New Publication: Hybrid methodology for optimised water vapour mixing ratio profiles from Raman lidar measurements
EARLICOST is pleased to highlight a recent publication in Atmospheric Measurement Techniques:
“Hybrid methodology for optimised water vapour mixing ratio profiles from Raman lidar measurements”
Water vapour is one of the most important constituents of the Earth’s atmosphere, playing a crucial role in atmospheric thermodynamics, cloud formation, radiative processes, and climate variability. Accurate and continuous observations are essential for improving our understanding of atmospheric processes and future climate projections.
The study presents a hybrid methodology for retrieving high-quality water vapour mixing ratio profiles from Raman lidar measurements. The proposed approach combines Raman lidar observations with GNSS-derived precipitable water vapour data and numerical weather prediction and reanalysis data.
Applied to 14 years of measurements (2009–2022) from the EARLINET/ACTRIS Granada station, the methodology significantly expanded the available calibration dataset, increasing it from only 31 radiosonde-based calibration cases to more than 2,000 calibration values. This enabled the development of a comprehensive long-term database of water vapour mixing ratio profiles.
The work demonstrates the importance of advanced lidar methodologies for atmospheric monitoring, climate research, and the development of long-term observational datasets.
We congratulate Arlett Díaz-Zurita and all co-authors on this valuable contribution to the atmospheric remote sensing community.
Publication:
Díaz-Zurita, A., Pérez-Ramírez, D., Whiteman, D. N., Rodríguez-Navarro, O., Naval-Hernández, V. M., Muñiz-Rosado, J., Fernández-Carvelo, S., Abril-Gago, J., del Águila, A., Ortiz-Amezcua, P., Bravo-Aranda, J. A., Granados-Muñoz, M. J., Guerrero-Rascado, J. L., Antón, M., Vaquero-Martínez, J., Foyo-Moreno, I., Benavent-Oltra, J. A., Alados-Arboledas, L., and Navas-Guzmán, F.: Hybrid methodology for optimised water vapour mixing ratio profiles from Raman lidar measurements, Atmos. Meas. Tech., 19, 3169–3192, https://doi.org/10.5194/amt-19-3169-2026 , 2026.