Articles | Volume 13, issue 1
https://doi.org/10.5194/amt-13-85-2020
https://doi.org/10.5194/amt-13-85-2020
Research article
 | Highlight paper
 | 
13 Jan 2020
Research article | Highlight paper |  | 13 Jan 2020

First data set of H2O/HDO columns from the Tropospheric Monitoring Instrument (TROPOMI)

Andreas Schneider, Tobias Borsdorff, Joost aan de Brugh, Franziska Aemisegger, Dietrich G. Feist, Rigel Kivi, Frank Hase, Matthias Schneider, and Jochen Landgraf

Related authors

Isotopic measurements in water vapor, precipitation, and seawater during EUREC4A
Adriana Bailey, Franziska Aemisegger, Leonie Villiger, Sebastian A. Los, Gilles Reverdin, Estefanía Quiñones Meléndez, Claudia Acquistapace, Dariusz B. Baranowski, Tobias Böck, Sandrine Bony, Tobias Bordsdorff, Derek Coffman, Simon P. de Szoeke, Christopher J. Diekmann, Marina Dütsch, Benjamin Ertl, Joseph Galewsky, Dean Henze, Przemyslaw Makuch, David Noone, Patricia K. Quinn, Michael Rösch, Andreas Schneider, Matthias Schneider, Sabrina Speich, Bjorn Stevens, and Elizabeth J. Thompson
Earth Syst. Sci. Data, 15, 465–495, https://doi.org/10.5194/essd-15-465-2023,https://doi.org/10.5194/essd-15-465-2023, 2023
Short summary
Retrieving H2O/HDO columns over cloudy and clear-sky scenes from the Tropospheric Monitoring Instrument (TROPOMI)
Andreas Schneider, Tobias Borsdorff, Joost aan de Brugh, Alba Lorente, Franziska Aemisegger, David Noone, Dean Henze, Rigel Kivi, and Jochen Landgraf
Atmos. Meas. Tech., 15, 2251–2275, https://doi.org/10.5194/amt-15-2251-2022,https://doi.org/10.5194/amt-15-2251-2022, 2022
Short summary
Total water vapour columns derived from Sentinel 5P using the AMC-DOAS method
Tobias Küchler, Stefan Noël, Heinrich Bovensmann, John Philip Burrows, Thomas Wagner, Christian Borger, Tobias Borsdorff, and Andreas Schneider
Atmos. Meas. Tech., 15, 297–320, https://doi.org/10.5194/amt-15-297-2022,https://doi.org/10.5194/amt-15-297-2022, 2022
Short summary
The TROPOSIF global sun-induced fluorescence dataset from the Sentinel-5P TROPOMI mission
Luis Guanter, Cédric Bacour, Andreas Schneider, Ilse Aben, Tim A. van Kempen, Fabienne Maignan, Christian Retscher, Philipp Köhler, Christian Frankenberg, Joanna Joiner, and Yongguang Zhang
Earth Syst. Sci. Data, 13, 5423–5440, https://doi.org/10.5194/essd-13-5423-2021,https://doi.org/10.5194/essd-13-5423-2021, 2021
Short summary
Intercomparison of arctic XH2O observations from three ground-based Fourier transform infrared networks and application for satellite validation
Qiansi Tu, Frank Hase, Thomas Blumenstock, Matthias Schneider, Andreas Schneider, Rigel Kivi, Pauli Heikkinen, Benjamin Ertl, Christopher Diekmann, Farahnaz Khosrawi, Michael Sommer, Tobias Borsdorff, and Uwe Raffalski
Atmos. Meas. Tech., 14, 1993–2011, https://doi.org/10.5194/amt-14-1993-2021,https://doi.org/10.5194/amt-14-1993-2021, 2021
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

Aemisegger, F. and Papritz, L.: A Climatology of Strong Large-Scale Ocean Evaporation Events. Part I: Identification, Global Distribution, and Associated Climate Conditions, J. Climate, 31, 7287–7312, https://doi.org/10.1175/JCLI-D-17-0591.1, 2018. a
Aemisegger, F. and Sjolte, J.: A Climatology of Strong Large-Scale Ocean Evaporation Events. Part II: Relevance for the Deuterium Excess Signature of the Evaporation Flux, J. Climate, 31, 7313–7336, https://doi.org/10.1175/JCLI-D-17-0592.1, 2018. a
Aemisegger, F., Sturm, P., Graf, P., Sodemann, H., Pfahl, S., Knohl, A., and Wernli, H.: Measuring variations of δ18O and δ2H in atmospheric water vapour using two commercial laser-based spectrometers: an instrument characterisation study, Atmos. Meas. Tech., 5, 1491–1511, https://doi.org/10.5194/amt-5-1491-2012, 2012. a
Barthlott, S., Schneider, M., Hase, F., Blumenstock, T, Mengistu Tsidu, G., Grutter de la Mora, M., Strong, K., Notholt, J., Mahieu, E., Jones, N., and Smale, D.: The ground-based MUSICA dataset: Tropospheric water vapour isotopologues (H216O, H218O and HD16O) as obtained from NDACC/FTIR solar absorption spectra, https://doi.org/10.5281/zenodo.48902, Zenodo, 2016. a, b, c, d, e, f, g, h
Barthlott, S., Schneider, M., Hase, F., Blumenstock, T., Kiel, M., Dubravica, D., García, O. E., Sepúlveda, E., Mengistu Tsidu, G., Takele Kenea, S., Grutter, M., Plaza-Medina, E. F., Stremme, W., Strong, K., Weaver, D., Palm, M., Warneke, T., Notholt, J., Mahieu, E., Servais, C., Jones, N., Griffith, D. W. T., Smale, D., and Robinson, J.: Tropospheric water vapour isotopologue data (H216O, H218O, and HD16O) as obtained from NDACC/FTIR solar absorption spectra, Earth Syst. Sci. Data, 9, 15–29, https://doi.org/10.5194/essd-9-15-2017, 2017. a, b
Download
Short summary
This paper presents a new H2O/HDO data set from TROPOMI short-wave infrared measurements. It is validated against recent ground-based FTIR measurements from the TCCON network. A bias in TCCON HDO (which is not verified) is corrected by fitting a correction factor for the HDO column to match MUSICA δD for common observations. The use of the new TROPOMI data set is demonstrated using a case study of a blocking anticyclone over Europe in July 2018.
Share