区域集合预报系统的集合变换卡尔曼滤波初始扰动的余弦分析约束方案

Cosine Analysis Constraint Scheme Based on ETKF Initial Perturbations in the GRAPES Regional Ensemble Prediction System

基于GRAPES区域集合预报系统,针对初始扰动对预报误差描述能力依然不足的问题,在动力降尺度构造集合初始扰动的基础上,本文利用集合变换卡尔曼滤波(ETKF)方法更新集合扰动以捕获更多中小尺度扰动信息,提出并发展了一种融合资料同化分析增量特征信息的新的分析约束扰动方法——余弦分析约束扰动,对ETKF更新后集合初始扰动的不合理信息进行适应性自主调整,使得不同空间尺度的初始扰动物理结构和振幅尽可能与相应的预报误差结构和振幅相一致。试验结果表明,随天气形式的持续演变,强降水区域分析约束调整的集合初始扰动的中小尺度信息明显更为丰富,且温度扰动显示出更明显的优势;在模式积分初期,余弦分析约束扰动方案的集合离散度和扰动能量在空间分布与演变特征等方面均表现出更为合理的发展趋势,初始扰动质量及预报性能由此得到了有效改善。

The disparity between initial perturbations and forecast errors is a primary challenge in the Global/Regional Assimilation Prediction System–Regional Ensemble Prediction System(GRAPES–REPS).Herein,the Ensemble Transform Kalman Filter method is introduced to update the perturbations produced by dynamic downscaling in the GRAPES–REPS and can capture more mesoscale perturbations.Moreover,a new method called the cosine analysis constraint scheme is developed to optimize the updated initial perturbations,rendering the latest perturbations more consistent with the forecast errors.The results reveal that the perturbations adjusted using the cosine analysis constraint scheme may show the most abundant information on mesoscale perturbations compared to other experiments in the key area of precipitation.Notably,the structure and evolution of the perturbations become more reasonable and match better with the development of weather systems on different scales after constraining.In addition,the improvements in spread and perturbation energy are distinct,particularly in the early period of simulation.