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.
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.
the Creative Commons Attribution 4.0 License.
Version 2 of the IASI NH3 neural network retrieval algorithm: near-real-time and reanalysed datasets
Martin Van Damme
CORRESPONDING AUTHOR
Université libre de Bruxelles (ULB), Atmospheric Spectroscopy, Service de Chimie Quantique et Photophysique, Brussels, Belgium
Simon Whitburn
Université libre de Bruxelles (ULB), Atmospheric Spectroscopy, Service de Chimie Quantique et Photophysique, Brussels, Belgium
Lieven Clarisse
Université libre de Bruxelles (ULB), Atmospheric Spectroscopy, Service de Chimie Quantique et Photophysique, Brussels, Belgium
Cathy Clerbaux
Université libre de Bruxelles (ULB), Atmospheric Spectroscopy, Service de Chimie Quantique et Photophysique, Brussels, Belgium
LATMOS/IPSL, UPMC Univ. Paris 06 Sorbonne Universités, UVSQ, CNRS, Paris, France
Daniel Hurtmans
Université libre de Bruxelles (ULB), Atmospheric Spectroscopy, Service de Chimie Quantique et Photophysique, Brussels, Belgium
Pierre-François Coheur
Université libre de Bruxelles (ULB), Atmospheric Spectroscopy, Service de Chimie Quantique et Photophysique, Brussels, Belgium
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- The Diel Cycle of NH3 Observed From the FY‐4A Geostationary Interferometric Infrared Sounder (GIIRS) L. Clarisse et al. 10.1029/2021GL093010
- A General Framework for Global Retrievals of Trace Gases From IASI: Application to Methanol, Formic Acid, and PAN B. Franco et al. 10.1029/2018JD029633
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Latest update: 02 Nov 2024
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...