Alraddawi et al. (2026) Pseudo-Monthly Raman Lidar Dataset for Reference Water Vapor Observations in the UTLS

Identification

• Journal: Remote Sensing
• Year: 2026
• Date: 2026-04-12
• Authors: Dunya Alraddawi, Philippe Keckhut, G. Payen, Jean-Luc Baray, Florian Mandija, Abdanour Irbah, Alain Sarkissian, M. Sicard, A. Hauchecorne, Hélène Vérèmes
• DOI: 10.3390/rs18081144

Research Groups

• Laboratoire Atmosphere et Observations Spatiales (LATMOS/IPSL), UVSQ Université Paris-Saclay, Sorbonne Université, Centre National de Recherche Scientifique (CNRS), Guyancourt, France
• Observatoire des Sciences de l’Univers de La Réunion (OSU-Réunion), UAR 3365, Université de La Réunion, Centre National de Recherche Scientifique (CNRS), Météo-France, IRD, Saint-Denis, France
• Observatoire de Physique de Globe de Clermont (OPGC), UAR 833, Centre National de Recherche Scientifique (CNRS), Université Clermont Auvergne, Clermont-Ferrand, France
• Laboratoire de Météorologie Physique (LaMP), UMR 6016, Centre National de Recherche Scientifique (CNRS), Université Clermont Auvergne, Clermont-Ferrand, France
• Laboratoire de l’Atmosphère et des Cyclones (LACy), Météo-France, Université de la Réunion, Centre National de Recherche Scientifique (CNRS), Saint Denis, France
• Department of Signal Theory and Communications, Universitat Politècnica de Catalunya, Barcelona, Spain

Short Summary

This study evaluates 11 years of pseudo-monthly water vapor mixing ratio (WVMR) profiles from a UV Raman lidar at Réunion Island against MLS-Aura, ERA5, and GRUAN radiosondes, revealing systematic dry biases in MLS and GRUAN relative to the lidar, while ERA5 shows better agreement and is proposed for an alternative lidar calibration.

Objective

• To assess the reliability of multi-source water vapor datasets (Raman lidar, MLS-Aura, ERA5, GRUAN radiosondes) in the subtropical upper troposphere (UT) and evaluate the Li1200 lidar dataset, particularly using a pseudo-monthly averaging approach.

Study Configuration

• Spatial Scale: Subtropical region over Réunion Island (21°S, 55.4°E), specifically Maïdo Observatory (2160 m above sea level) and Saint-Denis (20.9°S, 55.5°E, 46 m above sea level). Vertical range from the surface up to 16 km in the upper troposphere and lower stratosphere (UTLS).
• Temporal Scale: 11 years (2013–2023) for lidar, MLS, and ERA5 data; 4 years (2019–2023) for GRUAN-processed radiosonde data. Data are aggregated into pseudo-monthly averages of nighttime measurements.

Methodology and Data

• Models used: ERA5 (ECMWF fifth-generation reanalysis)
• Data sources:
  • Ground-based UV Raman lidar (Li1200) at Maïdo Observatory, Réunion Island.
  • Microwave Limb Sounder (MLS) aboard NASA’s Aura satellite (Version 5, Level 2 Geophysical Product).
  • GRUAN-processed Meteomodem M10 radiosondes launched from Gillot meteorological station (Saint-Denis).
  • GNSS-integrated water vapor (IWV) measurements from a TRIMBLE-NETR9 receiver at Maïdo Observatory for conventional lidar calibration.
  • Collocated meteorological station data (surface pressure and temperature) for IWV conversion.

Main Results

• Pseudo-monthly lidar averages successfully extended water vapor mixing ratio (WVMR) profiles up to 16 km, improving the signal-to-noise ratio and temporal representativeness.
• MLS-Aura satellite retrievals consistently showed a dry shift of up to 30% relative to the lidar above 12 km, with this bias being more pronounced during the wet season.
• The operational Li1200 lidar dataset exhibited a small dry shift (approximately 5% lower) compared to ERA5 throughout the UT, with deviations reaching up to 10% drier during the dry season.
• GRUAN-processed M10 radiosondes displayed a substantial dry shift relative to the lidar, exceeding 30% above 12 km, while below 12 km, lidar measurements were slightly drier (5–10%).
• An alternative lidar calibration method, utilizing ERA5 WVMR in the 4–6 km altitude range, revealed a clear dry shift in ERA5 relative to the newly calibrated lidar dataset, increasing with altitude up to 25% in the UT.
• The alternative calibration also showed the new lidar dataset to be wetter than GRUAN-processed M10 radiosondes across almost all UT altitudes, with differences up to 20% below 13 km and exceeding 40% at higher altitudes.
• Radiosonde drift, which can extend up to 100 km from the launch site, did not significantly affect the relative shift between radiosonde and lidar measurements above 13 km.

Contributions

• Developed and applied a pseudo-monthly averaging approach for Raman lidar data, extending water vapor mixing ratio (WVMR) profiles up to 16 km in the subtropical upper troposphere, thereby maximizing data utility for long-term studies.
• Provided the first multi-year (11 years) comparative evaluation of lidar, MLS-Aura, ERA5, and GRUAN-processed M10 radiosonde WVMR profiles over a subtropical site (Réunion Island).
• Identified systematic dry biases in MLS-Aura (up to 30%) and GRUAN-processed M10 radiosondes (exceeding 30%) relative to lidar in the upper troposphere.
• Proposed and evaluated an alternative lidar calibration method using ERA5 reanalysis, which improves lidar estimates in the upper troposphere and reveals a dry shift in ERA5 (up to 25%) relative to the newly calibrated lidar.
• Enhanced the quality and consistency of Raman lidar water vapor observations, contributing to global efforts to monitor and validate tropical and subtropical upper tropospheric humidity.

Funding

• Horizon Europe Research and Innovation Actions program (Grant Agreement N◦101056885) through the BeCoM (Better Contrail Mitigation) project.
• French government (BPI) in the frame of France 2030 (Grant DOS0182433/00) for the CONTRAILS project.
• European Union (grant agreement No 101086690).
• COST Action EARLICOST (CA24135).
• ANR through the OBS4CLIM project (ANR-21-ESRE-0013).
• CNES through the projects EarthCARE, AOS, and EXTRASAT.
• OPAR (Observatoire de Physique de l’Atmosphère à la Réunion).
• OSU-Réunion (Observatoire des Sciences de l’Univers à La Réunion, UAR 3365), funded by CNRS (INSU), Météo-France, and Université de La Reunion.

Citation

@article{Alraddawi2026PseudoMonthly,
  author = {Alraddawi, Dunya and Keckhut, Philippe and Payen, G. and Baray, Jean-Luc and Mandija, Florian and Irbah, Abdanour and Sarkissian, Alain and Sicard, M. and Hauchecorne, A. and Vérèmes, Hélène},
  title = {Pseudo-Monthly Raman Lidar Dataset for Reference Water Vapor Observations in the UTLS},
  journal = {Remote Sensing},
  year = {2026},
  doi = {10.3390/rs18081144},
  url = {https://doi.org/10.3390/rs18081144}
}