短期集合降水概率预报试验

以MM5模式作为试验模式, 通过选取不同的物理过程参数化方案产生8个集合成员, 分别用平均法、相关法和Rank法对2001年11月至2002年5月期间的22个降水个例进行短期集合降水概率预报试验。试验结果显示对小雨—大暴雨6类降水的概率预报, Rank法的综合预报效果明显好于相关法和平均法, 相关法的综合预报效果与平均法基本相同; 无论从均方误差角度还是从命中率和假警报率的相对大小角度, 对小雨、中雨、大雨和暴雨各量级以上降水的概率预报, Rank法的平均预报效果是三种方法中最好的, 相关法的平均预报效果与平均法相同; Rank法好于平均法的平均幅度从均方误差角度较大, 从命中率和假警报率的相对大小角度则较小。平均而言, 三种方法对各量级以上降水的概率预报都是有技巧预报, 对量级小的降水的概率预报技巧高于对量级大的降水的概率预报技巧。

Experiments of Short-range Ensemble Precipitation Probability Forecasts

In order to obtain useful information and create probability forecasts from ensemble, experiments of short-range ensemble precipitation probability forecasts are made for 22 precipitation cases from November 2001 to May 2002. The ensemble is created by using MM5 model configuration with different model physical process parameterization schemes and identical initial conditions. There are 8 ensemble members. Precipitation probability forecasts are created from the ensemble by using the methods of "Average", "Correlation" and "Rank". Calculations of ranked probability score (RPS), Brier score (BS) and relative operating characteristic (ROC) indicate that, for the synthetic effect of all precipitation categories' probability forecasts, "Rank" is much better than "Correlation" and "Average", and "Correlation" is almost same as "Average". For the average effect of every precipitation category's probability forecasts, "Rank" is also the best among the three methods, and "Correlation" is same as "Average". The average BS difference between "Rank" and "Average" is large and the average ROC square difference between the two methods is small. Averagely, the three methods' probability forecasts are all skillful for all precipitation categories. The skill of probability forecast for small precipitation category is higher than the skill large precipitation category.