Atmospheric Measurement Techniques
Atmospheric Measurement Techniques
AMT
Articles | Volume 10, issue 12
Articles | Volume 10, issue 12
https://doi.org/10.5194/amt-10-4905-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-10-4905-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 10, issue 12
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, Simon Whitburn, Lieven Clarisse, Cathy Clerbaux, Daniel Hurtmans, and Pierre-François Coheur

Viewed

Total article views: 5,492 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
3,286 2,096 110 5,492 177 175
  • HTML: 3,286
  • PDF: 2,096
  • XML: 110
  • Total: 5,492
  • BibTeX: 177
  • EndNote: 175
Views and downloads (calculated since 04 Aug 2017)
Cumulative views and downloads (calculated since 04 Aug 2017)

Viewed (geographical distribution)

Total article views: 5,492 (including HTML, PDF, and XML) Thereof 5,362 with geography defined and 130 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 25 Nov 2025
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.
Read more
Share