The atmospheric boundary layer (ABL) depth, ziis a fundamental variable of ABL and a climatologically important quantity. The exchange of energy between the Earth’s surface and the atmosphere is governed by turbulent mixing processes in the daytime ABL, and thus, zi is important for scaling turbulence and diffusion in both meteorological and air quality models. A long-term data set of zi was derived at the Site Instrumental de Recherche par Télédétection Atmosphérique (SIRTA) observatory near Paris, using measurements obtained from a ground-based vertically pointing aerosol lidar and an autonomous algorithm STRAT+. Using multiparameter observational data sets covering a 5 year period (October 2008 to September 2013), this study aims to explore two interconnected ABL research topics: brief climatology involving multiscale temporal zi variability (diurnal, seasonal, annual, and interannual) and the relationship between zi and near-surface thermodynamic parameters to determinemeteorological processes governing zi variability. Both the zi and the growth rate over SIRTA showed large seasonal variability with higher mean values in spring (1633m and 225mh_1) and summer (1947m and 247mh–1) than in autumn (1439m and 196mh–1) and winter (1033m and 149mh–1). Seasonal variability of daytime maximumzi is found to be strongly and linearly correlated with downwelling solar radiation at the surface (r = 0.92), while the dependence between daytime maximum zi and sensible heat flux (SHF) at seasonal scales is not fully linear, in particular, for summer months. Interannual variability is studied using deseasonalizedmonthly-mean anomalies of each variable. Conditional sampling and linear regression analyses between the anomalies of deseasonalized SHF and daytime maximum zishow (1) stronger correlation between the two parameters for the soil conditions compared to the wet soil conditions, (2) that zi anomalies were more dependent on SHF anomalies for negative than for positive boundary layer wind speed anomalies, and (3) in the summer season, zi anomalies varied more consistently with SHF anomalies for conditions with negative cloud cover anomalies than in conditions with positive cloud cover anomalies.