Articles | Volume 10, issue 12
https://doi.org/10.5194/amt-10-4905-2017
https://doi.org/10.5194/amt-10-4905-2017
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

Related authors

Measurement report: Ammonia in Paris derived from ground-based open-path and satellite observations
Camille Viatte, Nadir Guendouz, Clarisse Dufaux, Arjan Hensen, Daan Swart, Martin Van Damme, Lieven Clarisse, Pierre Coheur, and Cathy Clerbaux
Atmos. Chem. Phys., 23, 15253–15267, https://doi.org/10.5194/acp-23-15253-2023,https://doi.org/10.5194/acp-23-15253-2023, 2023
Short summary
Insights on the spatial distribution of global, national and sub-national GHG emissions in EDGARv8.0
Monica Crippa, Diego Guizzardi, Federico Pagani, Marcello Schiavina, Michele Melchiorri, Enrico Pisoni, Francesco Graziosi, Marilena Muntean, Joachim Maes, Lewis Dijkstra, Martin Van Damme, Lieven Clarisse, and Pierre Coheur
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-514,https://doi.org/10.5194/essd-2023-514, 2023
Revised manuscript accepted for ESSD
Short summary
The IASI NH3 version 4 product: averaging kernels and improved consistency
Lieven Clarisse, Bruno Franco, Martin Van Damme, Tommaso Di Gioacchino, Juliette Hadji-Lazaro, Simon Whitburn, Lara Noppen, Daniel Hurtmans, Cathy Clerbaux, and Pierre Coheur
Atmos. Meas. Tech., 16, 5009–5028, https://doi.org/10.5194/amt-16-5009-2023,https://doi.org/10.5194/amt-16-5009-2023, 2023
Short summary
Bridging the spatial gaps of the Ammonia Monitoring Network using satellite ammonia measurements
Rui Wang, Da Pan, Xuehui Guo, Kang Sun, Lieven Clarisse, Martin Van Damme, Pierre-François Coheur, Cathy Clerbaux, Melissa Puchalski, and Mark A. Zondlo
Atmos. Chem. Phys., 23, 13217–13234, https://doi.org/10.5194/acp-23-13217-2023,https://doi.org/10.5194/acp-23-13217-2023, 2023
Short summary
A roadmap to estimating agricultural ammonia volatilization over Europe using satellite observations and simulation data
Rimal Abeed, Camille Viatte, William C. Porter, Nikolaos Evangeliou, Cathy Clerbaux, Lieven Clarisse, Martin Van Damme, Pierre-François Coheur, and Sarah Safieddine
Atmos. Chem. Phys., 23, 12505–12523, https://doi.org/10.5194/acp-23-12505-2023,https://doi.org/10.5194/acp-23-12505-2023, 2023
Short summary

Related subject area

Subject: Gases | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
Greenhouse gas retrievals for the CO2M mission using the FOCAL method: first performance estimates
Stefan Noël, Michael Buchwitz, Michael Hilker, Maximilian Reuter, Michael Weimer, Heinrich Bovensmann, John P. Burrows, Hartmut Bösch, and Ruediger Lang
Atmos. Meas. Tech., 17, 2317–2334, https://doi.org/10.5194/amt-17-2317-2024,https://doi.org/10.5194/amt-17-2317-2024, 2024
Short summary
Quantitative imaging of carbon dioxide plumes using a ground-based shortwave infrared spectral camera
Marvin Knapp, Ralph Kleinschek, Sanam N. Vardag, Felix Külheim, Helge Haveresch, Moritz Sindram, Tim Siegel, Bruno Burger, and André Butz
Atmos. Meas. Tech., 17, 2257–2275, https://doi.org/10.5194/amt-17-2257-2024,https://doi.org/10.5194/amt-17-2257-2024, 2024
Short summary
The transition to new ozone absorption cross sections for Dobson and Brewer total ozone measurements
Karl Voglmeier, Voltaire A. Velazco, Luca Egli, Julian Gröbner, Alberto Redondas, and Wolfgang Steinbrecht
Atmos. Meas. Tech., 17, 2277–2294, https://doi.org/10.5194/amt-17-2277-2024,https://doi.org/10.5194/amt-17-2277-2024, 2024
Short summary
Advantages of assimilating multispectral satellite retrievals of atmospheric composition: a demonstration using MOPITT carbon monoxide products
Wenfu Tang, Benjamin Gaubert, Louisa Emmons, Daniel Ziskin, Debbie Mao, David Edwards, Avelino Arellano, Kevin Raeder, Jeffrey Anderson, and Helen Worden
Atmos. Meas. Tech., 17, 1941–1963, https://doi.org/10.5194/amt-17-1941-2024,https://doi.org/10.5194/amt-17-1941-2024, 2024
Short summary
An improved OMI ozone profile research product version 2.0 with collection 4 L1b data and algorithm updates
Juseon Bak, Xiong Liu, Kai Yang, Gonzalo Gonzalez Abad, Ewan O'Sullivan, Kelly Chance, and Cheol-Hee Kim
Atmos. Meas. Tech., 17, 1891–1911, https://doi.org/10.5194/amt-17-1891-2024,https://doi.org/10.5194/amt-17-1891-2024, 2024
Short summary

Cited articles

AERIS database, http://iasi.aeris-data.fr/NH3/, last access: 8 December 2017.
August, T., Klaes, D., Schlüssel, P., Hultberg, T., Crapeau, M., Arriaga, A., O'Carroll, A., Coppens, D., Munro, R., and Calbet, X.: IASI on Metop-A: Operational Level 2 retrievals after five years in orbit, J. Quant. Spectrosc. Ra., 113, 1340–1371, https://doi.org/10.1016/j.jqsrt.2012.02.028, 2012.
Bauduin, S., Clarisse, L., Hadji-Lazaro, J., Theys, N., Clerbaux, C., and Coheur, P.-F.: Retrieval of near-surface sulfur dioxide (SO2) concentrations at a global scale using IASI satellite observations, Atmos. Meas. Tech., 9, 721–740, https://doi.org/10.5194/amt-9-721-2016, 2016.
Bauduin, S., Clarisse, L., Theunissen, M., George, M., Hurtmans, D., Clerbaux, C., and Coheur, P.-F.: IASI's sensitivity to near-surface carbon monoxide (CO): Theoretical analyses and retrievals on test cases, J. Quant. Spectrosc. Ra., 189, 428–440, https://doi.org/10.1016/j.jqsrt.2016.12.022, 2017.
Beer, R., Shephard, M. W., Kulawik, S. S., Clough, S. A., Eldering, A., Bowman, K. W., Sander, S. P., Fisher, B. M., Payne, V. H., Luo, M., Osterman, G. B., and Worden, J. R.: First satellite observations of lower tropospheric ammonia and methanol, Geophys. Res. Lett., 35, L09801,https://doi.org/10.1029/2008GL033642, 2008.
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.