中文摘要：

四维变分资料同化仍将是未来相当长时间内业务数值天气预报中所使用的主流同化方法．针对全球数值天气预报业务系统对气象资料同化技术的需求，在WRFDA软件框架结构的基础上，发展了一个与全球谱模式配套使用的四维变分资料同化系统YH4DVAR．系统将背景场、观测处理、重力波控制和偏差订正进行综合考虑，设计了一体化目标函数，引入了小波背景场误差协方差模型，实现了增量方法以及卫星遥感资料的直接同化．单点试验表明YH4DVAR的背景场误差模型具有各向异性、垂直相关和水平相关不可分离性、以及与位置的相关等特性．从2009年7月到2010年6月的分析预报试验结果表明，由YH4DVAR和全球谱模式组成的分析预报系统在北半球和亚洲地区的可用预报时效可以达到8天以上．

英文摘要：

The mainstream data assimilation system in operation will still employ four-dimensional variational data assimilation（4DVAR） method in a long time of future. We develop a new 4DVAR system, i.e., YH4DVAR, using global spectral model as a constraint to impose a dynamic balance on the assimilation. The cost function of YH4DVAR consists of four terms： background, observations, digital filter, and bias correction, respectively. YH4DVAR employs the wavelet background error convarianee, the multi-resolution incremental formulation, the tangent linear and adjoint models for dynamics core and physical processes, and ATOVS radiance data assimilation. Simultaneous spatial and spectral variations of horizontal and vertical covariance are achieved by dividing the control vector into several parts, each of which corresponds to a band of total spherical wavenumbers. Using NWP consisting of YH4DVAR and global spectral model, the anomaly correlation with the verifying analysis for geopotential height 8-day forecast on the 500 hPa isobaric surface at 12-month mean is above 60%. The formulation and implementation of YH4VAR are described in detail in this paper.