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Water vapour plays a crucial role in the global radiation budget and energy transport mechanisms in the atmosphere (Ferrare et al., 2000). It contributes to microphysical processes that lead to the formation and development of clouds, and it influences the size, shape, and chemical composition of aerosol particles (Reichardt et al., 1996). Being integral to the water cycle, it is the primary absorber of infrared radiation, making it the most significant natural greenhouse gas (Prtner et al., 2022). However, monitoring water vapour is a difficult task due to its high temporal and spatial variability. The Raman lidar technique provides water vapour profiles with high spatial and temporal resolution, using the ratio of rotationalvibrational Raman scattering intensities from water vapour (signal at 408 nm) and nitrogen molecules (signal at 387 nm). In this research, we employed simultaneous and co-located radiosonde data to calibrate water vapour measurements acquired by a Raman lidar system operated at the ACTRIS AGORA station (37.16N, 3.60W, 680 m above sea level (asl)) in the city of Granada, in Southern Spain. Water vapour observations from a Raman lidar are analysed over a period of 18 years. Different calibration approaches have been evaluated to determine the optimal calibration constant for the lidar measurements. The first approach involves calculations of a calibration constant (K) as the ratio between the water vapour mixing ratio profiles obtained from radiosonde and the uncalibrated profiles from the Raman lidar. To achieve this, we selected a layer where the water vapour mixing ratio provides a robust response and calculated mean values. The second method employs calibration through linear regressions to determine the optimal least squares fits (Navas-Guzmn et al., 2014). The obtained calibration constants have been applied to retrieve the water vapour profiles from the Raman lidar system over Granada during the study period (2005-2022). A comprehensive statistical analysis was undertaken to delineate the vertical distribution of water vapour over the Granada area. Mean inter-annual and seasonal profiles were derived for this extensive timeframe. Trend analysis was employed to assess the long-term tendencies of water vapour in the lower troposphere. Additionally, the integrated profiles from the lidar were compared with the Integrated Water Vapour (IWV) obtained from various passive and active remote sensing techniques, including microwave radiometer (MWR), Sun photometer, and ground-based GNSS (Global Navigation Satellite System) stations. References Ferrare, R., et al. (2000). J.Geophys.Res.Atmos, 105.D8, 9917-9933. Navas-Guzmn, F. et al., (2014),Atmos.Meas.Tech,7(5), 1201-1211. Prtner, Hans-O., et al., IPCC 2022. Reichardt, J., et al., (1996), Optical Engineering, 35(5), 1457-1465.
Díaz-Zurita et al. (Fri,) studied this question.