Global Wind Field Reconstruction in the Mesosphere and Lower Thermosphere (MLT) During Geomagnetic Storms by Fusing TIDI and SABER Data: A Generative Adversarial Network ( GAN ) Approach

The Mesosphere and Lower Thermosphere establish an essential connection between Earth's lower atmosphere and upper atmosphere because wind patterns essential for atmospheric movement also influence energy distribution and chemical movements during geomagnetic storms that disrupt satellite operations and space weather prediction systems. The existing reconstruction methods that use single‐instrument data and physics‐based models and statistical methods show two main flaws because they cannot capture all the spatial details and face varying levels of uncertainty at different altitudes, and they cannot model the complex weather patterns during storm events. The study presents an innovative intelligent generative reconstruction framework which combines TIMED Doppler Interferometer wind data with SABER thermal emission data through a Generative Adversarial Network structure that utilizes an attention‐based spatial–channel feature fusion method which the Adam algorithm helps to improve. The attention module dynamically weights wind–temperature interactions to enhance spatial continuity and altitude‐aware learning, while the Generative Adversarial Network generator reconstructs physically consistent three‐dimensional wind vectors (U, V, W) and the discriminator enforces physical consistency. The research results based on 1390 fused samples, which included 973 training samples, 208 validation samples and 209 testing samples, achieved excellent prediction results. The study achieved R 2 values of 0.9889, 0.9891 and 0.9911 for the train, validation and test sets, respectively, while providing normalized RMSE values of 0.2321, 0.2343 and 0.2069 and MAE values of 0.1073, 0.1198 and 0.1111. The R 2 value between 0.98 and 0.99 stays intact during altitude‐binned evaluation across the 60–110‐km range, while the storm‐phase analysis shows that geomagnetic disturbances lead to increased RMSE, yet the system maintains its fundamental reconstruction stability. The proposed framework delivers an expandable solution that utilizes data to create ongoing high‐resolution worldwide Mesosphere and Lower Thermosphere wind reconstruction, which enables advanced space weather monitoring and upper atmospheric research.