Water vapor content retrieval under cloudy sky conditions from SWIR satellite measurements in the context of C <sup>3</sup> IEL space mission project

Abstract. A retrieval algorithm of integrated water vapor content above cloud, using shortwave infrared observations, is developed and evaluated through idealized and realistic atmospheric profiles, with its application currently limited to oceanic regions and latitudes within ±60°. Water vapor plays a crucial role in cloud formation and development, particularly in the formation of clouds resulting from convective processes. The resulting convective cloud locally influences the spatio-temporal variability of atmospheric water vapor content, through exchanges between cloud and its immediate environment. Therefore, a better understanding of the water vapor content above and around clouds is necessary to improve our comprehension of interactions between water vapor and cloud to better constrain Large-Eddy Simulations and numerical weather forecasting models. The algorithm was developed for the Cluster for Cloud evolution, ClImatE and Lightning space mission project. This mission, scheduled for 2028, aims to enhance our knowledge of the 3D convective cloud development velocities, the electrical activity associated with convective systems, and the water vapor content above and around the cloud. The retrieval algorithm presented in this study uses a Bayesian probabilistic approach, the optimal estimation method. The atmosphere is assumed to be composed of homogeneous plane-parallel layers, and synthetic radiance datasets were generated to test the developed retrieval algorithm. The feasibility of retrieving the integrated water vapor content above the cloud over the ocean from shortwave infrared radiances is shown to have, under idealized vertically homogeneous cloud profiles, absolute errors less than 2 kg m−2 for optically thick clouds or when the integrated water vapor content is below 20 kg m−2 and less than 1 kg m−2 for very thick clouds with an optical thickness exceeding 150. Tests using realistic water vapor and cloud extinction profiles that present non-homogeneous vertical distributions show that integrated water vapor content above water type clouds could be retrieved with a Root-Mean-Square Error related to cloud vertical penetration of approximately less than 1 kg m−2 except for optically thin and low-level clouds (cloud optical thickness less than 50 and cloud top height less than 2 km). For very low water vapor content encountered in the presence of high deep convective clouds, the retrieval algorithm tends to systematically overestimate the retrieved water vapor content due to an overestimation of the cloud extinction profile in the upper part of the cloud in the inversion model.

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Publication Details

Journal
Atmospheric measurement techniques
Published
2025-12-04
DOI
https://doi.org/10.5194/amt-18-7369-2025
Primary Topic
Atmospheric aerosols and clouds
Type
article
Field-Weighted Citation Impact
0.00

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article

Water vapor content retrieval under cloudy sky conditions from SWIR satellite measurements in the context of C 3 IEL space mission project

Olivier Pujol, Guillaume Penide, Raphaël Peroni, Charles Cornet et al.
Atmospheric measurement techniques
Atmospheric aerosols and clouds
article

Water vapor content retrieval under cloudy sky conditions from SWIR satellite measurements in the context of C 3 IEL space mission project

Olivier Pujol, Guillaume Penide, Raphaël Peroni, Charles Cornet, Clémence Pierangelo
article en

Abstract

Abstract. A retrieval algorithm of integrated water vapor content above cloud, using shortwave infrared observations, is developed and evaluated through idealized and realistic atmospheric profiles, with its application currently limited to oceanic regions and latitudes within ±60°. Water vapor plays a crucial role in cloud formation and development, particularly in the formation of clouds resulting from convective processes. The resulting convective cloud locally influences the spatio-temporal variability of atmospheric water vapor content, through exchanges between cloud and its immediate environment. Therefore, a better understanding of the water vapor content above and around clouds is necessary to improve our comprehension of interactions between water vapor and cloud to better constrain Large-Eddy Simulations and numerical weather forecasting models. The algorithm was developed for the Cluster for Cloud evolution, ClImatE and Lightning space mission project. This mission, scheduled for 2028, aims to enhance our knowledge of the 3D convective cloud development velocities, the electrical activity associated with convective systems, and the water vapor content above and around the cloud. The retrieval algorithm presented in this study uses a Bayesian probabilistic approach, the optimal estimation method. The atmosphere is assumed to be composed of homogeneous plane-parallel layers, and synthetic radiance datasets were generated to test the developed retrieval algorithm. The feasibility of retrieving the integrated water vapor content above the cloud over the ocean from shortwave infrared radiances is shown to have, under idealized vertically homogeneous cloud profiles, absolute errors less than 2 kg m−2 for optically thick clouds or when the integrated water vapor content is below 20 kg m−2 and less than 1 kg m−2 for very thick clouds with an optical thickness exceeding 150. Tests using realistic water vapor and cloud extinction profiles that present non-homogeneous vertical distributions show that integrated water vapor content above water type clouds could be retrieved with a Root-Mean-Square Error related to cloud vertical penetration of approximately less than 1 kg m−2 except for optically thin and low-level clouds (cloud optical thickness less than 50 and cloud top height less than 2 km). For very low water vapor content encountered in the presence of high deep convective clouds, the retrieval algorithm tends to systematically overestimate the retrieved water vapor content due to an overestimation of the cloud extinction profile in the upper part of the cloud in the inversion model.

Atmospheric measurement techniquesVol. 18(23)
Centre National de la Recherche Scientifique (FR), Université du Québec à Montréal (CA), Institut Universitaire de France (FR), Université de Lille (FR), Centre National d'Études Spatiales (FR), Laboratoire d'Optique Atmosphérique (FR)
Centre National d’Etudes Spatiales
Openalex Percentile: Top 64%
Atmospheric aerosols and clouds
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