結合衛星反演資料與WRF模式探討梅雨鋒面水氣傳送關聯性之個案研究

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題名:	結合衛星反演資料與WRF模式探討梅雨鋒面水氣傳送關聯性之個案研究
作者:	林敬傑;Lin,Ching-chieh
貢獻者:	大氣科學學系
關鍵詞:	高光譜紅外線垂直探測儀;先進微波垂直探測儀;極端降雨;梅雨鋒面;AIRS;Mei-Yu frontal;Extreme Precipitaion;AMSU
日期:	2015-11-26
上傳時間:	2016-01-05 16:43:14 (UTC+8)
出版者:	國立中央大學
摘要:	每年五月中到六月中為臺灣地區的梅雨季節，為全島帶來除了颱風以外的另一重要雨季。鋒面系統若伴隨劇烈降雨現象，常導致瞬間洪水、雷擊、冰雹等現象，易造成財產及生命的損失。衛星資料具有長時間穩定及廣範圍地面及空中觀測，彌補過去資料不易取得或缺乏地區。前人多個研究同化反演產品於颱風個案中結果都有改善。於此篇研究主要想了解三個問題:衛星反演資料於數值天氣預報(NWP)系統模擬台灣梅雨季節鋒面系統改善程度，及運用最佳評估後之分析場來探討鋒面系統影響降雨行為之水氣來源區域和水氣來源高度敏感度。高光譜紅外線垂直探測儀(Atmospheric Infrared Sounder, AIRS)為新一代觀測儀器，搭配先進微波垂直探測儀(Advanced Microwave Sounding Unit, AMSU)後，可提供高精確三維大氣熱力結構反演產品。以2012年6月12日的梅雨鋒面過境案例實驗，同化反演之溫、溼度產品與其他資料加入WRF中改善初始場。經均方根誤差(Root Mean Square Error, RMSE)及預報影響(Forecast Impact, FI)分數評比，AIRS表現最匹配ECMWF再分析資料，與中央氣象局(CWB)雷達觀測比對也最為相近，證實正確使用反演產品有助益於梅雨鋒面預報。最佳組別AIRS進一步作為探討水氣敏感實驗之控制組，以台灣中心分成四區，高度上選取四個特性高度調整共16組組別較ECMWF偏濕的地區進行85%水氣量調整。經預報偏離得分(Bias Score, BS)及預兆得分(Threat Score, TS)分析十組不同累積雨量，得到西南區域改變較其他三區明顯且在24小時內就能有感受，其中925百帕高度實驗組影響最顯著。由敏感性實驗結果得知特地區域或高度水氣傳送在預估梅雨劇烈天氣中是相當重要的，相信衛星觀測水氣傳輸敏感位置是能有助於提防的。 ;Mei-Yu systems arrive Taiwan region one after another from mid-May through mid-June bringing secondary precipitation in a year. Frontal and associated MCS may contribute extreme precipitation, hail, lightening, and sudden flooding to cause life and wealth loss in worst situation. Satellite data have many advantages such as stable and broad observation on ground and aerial atmosphere over long period that scarce data region has been recovered. Researchers concluded that assimilation with retrieval product in typhoon case had skills improved. There are three questions raised in this study: How satellite retrieved data used in NWP system for simulation of Mei-Yu season frontal system will be improved. And which region or height is the main source of water vapor derived to frontal rainfall. Combining AIRS, new generation sounder, and AMSU data would make a precise three dimensions thermal structure of atmosphere. WRF model was adopted to simulate one extreme precipitation case during Mei-Yu case on June 12, 2012. Retrieval data such as temperature and moisture and other dataset assimilated into the model for a more reasonable initial field. After analyzed RMSE and FI score, AIRS consisted with ECMWF reanalysis dataset and CWB radar observation than others. This conclusion showed positive benefit for Mei-Yu frontal forecast when retrieval data was appropriately used. AIRS, optimal performance member, was selected as control run for water vapor sensitivity experiment. Model area where wetter than ECMWF had 85% water vapor amount adjustment. Domain that centered on Taiwan central was sliced into 16 member which compose of four different regions and heights. Analyzing BS and TS score with 10 precipitation intensity intervals showed that SW had distinct change when compared to other three groups in first 24 hours. Especially, SW_925 had obvious shift. However, a series of adjustment experiment could be concluded that satellite observation on water vapor sensitive area are useful and important to alert severe weather condition such as Mei-Yu system.
顯示於類別:	[大氣物理研究所 ] 博碩士論文

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