系集定量降水預報方法之研究

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系集定量降水預報方法之研究

QPF Verification Study of the Ensemble Forecast System

葉世瑄 , Masters　　Advisor：林沛練　　

繁體中文

系集預報系統；定量降水預報；機率擬和平均PM ；修改之PM法PMmod. ；預兆得分；公正預兆得分； EPS(Ensemble Prediction System) ； QPF(Quantitative Precipitation Forecast) ； PM(Probability-matched mean) ； PMmod.(PM modify) ； TS(Threat Score) ； ETS(Equitable threat score)

Abstract │ Reference (78) │ Altmetrics

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From ensemble members results to get useful information is an important issue for ensemble forecast system. Since rainfall distribution is not continuous, and too localized such as especially extreme heavy rainfall occur, the averaging process usually "smears" the rain rates so that the maximum rainfall is reduced and area of light rain is artificially enlarged. PM(probability-matched ensemble mean) is a new ensemble product, it has the similar spatial pattern as the simple ensemble mean, and could catch correct frequency distribution of rain rates and QPFs. Especially, we will propose a modify PM( PMmod.). It is similar as PM could display similar spatial pattern as the simple ensemble mean, its performance depends on the actual rainfall extremes should be included in the all members QPFs of a good Ensemble Prediction System (EPS). Therefore it is suitable to average all the rain rates frequency distribution from all the individual members. 
  From the 20120610-20120612 case (Case1), Typhoon Soulik(2013) case (Case2) and 201206 monthly experiment to analyze the characteristic and skill of the ensemble mean, PM and PMmod., we can find that they can modify the QPF, especially PM and PMmod. can make the TS progress rate up to 11.5%, ETS progress rate even up to 50% in the 50 mm(12 accumulated precipitation). But in the light rain, the ensemble mean is still the best. Nerveless, in Case1, the ensemble members don’t catch the correct speed and strength of the Meiyu front, the rainfall for ensemble member distribution is generally underestimated, that is a reason why PM can’t forecast the heavy rain correctly. In Case2, it has good performance for PM and PMmod results from the previous 12 hours rainfall forecast of typhoon Soulik, however in the later 12 hours rainfall forecast of the Soulik, the QPF is generally overestimate in all three statistical methods, because the simulated storm speed is slower than actual. Especiall, the spatial pattern of the ensemble mean, in both PM and PMmod concentrated in the mountains and result in bias. From this study, we can find that derive the correct distribution of rainfall result from the ensemble forecast system(WEPS) over the complex terrain in Taiwan has some progress but still need be investigated in the coming days.
  If all ensemble members of forecast model can’t catch the correct event signal, no matter what kind post processes method as simple ensemble mean, PM or PMmod could only modify the forecast results a little. Nevertheless, all the products like mean, previous study pointed out several include a resampling of the ensemble realizations, a rainfall pattern adjustment, and a bias-correction, could modify PM scheme to substantially reduce or eliminate the intrinsic model rainfall bias and to provide better QPFs. Expectations of the future, pattern adjustment and bias-correction both PM or PMmod processes to improve QPFs of ensemble forecast.

Reference ( 78 ) 〈TOP〉

李志昕、洪景山，2011：區域系集預報系統研究：物理參數化擾動。大氣科學，
連結：
胡志文、馮欽賜、汪鳳如、陳建河、鄭明典，2002：中央氣象局全球模式之氣候特　　徵：東亞夏季季風。大氣科學，30，99-116。
連結：
曾仁佑、林沛練、馬佳齡、童裕翔，2004：東亞地區區域氣候之可預報度與回歸預　　報研究。全球變遷通訊雜誌，41，25-34。
連結：
簡芳菁、柳懿秦、周仲島、林沛練、洪景山和蕭玲鳳，2005：2003 年梅雨季MM5 　　系集降水預報。大氣科學，33，255 - 275。
連結：
27th session of the Working Group on Numerical 　　
連結：

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