| 06 Mar 2025
Water Vapor Content Retrieval Under Cloudy Sky Conditions from SWIR Satellite Measurements in the Context of C3IEL 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. Water vapor plays a crucial role in cloud formation and development, particularly those 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 (LES) and numerical weather forecasting models. The developed algorithm is part of the Cluster for Cloud evolution, ClImatE and Lightning, C3IEL space mission project. This mission, scheduled for early 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 is achieved through 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 SWIR 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 (RMSE) 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.
This paper addresses the long standing (and still of paramount importance) topic of convective cloud formation/development and the surrounding water vapour (WV) conditions that lead to it.
The problem of WV retrieval above clouds, although attempted in the literature (as mentioned by the authors), remains very appealing and very topical nowadays, because no systematic/operational retrieval exists at the moment in Meteorological agencies. The dedicated WV imager on the C3IL mission will cover this gap, allowing a 3-year long coverage.
The problem of WV retrieval above clouds is successfully addressed by proposing an optimal estimation approach, using SWIR imaging measurements in 3 relevant channels (covering the spectral range from ~1 to 1.3µm) in and off the water vapour absorption band and taking into account the relevant factors affecting (together with the water vapour profile) the observed radiances in these channels, i.e., the surface properties such as albedo and the cloud optical thickness (COT) and height).
The retrieval approach is motivated based on previous works conducted with POLDER and MERIS data and demonstrated using appropriate simulated data, and test retrieval using both idealized and realistic atmospheric profiles. The results are convincing (i.e., the proposed algorithm is clearly sensitive to the water vapour amount above clouds and its quantification is reliable within well motivated uncertainty (i.e. impact of realistic cloud profiles, of high COT, of low WV content, etc.).
Although demonstrated on simulated data only, the method opens interesting perspectives for the 3-years limited C3IL mission, and maybe for possible longer future satellite missions equipped with the same channels as the C3IL/WV imager.
All this considered, I have no doubt in recommending the publication of this paper after minor revision. In the attached PDF, I added all my comments to the text. Most of them are typos corrections or request for clarifications (e.g., clarify in abstract/conclusion that the proposed algorithm is demonstrated only over ocean and excludes latitudes higher the ±60 deg). However, I also added suggestions and comments that in my opinion may further improve the quality of this work (e.g., future work using real profiles and 3D cloud reconstruction from EarthCARE). The authors shall go through them, providing feedback where required.