Articles | Volume 16, issue 12
https://doi.org/10.5194/essd-16-5579-2024
https://doi.org/10.5194/essd-16-5579-2024
Data description paper
 | 
06 Dec 2024
Data description paper |  | 06 Dec 2024

Water vapor Raman lidar observations from multiple sites in the framework of WaLiNeAs

Frédéric Laly, Patrick Chazette, Julien Totems, Jérémy Lagarrigue, Laurent Forges, and Cyrille Flamant

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Cited articles

Ansmann, A., Riebesell, M., Wandinger, U., Weitkamp, C., Voss, E., Lahmann, W., and Michaelis, W.: Combined raman elastic-backscatter LIDAR for vertical profiling of moisture, aerosol extinction, backscatter, and LIDAR ratio, Appl. Phys. B, 55, 18–28, https://doi.org/10.1007/BF00348608, 1992. 
Chazette, P.: The monsoon aerosol extinction properties at Goa during INDOEX as measured with lidar, J. Geophys. Res.-Atmos., 108, 4187, https://doi.org/10.1029/2002jd002074, 2003. 
Chazette, P., Bocquet, M., Royer, P., Winiarek, V., Raut, J. C., Labazuy, P., Gouhier, M., Lardier, M., and Cariou, J. P.: Eyjafjallajökull ash concentrations derived from both lidar and modeling, J. Geophys. Res.-Atmos., 117, D00U14, https://doi.org/10.1029/2011JD015755, 2012a. 
Chazette, P., Dabas, A., Sanak, J., Lardier, M., and Royer, P.: French airborne lidar measurements for Eyjafjallajökull ash plume survey, Atmos. Chem. Phys., 12, 7059–7072, https://doi.org/10.5194/acp-12-7059-2012, 2012b. 
Chazette, P., Marnas, F., and Totems, J.: The mobile Water vapor Aerosol Raman LIdar and its implication in the framework of the HyMeX and ChArMEx programs: application to a dust transport process, Atmos. Meas. Tech., 7, 1629–1647, https://doi.org/10.5194/amt-7-1629-2014, 2014a. 
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Short summary
We present a dataset of water vapor mixing ratio profiles acquired during the Water Vapor Lidar Network Assimilation campaign in fall and winter 2022 and summer 2023, using three lidar systems deployed on the western Mediterranean coastline. This innovative campaign provides access to lower-tropospheric water vapor variability to constrain meteorological forecasting models. The scientific objective is to improve forecasting of heavy-precipation events that lead to flash floods and landslides.
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