雷達外推與數值模式動態融合降水概率預報方法
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國家自然科學基金項目(41276033)、南京氣象雷達開放實驗室研究基金(BJG201105)資助


Dynamic Blending Probabilistic Precipitation Forecast Method Based on Radar Extrapolation and Numerical Weather Prediction
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    摘要:

    提出一種基于動態權重的降水概率融合預報方法。首先建立一個適用于權重分配的評分模型,對基于雷達光流外推的降水概率預報和基于數值模式經反射率換算后的降水概率預報的預報準確率分別加以評估;提出一種改進的Brier評分法,該方法兼顧了降水落區的大小和降水量,降低評分對樣本數據數量多少的敏感性;根據兩種在不同預報時效的評分,動態地分配兩種預報方法在不同預報時效的權重。試驗部分通過Brier等評分驗證表明,融合后各個預報時效的預報都表現出與雷達外推或數值模式相近甚至更高的技術評分。

    Abstract:

    A new method for probabilistic precipitation forecasts with dynamic weights is proposed. First, a scoring model for weight distribution is established and the forecast accuracy calculated from radar extrapolation and numerical model prediction is evaluated. Second, an improved method based on the Brier scoring is presented, which takes into account the size of the precipitation area and precipitation, and reduces the sensitivity to the number of samples. Third, according to the scores of different lead times, the weights of two kinds of forecasting methods are dynamically allocated in different forecast lead time. In the experimental part, the Brier and other ratings show that the prediction of each lead time is similar to the radar extrapolation or the numerical model, and even has a higher technical score.

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薛峰,王興,吳雙,苗春生,張琳焓.雷達外推與數值模式動態融合降水概率預報方法[J].氣象科技,2017,45(6):1036~1042

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  • 收稿日期:2016-11-01
  • 定稿日期:2017-02-07
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  • 在線發布日期: 2017-12-28
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