Journal metrics

Journal metrics

  • IF value: 3.248 IF 3.248
  • IF 5-year value: 3.650 IF 5-year 3.650
  • CiteScore value: 3.37 CiteScore 3.37
  • SNIP value: 1.253 SNIP 1.253
  • SJR value: 1.869 SJR 1.869
  • IPP value: 3.29 IPP 3.29
  • h5-index value: 47 h5-index 47
  • Scimago H index value: 60 Scimago H index 60
Volume 10, issue 12 | Copyright
Atmos. Meas. Tech., 10, 4905-4914, 2017
https://doi.org/10.5194/amt-10-4905-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 15 Dec 2017

Research article | 15 Dec 2017

Version 2 of the IASI NH3 neural network retrieval algorithm: near-real-time and reanalysed datasets

Martin Van Damme 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 Martin Van Damme on behalf of the Authors (20 Oct 2017)  Author's response    Manuscript
ED: Publish as is (07 Nov 2017) by Mark Weber
Publications Copernicus
Download
Short summary
This paper presents an improved version (v2.1) of the neural-network-based algorithm for retrieving atmospheric ammonia (NH3) columns from IASI satellite observations. Two datasets using different input data for the retrieval are described: one is based on the operationally provided EUMETSAT Level 2 (ANNI-NH3-v2.1), and the other uses the ECMWF ERA-Interim data (ANNI-NH3-v2.1R-I). Analyses illustrate well that the (meteorological) input data can have a large impact on the retrieved NH3 columns.
This paper presents an improved version (v2.1) of the neural-network-based algorithm for...
Citation
Share