Pseudo-Monthly Raman Lidar Dataset for Reference Water Vapor Observations in the UTLS

Upper troposphere (UT) humidity records are crucial for climate studies. To maximize temporal representativeness and enhance the lidar signal, pseudo-monthly averaging—limited to nighttime measurement—is applied, yielding water vapor mixing ratio (WVMR) profiles up to 16 km. This study evaluates 11 years (2013–2023) of WVMR profiles from a UV Raman lidar (Li1200) at Réunion Island, comparing them with MLS-Aura satellite retrievals, ERA5 reanalysis data, and GRUAN-processed M10 radiosondes. The results reveal a systematic dry shift in MLS of up to 30% above 12 km, particularly during the wet season. The lidar exhibits a slight downward shift in WVMR, approximately 5% lower than ERA5 throughout the UT, with the largest deviations occurring above 14 km and greater variability during the wet season. Calibration-related challenges during the dry season result in lidar WVMR profiles that are up to 10% drier than ERA5. Additionally, comparisons with GRUAN-processed radiosondes show a substantial dry shift relative to the lidar, exceeding 30% above 12 km. We investigate the effect of GNSS-based lidar calibration by applying an alternative calibration method, which produces higher WVMR values. This reveals a dry shift in ERA5 relative to the lidar, increasing with altitude in the UT up to 25%. These measurements contribute to the global effort to monitor and validate tropical and subtropical upper tropospheric humidity.

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Publication Details

Journal
Remote Sensing
Published
2026-04-12
DOI
https://doi.org/10.3390/rs18081144
Primary Topic
Soil Moisture and Remote Sensing
Type
article
Field-Weighted Citation Impact
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article

Pseudo-Monthly Raman Lidar Dataset for Reference Water Vapor Observations in the UTLS

Abdanour Irbah, Hélène Vérèmes, Jean‐Luc Baray, Alain Sarkissian et al.
Remote Sensing
Soil Moisture and Remote Sensing
article

Pseudo-Monthly Raman Lidar Dataset for Reference Water Vapor Observations in the UTLS

Abdanour Irbah, Hélène Vérèmes, Jean‐Luc Baray, Alain Sarkissian, Dunya Alraddawi, G. Payen, Florian Mandija, Philippe Keckhut, M. Sicard, A. Hauchecorne
article en

Abstract

Upper troposphere (UT) humidity records are crucial for climate studies. To maximize temporal representativeness and enhance the lidar signal, pseudo-monthly averaging—limited to nighttime measurement—is applied, yielding water vapor mixing ratio (WVMR) profiles up to 16 km. This study evaluates 11 years (2013–2023) of WVMR profiles from a UV Raman lidar (Li1200) at Réunion Island, comparing them with MLS-Aura satellite retrievals, ERA5 reanalysis data, and GRUAN-processed M10 radiosondes. The results reveal a systematic dry shift in MLS of up to 30% above 12 km, particularly during the wet season. The lidar exhibits a slight downward shift in WVMR, approximately 5% lower than ERA5 throughout the UT, with the largest deviations occurring above 14 km and greater variability during the wet season. Calibration-related challenges during the dry season result in lidar WVMR profiles that are up to 10% drier than ERA5. Additionally, comparisons with GRUAN-processed radiosondes show a substantial dry shift relative to the lidar, exceeding 30% above 12 km. We investigate the effect of GNSS-based lidar calibration by applying an alternative calibration method, which produces higher WVMR values. This reveals a dry shift in ERA5 relative to the lidar, increasing with altitude in the UT up to 25%. These measurements contribute to the global effort to monitor and validate tropical and subtropical upper tropospheric humidity.

Remote SensingVol. 18(8)
Centre National de la Recherche Scientifique (FR), Université de Versailles Saint-Quentin-en-Yvelines (FR), Université Paris-Saclay (FR), Sorbonne Université (FR), Observatoire de Physique du Globe de Clermont-Ferrand (FR), Institut Pierre-Simon Laplace (FR), Laboratoire de l'Atmosphère et des Cyclones (RE), Laboratoire de Météorologie Physique (FR), Laboratoire atmosphères, milieux, observations spatiales (FR), Observatoire des Sciences de l'Univers de la Réunion (RE), Institut de Recherche pour le Développement (FR), Universitat Politècnica de Catalunya (ES)
Climate action
Openalex Percentile: Top 28%
Soil Moisture and Remote Sensing
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