Summertime westward-to-eastward zonal wind reversal near the mesopause is a key manifestation of wave–mean flow interaction in the mesosphere and lower thermosphere. We examined this zonal wind reversal over Langfang, China, during May–July 2024 using co-located MF and meteor–radar winds together with SD-WACCM output. The reversal height and vertical shear near the reversal height were obtained from a linear fitting. Both radars showed pronounced temporal dependence for the zonal wind-reversal height, with a higher height at the beginning of summer, which decreased from May to July. The MF radar placed the transition slightly higher than meteor radar, both of which are confined to the mesopause region. The SD-WACCM output showed clear zonal wind reversal, but the reversal heights were between MF and meteor observations. Moreover, the decreasing trend of the zonal wind-reversal height in the SD-WACCM output was less evident than in radar observations. Nevertheless, the zonal wind reversal exhibited clear diurnal variations. The total zonal wind tendency due to gravity wave-breaking in the SD-WACCM output was utilized to diagnostically analyze the reasons, wherein diurnal variations in the wind-reversal height corresponded well to the diurnal variations in gravity wave-dragging. Monthly model diagnostics further showed the positive strengthening of gravity wave drag near 80–90 km from May to July. Our analysis showed that the temporal variation in the background flow and the reversal layers during 2024 were intimately related to gravity wave momentum deposition locally and globally.

Accurate wind measurements in the mesosphere and lower thermosphere (MLT) region are essential for climate modeling, satellite drag estimation, and space weather prediction. This study presents a comprehensive comparison and correlation analysis of the zonal and meridional wind observations from co-located meteor radar and medium-frequency (MF) radar systems in Kunming (102.1°E, 24.2°N), China, in the year 2022. Both zonal and meridional wind components were analyzed within the overlapping altitude range of 70–100 km. Statistical distributions of the wind speeds from both radars followed a near-Gaussian pattern concentrated within ±100 m/s, indicating good consistency. A joint dataset was constructed for the 78–100 km range, where over 2000 h of concurrent observations were available. The strongest correlation between the wind speed measurements of the two radars was ~0.6, which occurred near 82–84 km. Seasonal analysis further indicated better consistency in the winter and spring months, while the summer months exhibited reduced correlations, especially for zonal wind measurements. Systematic biases between the two instruments were also identified, with minimal intercept offsets observed from April to October. This study is valuable in the development of high-quality, long-term MLT wind field datasets for atmospheric research and numerical model validation.