Articles | Volume 13, issue 2
https://doi.org/10.5194/amt-13-985-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-13-985-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
02 Mar 2020
Research article |
| 02 Mar 2020
| 02 Mar 2020
Applying FP_ILM to the retrieval of geometry-dependent effective Lambertian equivalent reflectivity (GE_LER) daily maps from UVN satellite measurements
German Aerospace Center (DLR), Remote Sensing Technology Institute,
Oberpfaffenhofen, 82234 Weßling, Germany
German Aerospace Center (DLR), Remote Sensing Technology Institute,
Oberpfaffenhofen, 82234 Weßling, Germany
Klaus-Peter Heue
German Aerospace Center (DLR), Remote Sensing Technology Institute,
Oberpfaffenhofen, 82234 Weßling, Germany
Walter Zimmer
German Aerospace Center (DLR), Remote Sensing Technology Institute,
Oberpfaffenhofen, 82234 Weßling, Germany
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Latest update: 04 Feb 2025
Short summary
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.
In this paper we present a novel algorithm for the retrieval of geometry-dependent effective...
