3D cloud reconstruction from all-sky camera images for the analysis of their impact on sky radiances and retrieved aerosol properties

Atmospheric aerosols influence the Earth’s energy balance through direct (aerosol-radiation) and indirect (aerosol-clouds) effects. Aerosol properties are very variable in space, time and type. An accurate knowledge of the microphysical and optical properties is key to assess their impact on climate. The sky radiances contain information about the aerosol properties and are commonly used in inversion algorithms to retrieve them, like the one from AERONET (Sinyuk et al., 2020). However, the inversion algorithms commonly used employ a RTM which only considers cloud-free conditions. Therefore, the input measurements used for the inversion algorithm are previously filtered using a cloud-screening to remove sky radiances at points where clouds are located.

However, the synthetic study conducted by Herrero-Anta et al. (2025) showed that even the points which are not removed by the cloud-screening are affected by the presence of clouds, showing an enhancement in the sky radiances with respect to the cloud-free situation. When the enhanced sky radiances are used as input for an inversion algorithm, a bias is observed in the aerosol properties with respect to the aerosol properties retrieved under cloud-free conditions.

To evaluate this effect in real conditions, a new methodology has been proposed to reconstruct clouds in 3D using images from all-sky cameras. For this study, we have used data from a camera installed in Valladolid, where a CE318-T sun photometer from AERONET is co-located.

Once the 3D cloud maps are obtained, they have been used as input for the radiative transfer model MYSTIC (Emde et al., 2016) to simulate the sky radiances under cloudy and cloud-free conditions, to calculate the enhancement. This enhancement has been used to correct the sky radiance measurements from the CE318-T and retrieve the corrected aerosol properties using GRASP (Generalized Retrieval of Atmosphere and Surface Properties; Dubovik et al., 2021).

 

This work was supported by Ministerio de Ciencia e Innovación (MICINN), with the grant no. PID2024-157697OB-I00. This work is part of the project TED2021-131211B-I00375 funded by MCIN/AEI/10.13039/501100011033 and European Union, “NextGenerationEU”/PRTR and is based on work from COST Action CA21119 HARMONIA. Financial support of the Department of Education, Junta de Castilla y León, and FEDER Funds is gratefully acknowledged (Reference: CLU-2023-1-05). This work was funded by European Comision through the EUBURN-RISK project (INTERREG-SUDOE; S2/2.4/F0327). The authors acknowledge support of the Spanish Ministry for Science and Innovation to ACTRIS ERIC and the Marie Sklodowska-Curie Staff Exchange Actions with the project GRASP-SYNERGY (grant no. 10101131631).

Dubovik, Oleg, et al. "A comprehensive description of multi-term LSM for applying multiple a priori constraints in problems of atmospheric remote sensing: GRASP algorithm, concept, and applications." Frontiers in Remote Sensing 2 (2021): 706851. Emde, Claudia, et al. "The libRadtran software package for radiative transfer calculations (version 2.0. 1)." Geoscientific Model Development 9.5 (2016): 1647-1672. Herrero-Anta, Sara, et al. "Impact of cloud presence on sky radiances and the retrieval of aerosol properties." Atmospheric Research 317 (2025): 107938.  Sinyuk, Alexander, et al. "The AERONET Version 3 aerosol retrieval algorithm, associated uncertainties and comparisons to Version 2." Atmospheric Measurement Techniques 13.6 (2020): 3375-3411.