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ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2023
License: CC BY
Data sources: ZENODO
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SEVIRI AOD/COD Product [DUST2MSG]

Authors: Lucio Franceschini; Marta Luffarelli; Yves Govaerts; Simon Pinnock; Jens Loehring;

SEVIRI AOD/COD Product [DUST2MSG]

Abstract

{"references": ["Govaerts and Luffarelli (2018), Joint retrieval of surface reflectance and aerosol properties with continuous variation of the state variables in the solution space \u2013 Part 1: theoretical concept, https://amt.copernicus.org/articles/11/6589/2018/", "Luffarelli and Govaerts (2019), Joint retrieval of surface reflectance and aerosol properties with continuous variation of the state variables in the solution space \u2013 Part 2: application to geostationary and polar-orbiting satellite observations, https://amt.copernicus.org/articles/12/791/2019/", "Luffarelli et al (2022), Aerosol Optical Thickness Retrieval in Presence of Cloud: Application to S3A/SLSTR Observations, https://www.mdpi.com/2073-4433/13/5/691"]}

In the framework of the DUST2MSG ESA project, the CISAR algorithm, originally developed by Rayference for the joint retrieval of surface reflectance, aerosol and cloud single scattering properties, has been applied to SEVIRI observations acquired from both MSG1 and MSG4 from March to August 2020 to obtain a dust product. This Dataset includes hourly atmospheric products. Specification on the filename convention, format and content of the products can be found on the Product User Manual (PUM)

Related Organizations
Keywords

CISAR, DUST2MSG, AOD, DUST, SEVIRI, COD

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