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

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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
AR by Martin Van Damme on behalf of the Authors (07 Nov 2017)  Manuscript 
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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.
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