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https://doi.org/10.5194/egusphere-2025-2830
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/egusphere-2025-2830
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
19 Sep 2025
| 19 Sep 2025
Status: this preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
Methods for validation of random uncertainty estimates and their applications to ozone profiles from limb-viewing satellite instruments
Abstract. For satellite measurements of atmospheric composition, the random uncertainty estimates provided by retrieval algorithms might be imperfect due to various approximations used in the retrievals or presence of unknown error sources. This paper presents an overview of the methods used for validation of random uncertainty estimates. All methods discussed in this study are categorized, and assumptions and limitations of each method are discussed. This overview evaluates these methods in application to ozone profile measurements data from limb and occultation satellite instruments and provides practical illustrations of random uncertainty validation.
How to cite. Sofieva, V. F., Laeng, A., von Clarmann, T., Stiller, G., Kiefer, M., Tamminen, J., Rozanov, A., Arosio, C., Livesey, N., Damadeo, R., Sheese, P., Walker, K. A., Degenstein, D., Zawada, D., Kramarova, N. A., and Keppens, A.: Methods for validation of random uncertainty estimates and their applications to ozone profiles from limb-viewing satellite instruments, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2025-2830, 2025.
Competing interests: At least one of the (co-)authors is a member of the editorial board of Atmospheric Measurement Techniques.
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Viktoria F. Sofieva
CORRESPONDING AUTHOR
Finnish Meteorological Institute, Helsinki, Finland
Alexandra Laeng
Karlsruhe Institute of Technology, Institute of Meteorology and Climate Research - Atmospheric Trace Gases and Remote Sensing, Karlsruhe, Germany
Thomas von Clarmann
Karlsruhe Institute of Technology, Institute of Meteorology and Climate Research - Atmospheric Trace Gases and Remote Sensing, Karlsruhe, Germany
deceased
Gabriele Stiller
Karlsruhe Institute of Technology, Institute of Meteorology and Climate Research - Atmospheric Trace Gases and Remote Sensing, Karlsruhe, Germany
Michael Kiefer
Karlsruhe Institute of Technology, Institute of Meteorology and Climate Research - Atmospheric Trace Gases and Remote Sensing, Karlsruhe, Germany
Johanna Tamminen
Finnish Meteorological Institute, Helsinki, Finland
Alexey Rozanov
University of Bremen, Bremen, Germany
Carlo Arosio
University of Bremen, Bremen, Germany
Nathaniel Livesey
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA
Robert Damadeo
NASA Langley Research Center, Hampton, VA, USA
Patrick Sheese
Department of Physics, University of Toronto, Toronto, Canada
Kaley A. Walker
Department of Physics, University of Toronto, Toronto, Canada
Doug Degenstein
Institute of Space and Atmospheric Studies, University of Saskatchewan, Saskatoon, Canada
Daniel Zawada
Institute of Space and Atmospheric Studies, University of Saskatchewan, Saskatoon, Canada
Natalya A. Kramarova
NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
Arno Keppens
Royal Belgian Institute for Space Aeronomy (BIRA-IASB), Brussels, Belgium
Short summary
For satellite measurements of atmospheric composition, the random uncertainty estimates provided by retrieval algorithms might be imperfect due to various approximations used in the retrievals or presence of unknown error sources. This paper presents an overview of the methods used for validation of random uncertainty estimates. All methods discussed in this study are categorized, and assumptions and limitations of each method are discussed.
For satellite measurements of atmospheric composition, the random uncertainty estimates provided...