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.