Winds between 20 and 80 km couple the lower and upper atmosphere through solar tides, planetary waves and gravity-wave forcing, and they set the operating envelope for near-space flight. Observations thin rapidly above the lower stratosphere, so reanalysis is in practice the only systematic source for studying and predicting this layer. Reanalyses reproduce the canonical solar-tidal harmonics here, and satellite comparisons of temperature indicate that their tidal amplitudes weaken too rapidly above the upper stratosphere. How much tidal wind amplitude survives near the mesopause has not been measured against ground-based observations, and the consequences for reanalysis-trained prediction have not been drawn. Winds from three meteor radars spanning 23° of latitude are compared with collocated ERA5, and an adaptive Takenaka–Malmquist neural operator is trained on seven-level ERA5 vector winds over eastern Asia and evaluated against eleven capacity-matched architectures, MERRA-2 and the radar observations. ERA5 retains 15 to 36 % of the observed semidiurnal and 30 to 82 % of the observed diurnal wind amplitude at 80 km. The operator attains the lowest wind-speed and direction errors evaluated, 2.215 ms^−1 and 5.2°, and improves on three-hour ERA5 persistence at all three radar sites. Without frequency supervision its learned poles converge on the semidiurnal and terdiurnal harmonics, vary by only 4 to 11 % across the domain, and reappear after retraining on MERRA-2. The amplitude deficit constrains what any reanalysis- trained model of this layer can reproduce, and the recovered frequencies give a representation that can be audited directly against observations.