## 5 Conclusions  
In conclusion, this study provides an in-depth evaluation of ERA5 reanalysis data in the complex terrain of Baotou, highlighting both its strengths and limitations. The results indicate that ERA5 is effective in simulating horizontal wind speeds at lower altitudes, but it struggles with overestimating wind speeds above 1000 m, particularly during winter, and underestimating wind speeds during summer convective events. Vertical wind speeds are consistently underestimated, likely due to the model's coarse resolution, which is insufficient to capture fine-scale convective processes. ERA5 performs reasonably well in simulating temperature and humidity in lower layers, but it shows the significant overestimation of temperature and relative humidity at higher altitudes, particularly during summer, which may be related to terrain-induced thermal effects like the Foehn effect. Boundary layer heights are generally overestimated by ERA5, with seasonal and weather-related biases further complicating accurate simulation. These overestimations are particularly problematic during convective weather events and polluted conditions. The study also demonstrates that ERA5's performance is compromised in regions with complex terrain, where local effects such as orographic forcing and convective processes are inadequately represented. While ERA5 is a valuable tool for large-scale atmospheric studies, its limitations in capturing local-scale phenomena necessitate the integration of higher-resolution data and regional models, particularly in areas with complex terrain. Given these findings, it is recommended that ERA5 be used in conjunction with higher-resolution observational data and advanced modeling techniques, such as machine learning, to enhance its accuracy in simulating local meteorological phenomena in complex regions like Baotou. Further research should focus on improving ERA5's spatial resolution and incorporating new technologies to reduce simulation errors, particularly in capturing the dynamics of convective events and terrain-induced phenomena. This would significantly improve weather forecasting, air quality modeling, and climate studies in regions with similar topographies. **Supplementary Materials:** The following supporting information can be downloaded at: [[https://www.mdpi.com/article/10.3390/rs17030393/s1](https://www.mdpi.com/article/10.3390/rs17030393/s1)]([https://www.mdpi.com/article/10.3390/rs17030393/s1](https://www.mdpi.com/article/10.3390/rs17030393/s1)), Figure S1: Time-series plot of horizontal wind speeds for ERA5 data at each altitude superimposed on the ERA5 absolute deviation plot (ERA5 reanalysis data values minus observed data values); Figure S2: Time-series plot of vertical wind speeds for ERA5 data at each altitude superimposed on the ERA5 absolute deviation plot (ERA5 reanalysis data values minus observed data values); Figure S3: Time-series plot of temperature for ERA5 data at each altitude superimposed on the ERA5 absolute deviation plot (ERA5 reanalysis data values minus observed data values); Figure S4: Time-series plot of relative humidity for ERA5 data at each altitude superimposed on the ERA5 absolute deviation plot (ERA5 reanalysis data values minus observed data values); Figure S5: Detection Principle of WindCube 100S. **Author Contributions:** Conceptualization, Y.W., Y.S., Y.M. and J.X. ; methodology, Y.W. and Y.S. ; software, Y.W. and Y.T. ([PERSON]); validation, S.Y., Y.M., Y.T. ([PERSON]), M.A., X.R. and Y.S. ; formal analysis, Y.W. and Y.S. ; investigation, Y.W., Y.M. and J.X. ; resources, Y.M., Z.L., X.Z., Y.R., Y.T. ([PERSON]) and J.X. ; data curation, Y.M., Z.L., X.Z., Y.R., Y.T. ([PERSON]) and J.X. ; writing--original draft preparation, Y.W. and J.X. ; writing--review and editing, Y.S., Y.M., Y.T. ([PERSON]), K.P., X.R., S.Y., M.A. and J.X. ; visualization, Y.W. ; supervision, Y.S., Y.M. and J.X. ; project administration, Y.M. and J.X. ; funding acquisition, Y.M. and J.X. All authors have read and agreed to the published version of the manuscript.