中文摘要：

利用WRFV2.2模式,对1977年5月20日发生在美国Oklahoma的典型超级单体风暴进行集合预报试验。采用蒙特卡洛法对不同区域初值扰动,对比分析成员个数的变化对预报技巧的影响,检验集合技术应用于风暴尺度系统的可行性及应用价值。结果显示,基于WRFV2.2模式的风暴尺度集合预报（storm-scale ensemble forecasting,SSEF）能够从热力场和动力场上改善单一确定性预报,并成功预报极端降水,表明SSEF具有较高的应用和研究价值;总体上预报技巧随成员数增加而增加,当集合成员数达到5-13时,预报技巧呈饱和特征,不同变量、不同扰动区域时的饱和成员数略有差异。

英文摘要：

The fundamental goal of ensemble forecasting（EF） is to estimate a forecast probability density function（PDF） of possible future states of the atmosphere from which the true state is consistently a random sample.The skills of EF is superior to the deterministic-style NWP（numerical weather prediction） where a single run is considered in long-/meso-range.However,the skills of EF in the storm-scale is inscient.So an ideal storm case is simulated by the WRF（weather research and forecasting） model V2.2 on the supercell severe local storm,occurred in central Oklahoma on 20 May 1977 to study the feasibility whether EF can be applied to the forecast for the storm-scale system.Simultaneously the influence of the different ensemble sizes on the skills of the ensemble is explored through experiments with the addition of the random initial errors to different areas.It is found that the ensemble average can work in gaining higher forecast skills and protracting the effective forecasting.Although it enhances with the increase of ensemble sizes as a whole,the improvement is saturated when the ensemble sizes comes to 5—13.