The traditional model perturbation method of ensemble prediction is usually used to describe random errors of physical processes, but the model inevitably has systematic bias. Therefore, in order to reduce the impact of systematic bias on ensemble prediction, the CMA-GEPS is employed to obtain systematic bias tendency using the empirical orthogonal function (EOF) method. In the integration process, the systematic bias correction method and the traditional Stochastically Perturbed Parameterization Tendency (SPPT) are combined to build a model perturbation method (Bias correction of bias tendency based on SPPT, SPPT-B) that combines systematic bias and random errors of ensemble forecast. Ensemble forecasting experiments are designed and carried out to explore the impact of SPPT-B on global ensemble forecasting. The conclusions are as follow: (1) The first EOF mode of the systematic bias can reflect the main characteristics of the systematic bias well. It shows that basically the systematic bias in the upper troposphere is larger than that in the middle and lower troposphere and increases linearly with forecast lead time. (2) The systematic bias correction method and SPPT-B can effectively reduce the systematic bias in upper and lower levels in the southern and northern Hemispheres and in the tropics, and SPPT-B can significantly improve Spread in the tropics. (3) The effect of the two schemes on the improvement of ensemble prediction skill in the upper troposphere is better than that in the lower troposphere. The above results indicate that the model perturbation method that considers both systematic bias and random errors can effectively improve global ensemble forecasting skill, and can provide a scientific basis for the development of global ensemble forecasting model perturbation method considering both systematic bias and random errors.

基于重庆市气象局中尺度数值预报业务系统,开展不同地形平滑方案对模式降水预报的影响研究,详细对比WRF模式中不使用地形平滑方案以及使用s-d-s和1-2-1两种平滑方案生成的静态地形高度场的差异,开展不同地形平滑方案批量平行试验并选取典型强降水个例进行对比分析,结果表明:不同地形平滑方案生成的静态地形高度场之间有明显的差异,特别是在地形较为陡峭的高原和山脉等地区,最大绝对偏差可达462.56 m;s-d-s和1-2-1两种地形平滑方案主要平滑掉了模式地形中较小尺度的地形特征,且总体而言1-2-1方案的平滑效果比s-d-s方案明显.连续一个月批量平行试验降水预报检验结果表明,进行模式地形平滑对大雨及以上量级降水预报有正面影响,且使用1-2-1平滑方案的预报结果优于使用s-d-s平滑方案的预报结果;降水个例对比分析结果表明:采用不同的地形平滑方案会造成垂直速度和水汽通量散度预报的明显差异,这样的明显差异会进而影响强降水预报的落区和强度.