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Discussion papers
https://doi.org/10.5194/acp-2020-101
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-2020-101
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 17 Feb 2020

Submitted as: research article | 17 Feb 2020

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This preprint is currently under review for the journal ACP.

Study of the dependence of stratospheric ozone long-term trends on local solar time

Eliane Maillard Barras1, Alexander Haefele1, Liliane Nguyen2, Fiona Tummon1, William T. Ball3,4, Eugene V. Rozanov4, Rolf Rüfenacht1, Klemens Hocke5, Leonie Bernet5, Niklaus Kämpfer5, Gerald Nedoluha6, and Ian Boyd7 Eliane Maillard Barras et al.
  • 1Federal Office of Meteorology and Climatology, MeteoSwiss, Switzerland
  • 2ISE, Institute for Environmental Sciences, University of Geneva, Switzerland
  • 3Institute for Atmospheric and Climate Science, Swiss Federal Institute of Technology Zurich, Switzerland
  • 4Physikalisch-Meteorologisches Observatorium Davos World Radiation Centre, Switzerland
  • 5Institute of Applied Physics and Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland
  • 6Naval Research Laboratory, Washington DC, USA
  • 7BC Scientific Consulting LLC, New Zealand

Abstract. Multi-instrument comparison analyses are essential to assess the long-term stability of data records by estimating the drift and bias of instruments. The ozone profile dataset from the SOMORA microwave radiometer (MWR) in Payerne, Switzerland, was compared with profiles from the GROMOS MWR in Bern, Switzerland, satellite instruments (MLS, MIPAS, HALOE, SCHIAMACHY, GOMOS), and profiles simulated by the SOCOL v3.0 chemistry-climate model (CCM). The Payerne MWR dataset has been homogenized to ensure a stable measurement contribution to the ozone profiles and to take into account the effects of three major instrument upgrades. At pressure levels smaller than 0.59 hPa (above ~ 50 km), the homogenization corrections to be applied to the Payerne MWR ozone profiles are dependent on local solar time (LST). Due to the lack of reference measurements with a comparable measurement contribution at a high time resolution, a comprehensive homogenization of the sub-daily ozone profiles was possible only for pressure levels larger than 0.59 hPa.

The long-term stability and mean biases of the time series were estimated as a function of the measurement time (day- and nighttime). The homogenized Payerne MWR ozone dataset agrees within ± 5 % with the MLS dataset over the 30 to 65 km altitude range and within ± 10 % of HARMOZ datasets over the 30 to 65 km altitude range. In the upper stratosphere, there is a large nighttime difference between Payerne MWR and other datasets, which is likely a result of the mesospheric signal aliasing with lower levels in the stratosphere due to a lower vertical resolution at that altitude. Hence, the induced bias at 55 km is considered an instrumental artefact and is not further analyzed and discussed.

In the upper stratosphere (5–1 hPa, 35–48 km), the Payerne MWR trends are significantly positive at 2 to 3 %/decade. This is in accordance with the northern hemisphere (NH) trends reported by other ground-based instruments in the SPARC LOTUS project. The reason for variability in the reported long-term ground-based and satellite ozone profile trends has multiple possibilities. To determine what part of the variability comes from measurement timing, MWR trends were estimated for each hour of the day with a multiple linear regression model to quantify trends as a function of LST. In the mid- and upper stratosphere, differences as a function of LST are reported for both the MWR and simulated trends for the 2000–2016 period. However, these differences are not significant at the 95 % confidence level. In the lower mesosphere (1–0.1 hPa, 48–65 km), the 2010–2018 day- and nighttime trends have been considered. Here again, the variation of the trend with LST is not significant at the 95 % confidence level. Based on these results we conclude that trend differences between instruments cannot to be attributed to a systematic temporal sampling.

Eliane Maillard Barras et al.

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Short summary
To determine the part of the variability of the long-term ozone profile trends coming from measurement timing, we estimate microwave radiometer trends for each hour of the day with a multiple linear regression model. The variation of the trend with local solar time is not significant at the 95 % confidence level neither in the stratosphere nor in the low mesosphere. We conclude that systematic sampling differences between instruments cannot explain significant differences in trend estimates.
To determine the part of the variability of the long-term ozone profile trends coming from...
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