中文摘要：

初始扰动方案是集合预报研究的核心问题之一。文中根据最新提出的基于集合卡尔曼变换（ETKF）理论的集合初始扰动方案,利用模拟观测系统及其调整的观测误差与放大因子的方案,研究发展了针对中国GRAPES全球预报系统的集合初始扰动方案,建立了GRAPES全球集合预报系统。利用14个集合成员进行了近两个月的集合预报试验,重点研究了初始扰动的结构特征、扰动振幅以及扰动增长特征,分析了集合扰动初始场的质量与性能。初步试验结果表明,基于ETKF初始扰动方案的GRAPES全球集合初始扰动能够较好地反映分析误差方差的主要模态结构和扰动振幅,并具有比较合理的集合离散度。分析误差方差能够准确地反应模拟观测资料的空间分布特征。初始扰动方差近似等于预报误差方差,并对全球观测系统的空间变化具有准确的响应。集合扰动具有合适的增长率,在96h的预报时效内可以有效地保持适当的集合离散度。52d集合预报统计分析显示,北半球集合平均的预报质量评分相对于控制预报具有较明显的优势,副热带高压特征线的个例预报也表明GRAPES全球集合预报在短期预报时效内具有很好的预报效果。基于ETKF初始扰动方案的GRAPES全球集合预报系统显示出良好的发展前景和应用潜力。

英文摘要：

Initial perturbations scheme is one of the important problems in the ensemble prediction. In this paper, an ensemble initial perturbations scheme for GRAPES is developed in terms of the ensemble transform Kalman filter （ETKF） method, and a new GRAPES global ensemble prediction system （GEPS） is constructed. The spherical simplex 14-member ensemble prediction experi- ments, using the simulated observation network and error characteristics of simulated observations and innovation-based inflation, are carried out over almost two months. The structural characters, perturbation amplitudes, and growth characters of the ETKF initial perturbations are investigated, and the qualities and abilities for the ensemble initial perturbations are analyzed. The preliminary experimental results indicate that the ETKF-based GRAPES ensemble initial perturbations could identify main normal structures of analysis error variance and reflect on the perturbation amplitudes. The initial perturbations and the spread are reasonable. The initial perturbation variance, which is equaled approximately to the forecast error variance, is found to respond to temporal changes in the observational spatial variations in simulated observational network density. The perturbations generated through the simplex method are also shown to exhibitvery high degree of consistency between initial analysis and short-range forecast perturbations. The appropriate growth and spread of ensemble perturbations can be maintained in 96 h lead time. The statistical results for 52 d ensemble forecasts show that the forecast scores of ensemble average for the Northern Hemisphere is higher than that of the control forecast. Potential additional benefits of the ETKF-based initial scheme when using more ensemble members, a real-time observational network and a more appropriate inflation factor will be explored in future.