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To validate the iCOR atmospheric correction algorithm applied to the Sentinel-3 Ocean and Land Color Instrument (OLCI), Top-of-Atmosphere (TOA) observations over land, globally retrieved Aerosol Optical Thickness (AOT), Top-of-Canopy (TOC) reflectance, and Vegetation Indices (VIs) were intercompared with (i) AERONET AOT and AERONET-based TOC reflectance simulations, (ii) RadCalNet surface reflectance observations, and (iii) SYN Level 2 (L2) AOT, TOC reflectance, and VIs. The results reveal that, overall, iCOR's statistical and temporal consistency is high. iCOR AOT retrievals overestimate relative to AERONET, but less than SYN L2. iCOR and SYN L2 TOC reflectances exhibit a negative bias of ~−0.01 and −0.02, respectively, in the Blue bands compared to the simulations. This diminishes for RED and NIR, except for a +0.02 bias for SYN L2 in the NIR. The intercomparison with RadCalNet shows relative differences < ±6%, except for bands Oa02 (Blue) and Oa21 (NIR), which is likely related to the reported OLCI "excess of brightness". The intercomparison between iCOR and SYN L2 showed R2 = 0.80–0.93 and R2 = 0.92–0.96 for TOC reflectance and VIs, respectively. iCOR's higher temporal smoothness compared to SYN L2 does not propagate into a significantly higher smoothness for TOC reflectance and VIs. Altogether, we conclude that iCOR is well suitable to retrieve statistically and temporally consistent AOT, TOC reflectance, and VIs over land surfaces from Sentinel-3/OLCI observations. [ABSTRACT FROM AUTHOR]

The aim of Copernicus Climate Change Service (C3S) is to supply reliable climate data in support of strategies to adaptation and mitigation to climate change. The C3S provides access to high-quality climate data through its Climate Data Records (CDRs) of atmospheric, marine and land Essential Climate Variables (ECVs). Global Earth Surface Albedo (SA) satellite-based products are included in the land (biosphere) portfolio. SA is a magnitude which quantifies the fraction of solar energy reflected by the surface of the Earth. This paper details the retrieval methodology and preliminary validation results for global estimates of surface albedo based on Sentinel-3 observations for the C3S ECVs data (C3S SA v3.0). The retrieval algorithm exploits the synergistic use of the Ocean and Land Colour Instrument (OLCI) and the Sea and Land Surface Temperature Radiometer (SLSTR) on-board Sentinel-3 A and B satellites. Firstly, the atmospherically corrected reflectances are generated in the Copernicus Global Land Service framework. After that, the Bidirectional Reflectance Distribution Function (BRDF) inversion module concludes the BRDF model parameters, which are transferred to the angular integration module in order to generate spectral albedo quantities for the selected OLCI (Oa03, Oa04, Oa07, Oa17 and Oa21) and SLSTR (S1, S2, S5 and S6) bands. At the end, the spectral integration module generates broadband albedo quantities in three different standard broadband spectral regions (visible [0.4μ m − 0.7μ m ], near infrared [0.7μ m − 4μ m ] and total shortwave [0.3μ m − 4μ m ]). Preliminary validation results over 10-months demonstration period (July 2018–April 2019) show, in terms of spatial and temporal consistency, that C3S Sentinel-3 SA global estimates reached in general good agreement as compared to other satellite operational references derived from MODIS (MCD43A3 C6) and PROBA-V (C3S PROBA-V SA v1.0) acquisitions. The comparison with ground data shows similar results to the MCD43A3 C6 comparisons but opposite sign in differences (marginally positive in case of Sentinel-3), with accuracy of 0.005 (3.7%), precision of 0.016 (11.3%) and uncertainty of 0.032 (22.7%). Our results have demonstrated the feasibility to estimate global fields of SA from Sentinel-3 observations, with similar quality of existing operational products. These Sentinel-3 based SA datasets will give the continuity to the existing C3S SA CDR, introducing improvements in terms of spatial resolution (300 m) and spectral information (9 spectral albedos) in contrast to previous datasets based on Advanced Very High Resolution Radiometer (AVHRR; 4 km, 4 channels) and Vegetation instruments (VGT; 1 km, 4 channels). • Retrieval method for global surface albedo estimates from Sentinel-3 is proposed. • Algorithm is based on BRDF inversion, angular and spectral integration. • A cross-comparison with MODIS and PROBA-V satellite products is performed. • The direct validation includes comparison with spatially representative ground data. [ABSTRACT FROM AUTHOR]