中文摘要：

气象数值预报中,由于分析过程引入初始非平衡,从而引起虚假快波振荡,重力波控制弱约束把资料分析过程和初始化过程结合在一起,通过数字滤波弱约束在极小化过程中实现对分析场的平衡约束,克服非平衡问题.以2008年初的一次南方雨雪天气为研究个例,进行了数字滤波弱约束的同化试验和预报试验,结果表明,数字滤波弱约束4D-Var能充分控制快波振荡的出现和初始调整现象,使得到的分析场不仅能更好的逼近观测,而且能更好地与模式动力相协调.预报检验的结果表明,在同化过程中施加数字滤波弱约束,能有效滤除由于地形或观测资料等因素带来的初始噪声信息,改善分析场的平衡性质,从而提高预报质量.

英文摘要：

Variational data assimilation is an advanced technique to provide correct and high quality initial fields for the numerical model. Digital filter is not restricted to initialization; it may also be implemented as a weak constraint penalizing the analysis towards a balanced state in a preoperational 4D-Var system. The constraint is imposed only on the analysis increments to damp spurious fast oscillations associated with gravity–inertia waves. The influence of DFI as a weak constraint on 4D-Var forecast is assessed by assimilation experiments with the recently occurring severe snow weather. It is shown that the weak constraint imposed only on the increments manages to control efficiently the emergence of fast oscillations in the resulting forecast while maintaining a closer fitting to the observations.