SLAF 方法的改进及其对广东地区一次飑线过程集合预报研究

摘要

本文在以滞后时间为权重的经典尺度化时间滞后法（SLAF）基础上，提出了一种改进方法，将滞后预报与控制预报之间差值场的均方根误差（RMSE）作为尺度化因子，构成集合预报成员，对比分析经典 SLAF 和改进 SLAF 方法对2007年4月23—24日广东地区一次飑线过程集合预报试验的模拟效果。结果表明：改进 SLAF 方法预报的各变量 RMSE 值有所降低，成员间离散度普遍增加；改进 SLAF 方法对强降水中心位置及降水强度的预报均优于经典 SLAF 方法。另外，多组加扰变量试验结果表明，对位温进行扰动的预报效果明显优于其他变量；不同的扰动变量对预报结果的影响不同，正确地选择扰动变量可明显提高预报效果。%A modified method of Scaled Lagged Average Forecasting (SLAF)was introduced to produce ensemble members considering root mean square error (RMSE)of difference between lagged forecasts and control runs as scaled factors.Both original and modified SLAF methods were utilized for the ensemble forecasts of a squall line process in Guangdong province on April 23 to 24,2007 and their simulation effects were compared.The results in-dicate that RMSEs of all variables determined using the modified SLAF decrease with increase of dispersion among members,while the forecasting center position and intensity of heavy rainfall for the modified SLAF are superior to those of the original one.Schemes with different variables for initial disturbances are tested.Forecasting is better for disturbance of potential temperature than for disturbance of other variables.The effect of different disturbance on forecasting is different,so selecting appropriate variables could enhance significantly the accuracy of forecas-ting.