Articles | Volume 9, issue 8
https://doi.org/10.5194/amt-9-3921-2016
https://doi.org/10.5194/amt-9-3921-2016
Research article
 | 
23 Aug 2016
Research article |  | 23 Aug 2016

HDO and H2O total column retrievals from TROPOMI shortwave infrared measurements

Remco A. Scheepmaker, Joost aan de Brugh, Haili Hu, Tobias Borsdorff, Christian Frankenberg, Camille Risi, Otto Hasekamp, Ilse Aben, and Jochen Landgraf

Related authors

The operational methane retrieval algorithm for TROPOMI
Haili Hu, Otto Hasekamp, André Butz, André Galli, Jochen Landgraf, Joost Aan de Brugh, Tobias Borsdorff, Remco Scheepmaker, and Ilse Aben
Atmos. Meas. Tech., 9, 5423–5440, https://doi.org/10.5194/amt-9-5423-2016,https://doi.org/10.5194/amt-9-5423-2016, 2016
Short summary
Carbon monoxide total column retrievals from TROPOMI shortwave infrared measurements
Jochen Landgraf, Joost aan de Brugh, Remco Scheepmaker, Tobias Borsdorff, Haili Hu, Sander Houweling, Andre Butz, Ilse Aben, and Otto Hasekamp
Atmos. Meas. Tech., 9, 4955–4975, https://doi.org/10.5194/amt-9-4955-2016,https://doi.org/10.5194/amt-9-4955-2016, 2016
Short summary
Validation of SCIAMACHY HDO/H2O measurements using the TCCON and NDACC-MUSICA networks
R. A. Scheepmaker, C. Frankenberg, N. M. Deutscher, M. Schneider, S. Barthlott, T. Blumenstock, O. E. Garcia, F. Hase, N. Jones, E. Mahieu, J. Notholt, V. Velazco, J. Landgraf, and I. Aben
Atmos. Meas. Tech., 8, 1799–1818, https://doi.org/10.5194/amt-8-1799-2015,https://doi.org/10.5194/amt-8-1799-2015, 2015
Interannual variability of isotopic composition in water vapor over western Africa and its relationship to ENSO
A. Okazaki, Y. Satoh, G. Tremoy, F. Vimeux, R. Scheepmaker, and K. Yoshimura
Atmos. Chem. Phys., 15, 3193–3204, https://doi.org/10.5194/acp-15-3193-2015,https://doi.org/10.5194/acp-15-3193-2015, 2015
Global-scale remote sensing of water isotopologues in the troposphere: representation of first-order isotope effects
S. J. Sutanto, G. Hoffmann, R. A. Scheepmaker, J. Worden, S. Houweling, K. Yoshimura, I. Aben, and T. Röckmann
Atmos. Meas. Tech., 8, 999–1019, https://doi.org/10.5194/amt-8-999-2015,https://doi.org/10.5194/amt-8-999-2015, 2015

Related subject area

Subject: Gases | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
MIPAS ozone retrieval version 8: middle-atmosphere measurements
Manuel López-Puertas, Maya García-Comas, Bernd Funke, Thomas von Clarmann, Norbert Glatthor, Udo Grabowski, Sylvia Kellmann, Michael Kiefer, Alexandra Laeng, Andrea Linden, and Gabriele P. Stiller
Atmos. Meas. Tech., 16, 5609–5645, https://doi.org/10.5194/amt-16-5609-2023,https://doi.org/10.5194/amt-16-5609-2023, 2023
Short summary
Atmospheric N2O and CH4 total columns retrieved from low-resolution Fourier transform infrared (FTIR) spectra (Bruker VERTEX 70) in the mid-infrared region
Minqiang Zhou, Bavo Langerock, Mahesh Kumar Sha, Christian Hermans, Nicolas Kumps, Rigel Kivi, Pauli Heikkinen, Christof Petri, Justus Notholt, Huilin Chen, and Martine De Mazière
Atmos. Meas. Tech., 16, 5593–5608, https://doi.org/10.5194/amt-16-5593-2023,https://doi.org/10.5194/amt-16-5593-2023, 2023
Short summary
A new accurate retrieval algorithm of bromine monoxide columns inside minor volcanic plumes from Sentinel-5P TROPOMI observations
Simon Warnach, Holger Sihler, Christian Borger, Nicole Bobrowski, Steffen Beirle, Ulrich Platt, and Thomas Wagner
Atmos. Meas. Tech., 16, 5537–5573, https://doi.org/10.5194/amt-16-5537-2023,https://doi.org/10.5194/amt-16-5537-2023, 2023
Short summary
Estimation of anthropogenic and volcanic SO2 emissions from satellite data in the presence of snow/ice on the ground
Vitali E. Fioletov, Chris A. McLinden, Debora Griffin, Nickolay A. Krotkov, Can Li, Joanna Joiner, Nicolas Theys, and Simon Carn
Atmos. Meas. Tech., 16, 5575–5592, https://doi.org/10.5194/amt-16-5575-2023,https://doi.org/10.5194/amt-16-5575-2023, 2023
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

Cited articles

Aggarwal, P. K., Gat, J. R., and Froehlich, K. F.: Isotopes in the Water Cycle: Past, present and future of a developing science, Springer, Dordrecht, the Netherlands, ISBN-13: 978-1-4020-3023-9, 2005.
Boesch, H., Deutscher, N. M., Warneke, T., Byckling, K., Cogan, A. J., Griffith, D. W. T., Notholt, J., Parker, R. J., and Wang, Z.: HDO/H2O ratio retrievals from GOSAT, Atmos. Meas. Tech., 6, 599–612, https://doi.org/10.5194/amt-6-599-2013, 2013.
Borsdorff, T., Hasekamp, O. P., Wassmann, A., and Landgraf, J.: Insights into Tikhonov regularization: application to trace gas column retrieval and the efficient calculation of total column averaging kernels, Atmos. Meas. Tech., 7, 523–535, https://doi.org/10.5194/amt-7-523-2014, 2014.
Boucher, O., Randall, D., Artaxo, P., Bretherton, C., Feingold, G., Forster, P., Kerminen, V.-M., Kondo, Y., Liao, H., Lohmann, U., Rasch, P., Satheesh, S., Sherwood, S., Stevens, B., and Zhang, X.: Clouds and Aerosols, in: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 2013.
Craig, H.: Isotopic Variations in Meteoric Waters, Science, 133, 1702–1703, https://doi.org/10.1126/science.133.3465.1702, 1961.
Download
Short summary
We have developed an algorithm to measure HDO (heavy water) in the atmosphere using the TROPOMI satellite instrument, scheduled for launch in 2016. Giving an insight in the history of water vapour, these measurements will help to better understand the water cycle and its role in climate change. We use realistic measurement simulations to describe the performance of the algorithm, and show that TROPOMI will greatly improve and extend the HDO datasets from the previous SCIAMACHY and GOSAT missions.