SWCWARMS模式小時降水量時間滯后集合預報研究
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四川省重點實驗室項目(省重實驗室2018重點06、SCQXKJZD2019001、SCQXKJZD2021013)、中國局預報員專項(CMAYBY2020110)和中國局氣象關鍵技術項目(YBGJXM(2020)2A14)共同資助


Time-Lagged Ensemble Forecast of Hourly Precipitation Based on SWCWARMS Model
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    摘要:

    基于SWCWARMS模式9 km×9 km分辨率逐小時降水預報,通過時間滯后集合預報方法構建多個集合成員,使用SAL評分值計算相應集合成員的權重系數,進行不等權集合平均,從而得到新的逐小時降水預報。利用SAL、TS和BIAS檢驗方法對四川省2019年8月的逐小時降水量時間滯后集合預報及相應的SWCWARMS模式最新時次預報進行對比分析,結果表明:①時間滯后集合預報SAL檢驗的L值和A值都較模式預報更接近于0,較好地改善了降水位置和強度的整體預報水平;②時間滯后集合預報對逐小時降水晴雨TS評分提升明顯,評分提高百分率在10%左右,有效地減小了模式在晴雨方面的空報;③臨近預報時效,時間滯后集合預報方法對于大量級降水預報也有較好的訂正效果。

    Abstract:

    Based on the hourly precipitation from the 9 km×9 km resolution SWCWARMS model, ensemble members are formed by the timelagged ensemble forecast method. A new hourly precipitation forecast is obtained from the ensemble average of differential weights, which are calculated by the SAL scores of ensemble members. This study verified the timelagged ensemble and the model uptodate forecast of hourly precipitation in Sichuan from 1 to 31 August 2019 by the SAL, TS and BIAS evaluation method. The results show: (1) The timelagged ensemble method led to improvement on the overall level of the rainfall intensity and location forecast. The values L and A of SAL scores were both closer to 0. (2) The clearrain TS score of timelagged ensemble forecast was higher, and the percentage increase was about 10%. The method can reduce the false alarm of rain forecast. (3) In the lead time of nowcasting, the improvement of the high intensity precipitation forecast was also obvious.

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張武龍,王彬雁,陳朝平,馮漢中. SWCWARMS模式小時降水量時間滯后集合預報研究[J].氣象科技,2021,49(4):561~568

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  • 收稿日期:2020-09-10
  • 定稿日期:2020-12-29
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  • 在線發布日期: 2021-08-23
  • 出版日期: 2021-08-31
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