基于GRAPES全球分析系统的Hybrid-3DVAR混合同化研究
Hybrid Ensemble-3DVAR Data Assimilation Scheme for the GRAPES Global Model
张利红 1龚建东 2庄照荣2
作者信息
- 1. 四川省气象台,成都 610071
- 2. 中国气象局地球系统数值预报中心,北京 100081
- 折叠
摘要
本文基于我国自主研发的GRAPES全球 3DVAR同化系统,利用NCEP全球集合预报产品和time-lagged方法,针对膨胀系数、集合样本数和集合权重系数,开展了每日 4次、连续一周的GRAPES全球Hybrid-3DVAR混合同化研究.结果表明:所有试验中,集合样本取 60个、集合权重取 0.5时,得到的混合同化分析和预报误差最小;在该混合同化系统中,在高层也考虑静态背景误差协方差和集合背景误差协方差的耦合,可避免混合同化方案分析场误差在 150 hPa及以上过大,并超过3DVAR分析场误差的情况.
Abstract
Using NCEP ensemble forecast products and continuous experiments,the GRAPES global ensemble-3DVAR,which is a new hybrid assimilation system is studied.Of all the experimental schemes,the GRAPES global ensemble-3DVAR is found to have the smallest analysis and forecast errors when the ensemble sample number is 60 and the ensemble weight is 0.5.However,above 150 hPa,the analysis error exceeded that of the 3DVAR.Therefore,the coupling of the static covariance and the ensemble covariance are also con-sidered for upper layers,which is different from that of the original design.Our experiments revealed that this improvement could resolve the above-mentioned problem of large errors in the upper layer analysis.
关键词
混合同化/GRAPES全球3DVAR/背景误差协方差Key words
Hybrid assimilation/GRAPES global 3DVAR system/Background error covariance引用本文复制引用
基金项目
长江流域气象开放基金项目(CJLY2022Y10)
高原与盆地暴雨旱涝灾害四川省重点实验室科技发展基金(SCQXKJYJXZD202303)
国家重点研发计划(2021YFC3000901)
四川省科技厅项目(2022YFS0540)
出版年
2024
NETL
NSTL
万方数据