Raman lidar derived WVMR profiles compared to ERA5 - A WaLiNeAs application

Vibrational Raman lidar measurements of the water vapour mixing ratio (WVMR) were conducted during the WaLiNeAs (Water Vapor Lidar Network Assimilation) field campaigns in the western Mediterranean during autumn and winter 2022–2023 and in southwestern France (Toulouse) between June and September 2023. These campaigns, which spanned different seasons and geographical locations, provided an opportunity to sample various meteorological phenomena, including a dry winter, rainstorms, long-range aerosol transport, and an intense heat wave. Consequently, the water vapour content recorded in the lower troposphere showed significant variability during WaLiNeAs, ranging from less than 1 g kg^-1 to more than 17 g kg^-1. For operational purposes, a vertical resolution of 100 m and a temporal resolution between 15 and 60 min have been chosen. These resolutions are aligned with the spatio-temporal resolution of the ERA5 dataset from ECMWF's Integrated Forecasting System (IFS) global numerical weather prediction models. The processing of the lidar data has resulted in a scientific publication explaining the methods used to invert the lidar data and recover various atmospheric parameters. Lidar measurements address a critical gap left by operational instruments, which struggle to capture the diurnal cycle of water vapour from the planetary boundary layer to the lower free troposphere. The primary aim of this study is to compare ERA5 data with lidar-derived WVMR profiles. The results reveal altitude-dependent differences in Pearson correlation coefficient (COR), mean bias (MB), and root mean square deviation (RMSD), particularly during periods of high-water vapour content (> 10 g kg⁻¹). Over all periods the MB ranges from 0.1 to 3 g kg⁻¹, and the RMSD varies between 0.6 and 3.7 g kg⁻¹. COR ranges from 0.16 to 0.94, with lower values observed in the free troposphere during warmer periods. These variations underline the differences in the performance of the reanalysis model over different periods and altitudes when compared to lidar profiles. We show that the reanalysis constantly underestimated the WVMR at all altitudes. This study highlights the importance of scrutinising WVMR and the challenges faced by models during high water vapour meteorological events. The results provide valuable insights into the performance of operational numerical weather prediction models and highlight the need to refine their representation of WVMR vertical profiles in the lower troposphere by incorporating ground-based lidar measurements.

We give special thanks to the ANR grant #ANR-20-CE04-0001 for its contribution to the WaLiNeAs programme, to Meteo-France for its help with the measurements in Toulouse, and to the CNRS INSU national LEFE programme for its financial contribution to this project.