航路网络作为民航运输网络的运行载体，承担着保障航空器安全高效运行的重要任务。当重要航路点因雷暴扰动失效时，易连锁反应至相邻节点最终导致网络性能的显著下降。针对现有复杂网络节点重要度评估模型未有效考虑雷暴扰动的问题，面向雷暴天气场景，将雷暴扰动特性纳入航路点重要度评估体系，利用博弈论方法对评估指标进行组合赋权，基于引力模型理论改进了TOPSIS（technique for order preference by similarity to an ideal solution）综合评价方法，建立基于博弈论-改进TOPSIS法的节点重要度评估模型，进而采用K中心点算法实现航路点聚类分级。以京津冀地区航班运行为例，对雷暴天气场景下的航路网络节点重要度进行评估，结果表明：在京津冀航路网络内，南部地区的航路点更易受雷暴天气影响且分布较为密集，该航路网络包含9个重要航路点，当航路网络中的重要航路点因雷暴影响而失效时，会对航路网络性能产生显著的负面影响。提出的基于博弈论-改进TOPSIS法的节点重要度评估模型可以有效识别出雷雨季节或雷暴高发地区航路网络中的重要航路点，从而为雷暴场景下航路网络结构优化与资源配置提供有效依据。

As the operational carrier of civil aviation transportation network, the air route network undertakes the important task of ensuring the safe and efficient operation of aircraft. When important waypoints fail due to thunderstorm disturbances, it is easy to chain reaction to adjacent nodes, ultimately leading to a significant decrease in network performance. Aiming at the problem that existing complex network node importance evaluation models do not effectively consider thunderstorm disturbances, the characteristics of thunderstorm disturbances were incorporated into the waypoint importance evaluation system for thunderstorm weather scenarios. The evaluation indicators were weighted using game theory methods, and the TOPSIS(technique for order preference by similarity to an ideal solution) comprehensive evaluation method was improved based on gravity model theory. A node importance evaluation model based on game theory improved TOPSIS method was established, and the K-medoids algorithm was then used to achieve waypoint clustering and grading. Taking flight operations in the Beijing-Tianjin-Hebei region as an example, the importance of air route network nodes in thunderstorm weather scenarios was evaluated. The results show that within the Beijing-Tianjin-Hebei route network, route points in the southern region are more susceptible to thunderstorm weather and are more densely distributed. The route network contains 9 important route points. When important route points in the route network fail due to thunderstorm impact, it will have a significant negative impact on the performance of the route network. The proposed node importance evaluation model based on game theory-improved TOPSIS method can effectively identify important waypoints in the route network during thunderstorm seasons or areas with high thunderstorm incidence, providing effective basis for optimizing the route network structure and resource allocation in thunderstorm scenarios.