结合历史资料的数值天气预报误差订正

Error Calibration of Numerical Weather Prediction with Historical Data

中文关键词:  数值预报订正  ANO方法  历史资料  降水  WRF模式

英文关键词:Calibration of numerical prediction  ANO method  Historical data  Precipitation  WRF model

中文摘要:

      运用基于历史资料的模式距平积分订正(ANO)方法,结合欧洲中心的ERA-interim再分析资料和0.1度分辨率的中国地面自动站与CMORPH卫星反演降水资料融合逐时降水产品,对高分辨非静力WRF模式的数值预报结果进行订正试验,检验了ANO方法对灾害性天气、尤其持续性强降水预报的订正改进效果。对1983-2013年7月中旬四川地区数值预报结果订正前后与观测和再分析数据的比较表明,ANO方法不仅在环流场的预报订正试验中有较为显著的效果,对模式降水预报结果也有改进,能够有效提高模式对强降水的预报精度和评分、减小预报偏差,其中对2013年7月8—13日高分辨预报结果的ANO订正试验发现,订正环流场各变量都有改进,其中位势高度距平相关系数ACC平均提高了7.8%,均方根误差RMSE平均降低了55.7%,降水(特别是暴雨以上量级)的ETS评分和TS评分也有不同程度的提高,并得到多年独立样本的高分辨数值预报订正结果的支持。

英文摘要:

      Using the method Anomaly Numerical-correction with Observations (ANO) based on historical observation data and anomaly integration, we performed a numerical calibration to the high-resolution simulations with the nonhydrostatic WRF3.5 model. The ERA-interim reanalysis and 0.1-degree rainfall data, which is a blending of the surface AWS rainfall observation and retrieved precipitation from CMORPH data, act as the historical observational series. The impact on numerical prediction of disaster weather, especially persistent heavy rainfall is evaluated. The results of the application of ANO in Sichuan heavy rainfall case in July 2013 illustrate that the correction not only improves atmospheric circulation simulation obviously, but also makes the modeled heavy rainfall more realistic in comparison with the observation. Amelioration of circulation and precipitation forecasting, ETS and TS score of heavy rain and also decrease of precipitation bias is observed. The calibration to high-resolution simulation of case 8-13 July shows obvious improvement to the circulation quantities, where an increase of Anomaly Correlation Coefficient (ACC) of the geopotential height by 7.8% and decrease of Root Mean Square Error (RMSE) by 55.7% in average. Meanwhile, ETS and TS score of precipitation (especially heavy rain and above) are also well corrected. The conclusion is supported with the independent samples of high-resolution numerical results across several years.