Comparative analysis of ERA5 and Raman lidar‐derived moisture profiles in the framework of the WaLiNeAs field campaigns

Abstract Water vapour mixing ratio (WVMR) measurements were performed by three Raman lidars during the WaLiNeAs field campaigns in the western Mediterranean basin. Observations took place along the French Mediterranean coast in autumn and winter 2022–2023, and in southwestern France near Toulouse in summer 2023. These multiseasonal campaigns captured a variety of meteorological phenomena, including a dry winter, rainstorms, long‐range aerosol transport, and a summer heatwave. The measured WVMR varied across the troposphere, ranging from less than 1 g·kg −1 to over 17 g·kg −1 in the planetary boundary layer, and from less than 1 g·kg −1 to approx. 15 g·kg −1 in the free troposphere. Lidar profiles have a vertical resolution of 100 m and a temporal resolution of one hour, matching the spatiotemporal resolution of the European Centre for Medium‐Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA5) model outputs. The primary goal is to compare the ERA5 reanalysis with the lidar‐derived WVMR profiles. Results show altitude‐dependent differences in Pearson correlation coefficient (COR), mean bias (MB), and root‐mean‐squared deviation (RMSD), especially during high WVMR periods (>10 g·kg −1 ). Over all cases, MB ranges from 0.1 to 3 g·kg −1 , and RMSD from 0.6 to 3.7 g·kg −1 . COR values range from 0.16 to 0.94, with the lowest values observed during warm episodes in the free troposphere. The statistical coefficients show the differences in the behaviour of the reanalysis model over different measurement periods and altitude ranges compared to lidar. However, in all cases the reanalysis underestimates the WVMR, whatever the altitude range. This article highlights the challenges faced by models during common meteorological events characterised by significant WVMR amounts. The results provide valuable insights into the performance of operational numerical weather prediction models. It highlights the necessity to refine the representation of the WVMR in the lower troposphere by assimilating ground‐based lidar measurements.