大气重力波对大气水平和垂直结构以及垂直耦合具有显著影响。目前大气重力波相关的 研究表明：①卫星适用于中高层大气重力波的观测，雷达在其垂直结构的精细观测方面最具优势， 再分析资料则更适合用于全球大气重力波的特征分析。②相较于非地形重力波，地形重力波的垂 直波长相对较长，且普遍可以传播至更高高度。③由于激发源相对固定，地形重力波溯源的结果 相对准确，而非地形重力波的溯源难度很大，准确率偏低。④采用主流的静力和非静力参数化方 案，能在数值模式中比较完整地模拟地形重力波的拖曳作用；采用单波和全局谱技术可以较为准 确地模拟非地形重力波东西向的动量通量；但是目前尚不能准确模拟两类大气重力波生成发展的 全过程。未来，随着观测技术的提升，会获取更多高质量的观测数据，这将有助于更清晰地了解大 气重力波的特征。在此基础上，参数化方法的进展以及人工智能技术的应用，有望对两类大气重 力波的形成机制有更深入的认识，从而提升天气和气候模拟预测的准确性。

Abstract：Gravity Waves (GW) have a significant impact on the structure of the entire atmosphere and the coupling between atmospheric layers. Research on gravitational waves is of great importance for deepening our understanding of atmospheric dynamics and improving atmospheric models. Gravitational waves play a significant role not only in astronomy and physics but also in atmospheric science, where they are used to study phenomena such as airflow, waves, and climate change in the atmosphere.The review in this paper showed that: ① Satellites are suitable for observing the middle- and upper- layer atmosphere, radar is most advantageous for fine observations of vertical wave connections, and reanalysis data are more suitable for analyzing global GW characteristics; ② Compared to non-orographic gravity waves, orographic gravity waves have relatively longer vertical wavelengths and can generally propagate to higher altitudes; ③ Compared with non-orographic gravity waves, it is much more easy to tracing orographic gravity waves because of the relatively fixed wave source; ④ Using the common parameterization schemes can simulate the drag effect of orographic gravity waves well; using single wave and global spectral techniques can predict the east-west momentum flux of non-orographic gravity waves. However, it is still not possible to accurately simulate the entire process of generation and development of both types of GW. Overall, there is still much room for further improvement and exploration in the areas of observation, identification, feature analysis, and parameterization of GW. In the future, with the advancement of observation technology, more high-quality observational data will emerge, which will help to gain a clearer understanding of the characteristics of GW. Based on this, the progress in parameterization methods and the application of artificial intelligence technology are expected to deepen our understanding of the formation mechanisms of the two types of GW, thereby improving the accuracy of weather and climate simulation predictions.