Journal cover Journal topic
Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

IF value: 3.668
IF3.668
IF 5-year value: 3.707
IF 5-year
3.707
CiteScore value: 6.3
CiteScore
6.3
SNIP value: 1.383
SNIP1.383
IPP value: 3.75
IPP3.75
SJR value: 1.525
SJR1.525
Scimago H <br class='widget-line-break'>index value: 77
Scimago H
index
77
h5-index value: 49
h5-index49
AMT | Articles | Volume 13, issue 2
Atmos. Meas. Tech., 13, 985–999, 2020
https://doi.org/10.5194/amt-13-985-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Atmos. Meas. Tech., 13, 985–999, 2020
https://doi.org/10.5194/amt-13-985-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

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.

Download

Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Anna Mirena Feist-Polner on behalf of the Authors (27 Nov 2019)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (27 Nov 2019) by Michel Van Roozendael
RR by Anonymous Referee #1 (12 Dec 2019)
RR by Anonymous Referee #2 (13 Dec 2019)
ED: Publish subject to minor revisions (review by editor) (14 Dec 2019) by Michel Van Roozendael
AR by Diego Loyola on behalf of the Authors (19 Dec 2019)  Author's response
ED: Publish as is (14 Jan 2020) by Michel Van Roozendael
Publications Copernicus
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.
In this paper we present a novel algorithm for the retrieval of geometry-dependent effective...
Citation