## 1 Introduction
(2013) combined sounding data to study the applicability of upper-air temperature fields in various reanalysis datasets across China, revealing that ERA5's upper-air temperature data accurately depicted the upper troposphere in northern China [15]. [PERSON] et al. (2024) investigated large-amplitude inertia gravity waves (GWs) over Syowa Station, Antarctica, using PANSY radar data and ECMWF reanalysis v5 (ERA5) data from October 2015 to September 2016. Their study found that ERA5 significantlyunderestimated the absolute momentum flux (AMF) of the GWs, particularly in the stratosphere, with a factor-of-5 underestimation between 5 and 12.5 km altitudes, primarily due to the model's larger vertical grid spacing and the shorter vertical wavelengths of the dominant GWs [16]. [PERSON] et al. (2019) evaluated the accuracy of ERA5, ERA-Interim, JRA-55, CFSv2, and MERRA-2 in the Arctic, finding that ERA5 had higher correlation coefficients and smaller biases and root mean square errors for temperature, wind speed, and specific humidity compared to other reanalysis datasets [17]. [PERSON] et al. (2024) assessed the vertical accuracy of various meteorological elements in ERA5 data over mountainous regions, finding that ERA5 data overestimated temperatures above 2000 m in mountainous areas [18]. However, the vertical structure accuracy of ERA5 data over the Inner Mongolia Plateau has not been fully evaluated. Therefore, evaluating and analyzing the vertical structure accuracy of ERA5 data in Baotou is of great significance for understanding the meteorological characteristics and changes in this region. The complex terrain near Baotou, bordered by the Yinshan Mountains to the north and the Yellow River to the south, induces intricate local circulations due to topographical forcing, impacting the accuracy of ERA5 reanalysis data. Previous research has indicated discrepancies between ERA5 boundary layer heights and actual heights, as ERA5 boundary layer heights are computed using the Richardson number, which relies on numerous basic meteorological variables [19; 20]. Therefore, the accuracy of ERA5's basic meteorological elements is crucial. This study utilizes core meteorological variables from ERA5, including temperature, humidity, horizontal and vertical wind speeds, wind direction, and planetary boundary layer height (PBLH), and compares them with high-precision observational data to evaluate the vertical structure accuracy of ERA5 in the complex terrain of Baotou. The inclusion of PBLH data in this comparison is particularly valuable, as the boundary layer height influences the dispersion of pollutants and impacts various atmospheric processes, which are especially crucial in industrial regions with complex terrain like Baotou. This research provides critical reference data for meteorological studies and climate modeling in Inner Mongolian industrial cities, offering reliable scientific evidence to support weather forecasting and climate change studies. The observational period spans January, February, and March (winter) and July and August (summer) of 2021. Extreme weather events, such as heavy rainfall and sandstorms, are common on the Mongolian Plateau, with significant impacts on local agriculture, livestock, and the daily lives of residents, resulting in substantial economic losses. This study analyzes the vertical structure and boundary layer height accuracy of ERA5 reanalysis data, with the goal of improving the accuracy and timeliness of disaster warnings, thereby aiding in more effective responses to extreme weather events. This study leverages high-precision instruments deployed by the Baotou Municipal Ecological Environment Bureau to observe the vertical profiles of key meteorological variables and uses the observational data to assess the accuracy of the ERA5 reanalysis, particularly in relation to planetary boundary layer height (PBLH).