly Monsoon.
Mon. Wea. Rev., 137, 2049-2064.
Wu, L., J. Liang, and C.-C. Wu, 2011: Monsoonal influence on Typhoon Morakot
(2009). Part 17 I: Observational analysis. J. Atmos. Sci., 68, 2208-2221.
Xiao, Q., X. Zou, and B. Wang, 2000: Initialization and simulation of a landing hurricane using a variational bogus data assimilation scheme. Mon. Wea. Rev.,
128, 2252-2269.
Zou, X., Y.-H. Kuo, and Y.-R. Guo, 1995: Assimilation of atmospheric radio
refractivity using a nonhydrostatic adjoint model. Mon. Wea. Rev., 123,
2229-2249.
––––, and Q. Xiao, 2000: Studies on the initialization and simulation of a mature
hurricane using a varitional bogus data assimilation scheme. J. Atmos. Sci.,
57, 836-860.