Calibration of water vapour Raman lidar using GNSS precipitable water vapour and reanalysis model data

Water vapour is a crucial and highly variable greenhouse gas in the Earth's atmosphere, which can significantly influence radiative balance, energy transport, and photochemical processes. It can also affect the radiative budget indirectly through cloud formation and by altering the size, shape, and chemical composition of aerosol particles. Accurate and systematic observations are essential for understanding its impacts and improving climate projections. Raman lidar technique is widely used for obtaining water vapour mixing ratio (WVMR) profiles with high vertical and temporal resolution. It relies on Raman scattering from water vapour and nitrogen molecules and is usually calibrated by reference to one or more external measurements of water vapour.

This study presents a hybrid methodology for obtaining high temporal resolution calibration constants for Raman lidar measurements, and posteriorly retrieves high accuracy WVMR profiles. It combines correlative measurements of precipitable water vapour (PWV) for calibrating lidar measurements with Numerical Weather Prediction (NWP) data to reconstruct the profile within the incomplete lidar overlap region. This methodology is applied to the MULHACEN Raman lidar system, operational at UGR station of the University of Granada (Spain) for the long period of 2009-2022. The hybrid method was optimized for the station by selecting Global Navigation Satellite System (GNSS) PWV data as the most appropriate due to its better agreement with correlative radiosondes (R² of 0.95). Furthermore, the ERA5 model was selected as the most appropriate for reconstructing the incomplete lidar overlap region due to its better temporal and spatial resolution and its accuracy when evaluated against radiosonde data. The advantages of the hybrid calibration methodology are evaluated compared to traditional radiosonde-based methods or PWV data assuming a constant WVMR in the incomplete overlap region. Although all methods generally provide good calibration constants, the hybrid approach presented the best performance, as quantified by an R² of 0.85, a slope of 0.97, and an intercept of -0.05 g/kg, particularly under conditions where atmospheric layers are not well-mixed. Comparison with radiosonde data revealed excellent agreement, with a mean bias error of -0.11 ± 0.38 g/kg and a standard deviation of 1.04 ± 0.35 g/kg across the entire period and vertical range (0 – 6.0 km agl). The most important result of this study is the ability to continuously evaluate calibration constants during 14 years of MULHACEN operation. The posterior application of the hybrid methodology to all MULHACEN measurements enabled the generation of a comprehensive long time database of WVMR profiles.