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Urban boundary layer characterization is currently a challenging and relevant issue, because of its role in weather and air quality modelling and forecast. In many cities, the effect of complex topography at local scale makes this modelling even more complicated. This is the case of mid-latitude urban areas located in typical basin topographies, which usually present low winds and high turbulence within the atmospheric boundary layer (ABL). This study focuses on the analysis of the first ever measurements of wind with high temporal and vertical resolution throughout the ABL over a medium-sized city surrounded by mountains in southern Spain. These measurements have been gathered with a scanning Doppler lidar system and analyzed using the Halo lidar toolbox processing chain developed at the Finnish Meteorological Institute. We have used the horizontal wind product and the ABL turbulence classification product to carry out a statistical study using a two-year database. The data availability in terms of maximum analyzed altitudes for statistically significant results was limited to around 1000–1500 m above ground level (a.g.l.) due to the decreasing signal intensity with height that also depends on aerosol load. We have analyzed the differences and similarities in the diurnal evolution of the horizontal wind profiles for different seasons and their modelling with Weibull and von Mises probability distributions, finding a general trend of mean daytime wind from the NW with mean speeds around 3–4 m/s at low altitudes and 6–10 m/s at higher altitudes, and weaker mean nocturnal wind from the SE with similar height dependence. The highest speeds were observed during spring, and the lowest during winter. Finally, we studied the turbulent sources at the ABL with temporal (for each hour of the day) and height resolution. The results show a clear convective activity during daytime at altitudes increasing with time, and a significant wind-shear-driven turbulence during night-time.

The atmospheric molecular number density can be obtained from atmospheric temperature and pressure profiles and is a significant input parameter for the inversion of lidar measurements. When measurements of vertical profiles of temperature and pressure are not available, atmospheric models are typically considered a valid alternative option. This paper investigates the influence of different atmospheric models (forecast and reanalysis) on the retrieval of aerosol optical properties (extinction and backscatter coefficients) by applying Raman and elastic-only methods to lidar measurements, to assess their use in lidar data processing. In general, reanalyzes are more accurate than forecasts, but, typically, they are not delivered in time for allowing near-real-time lidar data analysis. However, near-real-time observation is crucial for real-time monitoring of the environment and meteorological studies. The forecast models used in the paper are provided by the Integrated Forecasting System operated by the European Centre for Medium-Range Weather Forecasts (IFS_ECMWF) and the Global Data Assimilation System (GDAS), whereas the reanalysis model is obtained from the fifth-generation European Centre for Medium-Range Weather Forecasts ReAnalysis v5 (ERA5). The lidar dataset consists of measurements collected from four European Aerosol Research Lidar Network (EARLINET) stations during two intensive measurement campaigns and includes more than 200 cases at wavelengths of 355 nm, 532 nm, and 1064 nm. We present and discuss the results and influence of the forecast and reanalysis models in terms of deviations of the derived aerosol optical properties. The results show that the mean relative deviation in molecular number density is always below ±3%, while larger deviations are shown in the derived aerosol optical properties, and the size of the deviation depends on the retrieval method together with the different wavelengths. In general, the aerosol extinction coefficient retrieval is more dependent on the model used than the aerosol backscatter retrievals are. The larger influence on the extinction retrieval is mainly related to the deviation in the gradient of the temperature profile provided by forecast and reanalysis models rather than the absolute deviation of the molecular number density. We found that deviations in extinction were within ±5%, with a probability of 83% at 355 nm and 60% at 532 nm. Moreover, for aerosol backscatter coefficient retrievals, different models can have a larger impact when the backscatter coefficient is retrieved with the elastic method than when the backscatter coefficient is calculated using the Raman method at both 355 nm and 532 nm. In addition, the atmospheric aerosol load can also influence the deviations in the aerosol extinction and backscatter coefficients, showing a larger impact under low aerosol loading scenarios.