Boundary layer and mixing layer height: Models vs. Ground-based measurements intercomparison

Detailed characterization of the planetary boundary layer (PBL) and mixing layer height (MLH) is essential for gaining insights into air quality, pollutant dispersion, and the dynamics of the lower atmosphere. This research involves MLH from four atmospheric models—ERA5 (European Centre for Medium-Range Weather Forecasts Reanalysis v5), Reanalysis, GDAS (Global Data Assimilation System), and GFS (Global Forecast System), representing diverse approaches commonly applied in atmospheric research, mainly in air quality studies. The intercomparison analyzes the simulated MLH from the models, comparing them with observations from radiosondes and ceilometers to capture diurnal and seasonal variations in boundary layer dynamics. The study reveals significant diurnal and seasonal variations, with a close alignment between ERA5 boundary layer and ceilometer mixing layer observations, Reanalysis consistently underestimating MLH altitude, and both GFS and GDAS models demonstrating reasonable diurnal cycles of MLH. During summer, all models underestimate MLH compared to ceilometer observations by 34–42 %, while in winter, overestimation relative to ceilometer observations ranges from 11 to 20 %. Factors contributing to this discrepancy, including meteorological variables and synoptic situations, were examined. GFS and GDAS tend to overestimate global radiation after 12:00 but underestimate MLH, while ERA5 consistently underestimated both radiation and MLH. Dependence in agreement between models and ceilometer observations was also observed for various synoptic situations. The interconnected nature of atmospheric stability and turbulence, highlighted by Richardson number analysis, further emphasizes the importance of understanding turbulence patterns for accurate MLH predictions. • HYSPLIT-Reanalysis model consistently underestimates the mixing layer height. • Models underestimate mixing layer height during summer and overestimate in winter. • GFS and GDAS overestimate global radiation after noon but underestimate MLH. • During anticyclonic situations, the mixing layer is underestimated in models. • During cyclonic situations, the models' results depended on the situation.