Articles | Volume 13, issue 2
Atmos. Meas. Tech., 13, 985–999, 2020
https://doi.org/10.5194/amt-13-985-2020
Atmos. Meas. Tech., 13, 985–999, 2020
https://doi.org/10.5194/amt-13-985-2020

Research article 02 Mar 2020

Research article | 02 Mar 2020

Applying FP_ILM to the retrieval of geometry-dependent effective Lambertian equivalent reflectivity (GE_LER) daily maps from UVN satellite measurements

Diego G. Loyola et al.

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Cited articles

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In this paper we present a novel algorithm for the retrieval of geometry-dependent effective Lambertian equivalent reflectivity (GE_LER) from UVN sensors based on the full-physics inverse learning machine (FP_ILM) retrieval. The GE_LER retrieval is optimized for the trace gas retrievals using the DOAS technique and the large amount of data of TROPOMI on board the EU/ESA Sentinel-5 Precursor mission.