We investigate the time evolution of the Local Boundary Layer (LBL) for the first time over a mountain ridge at Nainital (79.5° E, 29.4° N, 1958 m a.m.s.l.) in the central Himalayan region, using a radar wind profiler (RWP) during November 2011 to March 2012, as a part of the Ganges Valley Aerosol Experiment (GVAX). We restrict our analysis to clear–sunny days, resulting in a total of 78 days of observations. The standard criterion of the peak in the signal-to-noise ratio (S ∕ N) profile was found to be inadequate in the characterization of mixed layer (ML) top at this site. Therefore, we implemented a criterion of S ∕ N > 6 dB for the characterization of the ML and the resulting estimations are shown to be in agreement with radiosonde measurements over this site. The daytime average (05:00–10:00 UTC) observed boundary layer height ranges from 440 ± 197 m in November (late autumn) to 766 ± 317 m above ground level (a.g.l.) in March (early spring). The observations revealed a pronounced impact of mountain topography on the LBL dynamics during March, when strong winds (> 5.6 m s⁻¹) lead to LBL heights of 650 m during nighttime. The measurements are further utilized to evaluate simulations from the Weather Research and Forecasting (WRF) model. WRF simulations captured the day-to-day variations up to an extent (r² = 0.5), as well as the mean diurnal variations (within 1σ variability). The mean biases in the daytime average LBL height vary from −7 % (January) to +30 % (February) between model and observations, except during March (+76 %). Sensitivity simulations using a mixed layer model (MXL/MESSy) indicated that the springtime overestimation of LBL would lead to a minor uncertainty in simulated surface ozone concentrations. However, it would lead to a significant overestimation of the dilution of black carbon aerosols at this site. Our work fills a gap in observations of local boundary layer over this complex terrain in the Himalayas, and highlights the need for year-long simultaneous measurements of boundary layer dynamics and air quality to better understand the role of lower tropospheric dynamics in pollution transport.