基于概率密度匹配方法的WRF模式陣風風速誤差訂正
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安徽省氣象局預報員專項項目(kY201713)和國家自然科學基金項目(41705029)聯合資助


Error Correction of WRF Model Gust Speed Based on Probability Density Function Matching Method
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    摘要:

    為提高數值模式對陣風風速預報能力,采用概率密度匹配方法(Probability Density Function Matching Method,簡稱PDF方法)對WRF模式地面極大風速預報數據開展誤差訂正。結果表明:①基于PDF方法訂正后的陣風預報效果明顯優于WRF預報結果,當實況極大風力≤5級時,兩種預報結果均與實況較為一致;當實況極大風力≥6級時,WRF預報相比實況明顯偏小,而PDF方法訂正結果則與實況較為接近;②對比不同地形條件下兩種預報結果發現,在實況風力整體偏弱的平原地區,WRF預報和PDF訂正結果對極大風的預報效果均較好;在風力偏強的山區和沿江河谷地區,PDF訂正結果的預報效果相比WRF預報則有明顯提升;③對2017年安徽省81個國家站逐日極大風速的預報效果檢驗發現:預報誤差和過去五年整體擬合誤差基本相當,說明基于2012—2016年歷史數據建立的概率密度分布函數可以代表安徽各站多年的實況和WRF預報極大風速的聯合分布特征,利用PDF方法進行逐日極大風速預報具有一定的可靠性。

    Abstract:

    In order to improve the forecasting ability of WRF mode against the gust wind speed, the probability density function matching method (PDF) is used to correct the wind speed errors of wind speed forecasting data from WRF model. The results show that: (1) The gust wind force forecasting based on the PDF method is significantly better than the WRF output. When the observed daily maximum wind speed force ≤ level 5, two forecasting results are both consistent with the observation. When observed daily maximum wind speed force ≥ level 6, comparing with the observed and the wind speed forecasting based on the PDF method, the output from WRF is weaker. (2) By comparing two forecasting results above different topographic conditions, it is found that the effects of the WRF and PDF methods on gust wind in the plain area where the observed wind force is weak are both good. However, in the mountain and valley areas where the observed wind force is strong, the effect of WRF forecast is obviously poor but the effect of the PDF method is improved compared with WRF. (3) By testing forecasting effect on the daily maximum wind speed of 81 national stations in Anhui Province in 2017, it is showed that the forecast error is basically the same as that of the past 5 years, which shows that the probability density distribution function based on the historical data from 2012 to 2016 can represent the joint distribution characteristics of the observed and WRF simulated maximum wind speed from 81 national stations in Anhui Province for many years. So it is reliable by using the PDF method to forecast daily maximum wind speed.

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錢磊,邱學興,鄭淋淋.基于概率密度匹配方法的WRF模式陣風風速誤差訂正[J].氣象科技,2019,47(6):916~926

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  • 收稿日期:2018-01-11
  • 定稿日期:2019-01-31
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  • 在線發布日期: 2019-12-16
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