Journal cover Journal topic
Atmospheric Chemistry and Physics An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

Journal metrics

  • IF value: 5.668 IF 5.668
  • IF 5-year value: 6.201 IF 5-year
  • CiteScore value: 6.13 CiteScore
  • SNIP value: 1.633 SNIP 1.633
  • IPP value: 5.91 IPP 5.91
  • SJR value: 2.938 SJR 2.938
  • Scimago H <br class='hide-on-tablet hide-on-mobile'>index value: 174 Scimago H
    index 174
  • h5-index value: 87 h5-index 87
Discussion papers
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 08 Nov 2019

Submitted as: research article | 08 Nov 2019

Review status
A revised version of this preprint is currently under review for the journal ACP.

Sensitivity of Age of Air Trends on the derivation method for non-linear increasing tracers

Frauke Fritsch1,2, Hella Garny1,2, Andreas Engel3, Harald Bönisch4, and Roland Eichinger1,2 Frauke Fritsch et al.
  • 1Deutsches Zentrum für Luft- und Raumfahrt (DLR), Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany
  • 2Ludwig Maximilians University of Munich, Meteorological Institute Munich, Munich, Germany
  • 3Institute for Atmospheric and Environmental Sciences, Goethe University Frankfurt am Main, Frankfurt am Main, Germany
  • 4Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany

Abstract. Mean age of air (AoA) is a diagnostic of transport along the stratospheric Brewer-Dobson circulation. While models consistently show negative trends, long-term time series (1975–2016) of AoA derived from observations show non-significant positive trends in mean AoA in the northern hemisphere. This discrepancy between observed and modeled mean AoA trends is still not resolved. There are uncertainties and assumptions required when deriving AoA from trace gas observations. At the same time, AoA from climate models is subject to uncertainties, too.

In this paper, we focus on the uncertainties due to the parameter selection in the method that is used to derive mean AoA from SF6 measurements in Engel et al. (2009) and Engel et al. (2017). To correct for the non-linear increase in SF6 concentrations, a quadratic fit to the time-series at the reference location, i.e. the tropical surface, is used. For this derivation, the width of the AoA distribution (age spectrum) has to be assumed. In addition, to choose the number of years the quadratic fit is performed for, the fraction of the age spectrum to be considered has to be assumed. Even though the uncertainty range due to all different aspects has already been taken into account for the total errors on the AoA values, the systematic influence of the parameter selection on AoA trends is described for the first time in the present study.

In addition, a method to derive mean AoA is evaluated that applies a convolution to the reference time series. The resulting mean AoA and its trend only depend on an assumption about the ratio of moments. Also in that case, it is found that the larger the ratio of moments, the more the AoA trend gravitates towards the negative. The linear tracer and SF6 AoA is found to agree within 0.3 % in the mean and 6 % in the trend.

The different methods and parameter selections were then applied to the balloon borne SF6 and CO2 observations. We found the same systematic changes in mean AoA trend dependent on the specific selection. When applying a parameter choice that is suggested by the model results, the AoA trend is reduced from 0.15 years/decade to 0.07 years/decade. It illustrates that correctly constraining those parameters is crucial for correct mean AoA and trend estimates and still remains a challenge in the real atmosphere.

Engel, A., Möbius, T., Bönisch, H., Schmidt, U., Heinz, R., Levin, I., Atlas, E., Aoki, S., Nakazawa, T., Sugawara, S., et al.: Age of stratospheric air unchanged within uncertainties over the past 30 years, Nature Geoscience, 2, 28, 2009.

Engel, A., Bönisch, H., Ullrich, M., Sitals, R., Membrive, O., Danis, F., and Crevoisier, C.: Mean age of stratospheric air derived from AirCore observations, Atmospheric Chemistry and Physics, 17, 6825–6838,, 2017.

Frauke Fritsch et al.

Interactive discussion

Status: final response (author comments only)
Status: final response (author comments only)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
[Login for Authors/Editors] [Subscribe to comment alert] Printer-friendly Version - Printer-friendly version Supplement - Supplement

Frauke Fritsch et al.

Frauke Fritsch et al.


Total article views: 245 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
191 52 2 245 4 3
  • HTML: 191
  • PDF: 52
  • XML: 2
  • Total: 245
  • BibTeX: 4
  • EndNote: 3
Views and downloads (calculated since 08 Nov 2019)
Cumulative views and downloads (calculated since 08 Nov 2019)

Viewed (geographical distribution)

Total article views: 178 (including HTML, PDF, and XML) Thereof 178 with geography defined and 0 with unknown origin.
Country # Views %
  • 1



No saved metrics found.


No discussed metrics found.
Latest update: 25 Feb 2020
Publications Copernicus
Short summary
We test two methods to derive Age of Air as a diagnostic of the Brewer-Dobson circulation from non-linear increasing trace gases such as SF6 using a chemistry-climate model and observations. Both the model and the observations show systematic variation of the Age of Air trend dependent on the chosen assumptions that are required when deriving Age of Air from measurements. This provides insight to the differences in Age of Air trends of observations and models.
We test two methods to derive Age of Air as a diagnostic of the Brewer-Dobson circulation from...