Articles | Volume 13, issue 2
https://doi.org/10.5194/amt-13-985-2020
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, Jian Xu, Klaus-Peter Heue, and Walter Zimmer

Viewed

Total article views: 6,139 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
4,748 1,311 80 6,139 84 62
  • HTML: 4,748
  • PDF: 1,311
  • XML: 80
  • Total: 6,139
  • BibTeX: 84
  • EndNote: 62
Views and downloads (calculated since 17 Apr 2019)
Cumulative views and downloads (calculated since 17 Apr 2019)

Viewed (geographical distribution)

Total article views: 6,139 (including HTML, PDF, and XML) Thereof 5,530 with geography defined and 609 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 15 Jan 2025
Download
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.