Articles | Volume 8, issue 8
https://doi.org/10.5194/amt-8-3315-2015
https://doi.org/10.5194/amt-8-3315-2015
Research article
 | 
14 Aug 2015
Research article |  | 14 Aug 2015

Retrieval and validation of carbon dioxide, methane and water vapor for the Canary Islands IR-laser occultation experiment

V. Proschek, G. Kirchengast, S. Schweitzer, J. S. A. Brooke, P. F. Bernath, C. B. Thomas, J.-G. Wang, K. A. Tereszchuk, G. González Abad, R. J. Hargreaves, C. A. Beale, J. J. Harrison, P. A. Martin, V. L. Kasyutich, C. Gerbig, O. Kolle, and A. Loescher

Related authors

Comparison study of COSMIC RO dry-air climatologies based on average profile inversion
Julia Danzer, Marc Schwärz, Veronika Proschek, Ulrich Foelsche, and Hans Gleisner
Atmos. Meas. Tech., 11, 4867–4882, https://doi.org/10.5194/amt-11-4867-2018,https://doi.org/10.5194/amt-11-4867-2018, 2018
Short summary
Profiling wind and greenhouse gases by infrared-laser occultation: results from end-to-end simulations in windy air
A. Plach, V. Proschek, and G. Kirchengast
Atmos. Meas. Tech., 8, 2813–2825, https://doi.org/10.5194/amt-8-2813-2015,https://doi.org/10.5194/amt-8-2813-2015, 2015
Short summary

Related subject area

Subject: Gases | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
Predictions of failed satellite retrieval of air quality using machine learning
Edward Malina, Jure Brence, Jennifer Adams, Jovan Tanevski, Sašo Džeroski, Valentin Kantchev, and Kevin W. Bowman
Atmos. Meas. Tech., 18, 1689–1715, https://doi.org/10.5194/amt-18-1689-2025,https://doi.org/10.5194/amt-18-1689-2025, 2025
Short summary
Deep transfer learning method for seasonal TROPOMI XCH4 albedo correction
Alexander C. Bradley, Barbara Dix, Fergus Mackenzie, J. Pepijn Veefkind, and Joost A. de Gouw
Atmos. Meas. Tech., 18, 1675–1687, https://doi.org/10.5194/amt-18-1675-2025,https://doi.org/10.5194/amt-18-1675-2025, 2025
Short summary
Global retrieval of TROPOMI tropospheric HCHO and NO2 columns with improved consistency based on the updated Peking University OMI NO2 algorithm
Yuhang Zhang, Huan Yu, Isabelle De Smedt, Jintai Lin, Nicolas Theys, Michel Van Roozendael, Gaia Pinardi, Steven Compernolle, Ruijing Ni, Fangxuan Ren, Sijie Wang, Lulu Chen, Jos Van Geffen, Mengyao Liu, Alexander M. Cede, Martin Tiefengraber, Alexis Merlaud, Martina M. Friedrich, Andreas Richter, Ankie Piters, Vinod Kumar, Vinayak Sinha, Thomas Wagner, Yongjoo Choi, Hisahiro Takashima, Yugo Kanaya, Hitoshi Irie, Robert Spurr, Wenfu Sun, and Lorenzo Fabris
Atmos. Meas. Tech., 18, 1561–1589, https://doi.org/10.5194/amt-18-1561-2025,https://doi.org/10.5194/amt-18-1561-2025, 2025
Short summary
Quantitative estimate of several sources of uncertainty in drone-based methane emission measurements
Tannaz H. Mohammadloo, Matthew Jones, Bas van de Kerkhof, Kyle Dawson, Brendan J. Smith, Stephen Conley, Abigail Corbett, and Rutger IJzermans
Atmos. Meas. Tech., 18, 1301–1324, https://doi.org/10.5194/amt-18-1301-2025,https://doi.org/10.5194/amt-18-1301-2025, 2025
Short summary
Implementation and application of an improved phase spectrum determination scheme for Fourier transform spectrometry
Frank Hase, Paolo Castracane, Angelika Dehn, Omaira Elena García, David W. T. Griffith, Lukas Heizmann, Nicholas B. Jones, Tomi Karppinen, Rigel Kivi, Martine de Mazière, Justus Notholt, and Mahesh Kumar Sha
Atmos. Meas. Tech., 18, 1257–1267, https://doi.org/10.5194/amt-18-1257-2025,https://doi.org/10.5194/amt-18-1257-2025, 2025
Short summary

Cited articles

Bovensmann, H., Burrows, J. P., Buchwitz, M., Frerick, J., Noël, S., Rozanov, V. V., Chance, K. V., and Goed, A. P. J.: SCIAMACHY: mission objectives and measurement modes, J. Atmos. Sci., 56, 127–150, https://doi.org/10.1175/1520-0469(1999)056<0127:SMOAMM>2.0.CO;2, 1999.
Brailsford, G. W., Stephens, B. B., Gomez, A. J., Riedel, K., Mikaloff Fletcher, S. E., Nichol, S. E., and Manning, M. R.: Long-term continuous atmospheric CO2 measurements at Baring Head, New Zealand, Atmos. Meas. Tech., 5, 3109–3117, https://doi.org/10.5194/amt-5-3109-2012, 2012.
Chalon, G., Cayla, F., and Diebel, D.: IASI: an advanced sounder for operational meteorology, in: Proc. 52nd Int. Astronautical Congress, 1–9, available at: http://smsc.cnes.fr/documentation/IASI/Publications/PRESENTATION_IAF_2001.pdf, 2001.
Download
Share