Articles | Volume 13, issue 8
https://doi.org/10.5194/amt-13-4393-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/amt-13-4393-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Review article
| 
17 Aug 2020
Review article |
| 17 Aug 2020
| 17 Aug 2020
Overview: Estimating and reporting uncertainties in remotely sensed atmospheric composition and temperature
Thomas von Clarmann
CORRESPONDING AUTHOR
Karlsruhe Institute of Technology, Institute of Meteorology and Climate Research, Karlsruhe, Germany
Douglas A. Degenstein
Department of Physics & Engineering Physics, University of Saskatchewan, Saskatoon, Canada
Nathaniel J. Livesey
NASA Jet Propulsion Laboratory and California Institute of Technology, Pasadena, CA, USA
Stefan Bender
Department of Physics, Norwegian University of Science and Technology (NTNU), 7491 Trondheim, Norway
Amy Braverman
NASA Jet Propulsion Laboratory and California Institute of Technology, Pasadena, CA, USA
André Butz
Institut für Umweltphysik, Department of Physics and Astronomy, Universität Heidelberg, Heidelberg, Germany
Steven Compernolle
Department of Atmospheric Composition, Royal Belgian Institute for Space Aeronomy (BIRA-IASB), 1180 Brussels, Belgium
Robert Damadeo
NASA Langley Research Center, Hampton, VA, USA
Seth Dueck
Department of Physics & Engineering Physics, University of Saskatchewan, Saskatoon, Canada
Patrick Eriksson
Department of Space, Earth and Environment, Chalmers University of Technology, Gothenburg, Sweden
Bernd Funke
Instituto de Astrofísica de Andalucía, CSIC
Margaret C. Johnson
NASA Jet Propulsion Laboratory and California Institute of Technology, Pasadena, CA, USA
Yasuko Kasai
National Institute of Information and Communications Technology (NICT), 4-2-1 Nukui-kita, Koganei, Tokyo 184-8795, Japan
Arno Keppens
Department of Atmospheric Composition, Royal Belgian Institute for Space Aeronomy (BIRA-IASB), 1180 Brussels, Belgium
Anne Kleinert
Karlsruhe Institute of Technology, Institute of Meteorology and Climate Research, Karlsruhe, Germany
Natalya A. Kramarova
NASA Goddard Space Flight Center, Greenbelt, MD, USA
Alexandra Laeng
Karlsruhe Institute of Technology, Institute of Meteorology and Climate Research, Karlsruhe, Germany
Bavo Langerock
Department of Atmospheric Composition, Royal Belgian Institute for Space Aeronomy (BIRA-IASB), 1180 Brussels, Belgium
Vivienne H. Payne
NASA Jet Propulsion Laboratory and California Institute of Technology, Pasadena, CA, USA
Alexei Rozanov
Institute of Environmental Physics (IUP), University of Bremen, Bremen, Germany
Tomohiro O. Sato
National Institute of Information and Communications Technology (NICT), 4-2-1 Nukui-kita, Koganei, Tokyo 184-8795, Japan
Matthias Schneider
Karlsruhe Institute of Technology, Institute of Meteorology and Climate Research, Karlsruhe, Germany
Patrick Sheese
Department of Physics, University of Toronto, Toronto, Canada
Viktoria Sofieva
Finnish Meteorological Institute, Helsinki, Finland
Gabriele P. Stiller
Karlsruhe Institute of Technology, Institute of Meteorology and Climate Research, Karlsruhe, Germany
Christian von Savigny
Institute of Physics, Greifswald University, Greifswald, Germany
Daniel Zawada
Department of Physics & Engineering Physics, University of Saskatchewan, Saskatoon, Canada
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Latest update: 13 Dec 2024
Short summary
Remote sensing of atmospheric state variables typically relies on the inverse solution of the radiative transfer equation. An adequately characterized retrieval provides information on the uncertainties of the estimated state variables as well as on how any constraint or a priori assumption affects the estimate. This paper summarizes related techniques and provides recommendations for unified error reporting.
Remote sensing of atmospheric state variables typically relies on the inverse solution of the...
Special issue