中文摘要：

本文基于YH4DVAR业务系统构建了集合资料同化试验平台,利用10个集合样本统计得到的流依赖背景误差能显著改进业务应用中背景误差方差的结构和大小.但是受样本数的限制,背景误差方差的集合估计值中引入了大量的随机取样噪声.为了降低噪声对估计值的影响,本文采用谱滤波方法,根据信号和噪声尺度的统计特征构造一个低通滤波器来滤除背景误差方差估计值中的大部分随机取样噪声.在2013年第九号台风＂飞燕＂的集合方差滤波试验中,10个样本的滤波结果优于30个样本的集合估计值.谱滤波方法的成功应用有效降低了集合资料同化系统对集合样本数的要求,将是集合资料同化系统未来业务化运行的一项不可或缺的关键技术.

英文摘要：

Ensemble Data Assimilation（EDA）system is able to provide flow-dependent estimates of background error covariances matrix.Therefore,it is possible to overcome the shortcomings of quasi-static or climatic covariance models currently used in most of the variational data assimilation systems.However,the finite ensemble size implies a detrimental sampling noise for the background error variances estimation.To resolve this problem,a spectral filtering technique is employed to formulate a low-passing filter whose truncation wave number is determined according to the typical horizontal length scales of noises and valuable signals.The rationality and efficiency of this technique are analysed in a typhoon assimilation experiment.The method of spectral filtering was used to filter sampling noise in the EDA raw background error estimation.At first,an experimental EDA system was built based on the operational YH4 DVAR analysis.This system consisted 10 lower resolution members generated by perturbing observations,sea surface temperature（SST）fields and model physical tendencies.Secondly,the vorticity background error of the 9th typhoon in 2013 calculated from 10,20 and 30members respectively were compared with the operational one.Though EDA estimates showed superiority to the later,its slow rate convergence of sampling noise with respect to ensemble size and the limited ensemble dimensions made the filtering process still necessary.FollowingRaynaud′s theory,the sampling noise power spectrum was calculated from the expectation of the ensemble-based error covariance matrix.Then,a smooth spectral filter was applied to the 10 member raw estimate.The filter′s truncation wave number was determined according to the typical horizontal length scales of noises and valuable signals.The filtered result was compared with 30 member raw estimate.In this typhoon assimilation experiment,flow-dependent background error variances can be estimated accurately from the experimental EDA system with 10,20 or 30 members.Corresponding to the