Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Aerosol Optical Thickness Retrieval in Presence of Cloud: Application to S3A/SLSTR Observations

Version 1 : Received: 30 March 2022 / Approved: 31 March 2022 / Online: 31 March 2022 (11:47:56 CEST)

A peer-reviewed article of this Preprint also exists.

Luffarelli, M.; Govaerts, Y.; Franceschini, L. Aerosol Optical Thickness Retrieval in Presence of Cloud: Application to S3A/SLSTR Observations. Atmosphere 2022, 13, 691. Luffarelli, M.; Govaerts, Y.; Franceschini, L. Aerosol Optical Thickness Retrieval in Presence of Cloud: Application to S3A/SLSTR Observations. Atmosphere 2022, 13, 691.

Journal reference: Atmosphere 2022, 13, 691
DOI: 10.3390/atmos13050691

Abstract

The Combined Inversion of Surface and AeRosols (CISAR) algorithm for the joint retrieval of surface and aerosol single scattering properties has been further developed in order to extend the retrieval to clouds and overcome the need for an external cloud mask. Pixels located in the transition zone between pure cloud and pure aerosol are often discarded by both aerosol and cloud algorithms, despite being essential for studying aerosol-cloud interactions, which still represent the largest source of uncertainty in climate predictions. The proposed approach aims at filling this gap and deepening the understanding of aerosol properties in cloudy environments. The new CISAR version is applied to Sentinel-3A/SLSTR observations and evaluated against different satellite products and ground measurements. The spatial coverage is greatly improved with respect to algorithms processing only pixels flagged as clear sky by the SLSTR cloud mask. The continuous retrieval of aerosol properties without any safety zone around clouds opens new possibilities for studying aerosol properties in cloudy environments.

Keywords

aerosols; clouds; inversion; optimal estimation

Subject

EARTH SCIENCES, Atmospheric Science

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