Dun-Yong Zheng

Learning Thermospheric State Evolution: An Adaptive Neural Operator Framework Based on TIE-GCM Simulations

Reliable short-term prediction of thermospheric states is important for satellite drag applications but remains difficult because of nonlinear, multiscale variability. We developed a multivariable Adaptive Fourier Neural Operator (AFNO) surrogate using 24 years (2000–2023) of Thermosphere–Ionosphere Electrodynamics Gen...