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Discussion papers
https://doi.org/10.5194/acp-2019-1010
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-2019-1010
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 31 Jan 2020

Submitted as: research article | 31 Jan 2020

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This preprint is currently under review for the journal ACP.

Quantifying uncertainties of climate signals related to the 11–year solar cycle. Part I: Annual mean response in heating rates,temperature and ozone

Markus Kunze1, Tim Kruschke5, Ulrike Langematz1, Miriam Sinnhuber3, Thomas Reddmann3, and Katja Matthes2,4 Markus Kunze et al.
  • 1Institut für Meteorologie, Freie Universität Berlin, 12165 Berlin, Germany
  • 2Research Division Ocean Circulation and Climate, GEOMAR Helmholtz Centre for Ocean Research, 24105 Kiel, Germany
  • 3Karlsruhe Institute of Technology, 76021 Karlsruhe, Germany
  • 4Christian-Albrechts Universität zu Kiel, 24105 Kiel, Germany
  • 5Swedish Meteorological and Hydrological Institute - Rossby Centre, Norrköping, Sweden

Abstract. Variations of the solar spectral irradiance (SSI) with the 11-year sunspot cycle have been shown to have a significant impact on temperatures and the mixing ratios of atmospheric constituents in the stratosphere and mesosphere. Uncertainties in modelling the effects of SSI variations arise from uncertainties in the empirical models reconstructing the prescribed SSI data set as well as from uncertainties in the chemistry-climate model (CCM) formulation. In this study CCM simulations with the ECHAM MESSy Atmospheric Chemistry (EMAC) model and the Community Earth System Model 1 (CESM1) – Whole Atmosphere Chemistry Climate Model (WACCM) have been performed to quantify the uncertainties of the solar responses in chemistry and dynamics that are due to the usage of five different SSI data sets or the two CCMs. We apply a two-way analysis of variance (ANOVA) to separate the influence of the SSI data sets and the CCMs on the variability of the solar response in shortwave heating rates, temperature and ozone. The ANOVA identifies the SSI data set with the strongest influence on the variability of the solar signal in shortwave heating rates in the upper mesosphere and in the upper stratosphere/lower mesosphere. The strongest influence on the variability of the solar signal in ozone and temperature is identified in the upper stratosphere/lower mesosphere. The largest influence of the CCMs on variability of the solar responses can be identified in the upper mesosphere. The solar response in the lower stratosphere also depends on the CCM used, especially in the tropics and northern hemispheric subtropics and mid latitudes, where the model dynamics modulate the solar responses.

Markus Kunze et al.

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Markus Kunze et al.

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