中文摘要：

初始化和起始的不平衡问题在新一代的一个三维的变化数据吸收系统的上下文被讨论“天气研究”和预报模型。数字过滤器初始化的 Severaloptions 与一个雨暴风雨盒子被测试了。它被看那数字过滤器初始化，特别 diabatic 数字过滤器初始化和两次数字的过滤器初始化，有效地为数字天气把假高频率噪音从起始的数据移开预言和生产平衡起始的条件。为盖住一个 3 天的时期的六个连续断断续续的数据吸收周期，意味着初始化增长并且影响预报变量被学习。DFI 被表明了提供 hydrometeors 和垂直速度的更好的调整，减少了旋转起来时间，并且改进了预报变量数量。

英文摘要：

Initialization and initial imbalance problem were discussed in the context of a three-dimensional variational data assimilation system of the new generation ＂Weather Research and Forecasting Model＂. Several options of digital filter initialization have been tested with a rain storm case. It is shown that digital filter initialization, especially diabatic digital filter initialization and twice digital filter initialization, have effectively removed spurious high frequency noise from initial data for numerical weather prediction and produced balanced initial conditions. For six consecutive intermittent data assimilation cycles covering a 3-day period, mean initialization increments and impact on forecast variables are studied. DFI has been demonstrated to provide better adjustment of the hydrometeors and vertical velocity, reduced spin-up time, and improved forecast variables quantity.