The representation of solar cycle signals in stratospheric ozone – Part 2: Analysis of global models

Amanda C. Maycock (1) , Katja Matthes (2, 3) , Susann Tegtmeier (3) , Hauke Schmidt (4) , Rémi Thiéblemont (5) , Lon Hood (6) , Hideharu Akiyoshi (7) , Slimane Bekki (5) , Makoto Deushi (8) , Patrick Jöckel (9) , Oliver Kirner (10) , Markus Kunze (11) , Marion Marchand (5) , Daniel R. Marsh (12) , Martine Michou (13) , David A. Plummer (14) , Laura E. Revell (15, 16) , Eugene Rozanov (17, 15) , Andrea Stenke (15) , Yousuke Yamashita (7, 18) , Kohei Yoshida (8)

1 SEE - School of Earth and Environment [Leeds]
2 CAU - Christian-Albrechts-Universität zu Kiel
3 GEOMAR - Helmholtz Centre for Ocean Research [Kiel]
4 MPI-M - Max-Planck-Institut für Meteorologie
5 STRATO - LATMOS
6 University of Arizona
7 NIES - National Institute for Environmental Studies
8 MRI - Meteorological Research Institute [Tsukuba]
9 IPA - DLR Institut für Physik der Atmosphäre
10 SCC - Steinbuch Centre for Computing [Karlsruhe]
11 Institut für Meteorologie [Berlin]
12 NCAR - National Center for Atmospheric Research [Boulder]
13 CNRM - Centre national de recherches météorologiques
14 Environment and Climate Change Canada
15 IAC - Institute for Atmospheric and Climate Science [Zürich]
16 Bodeker Scientific
17 PMOD/WRC - Physikalisch-Meteorologisches Observatorium Davos/World Radiation Center
18 JAMSTEC - Japan Agency for Marine-Earth Science and Technology

The impact of changes in incoming solar irradiance on stratospheric ozone abundances should be included in climate model simulations to fully capture the atmospheric response to solar variability. This study presents the first systematic comparison of the solar-ozone response (SOR) during the 11 year solar cycle amongst different chemistry-climate models (CCMs) and ozone databases specified in climate models that do not include chemistry. We analyse the SOR in eight CCMs from the WCRP/SPARC Chemistry-Climate Model Initiative (CCMI-1) and compare these with three ozone databases: the Bodeker Scientific database, the SPARC/AC&C database for CMIP5, and the SPARC/CCMI database for CMIP6. The results reveal substantial differences in the representation of the SOR between the CMIP5 and CMIP6 ozone databases. The peak amplitude of theSOR in the upper stratosphere (1–5 hPa) decreases from 5 % to 2 % between the CMIP5 and CMIP6 databases. This difference is because the CMIP5 database was constructed from a regression model fit to satellite observations, whereas the CMIP6 database is constructed from CCM simulations, which use a spectral solar irradiance (SSI) dataset with relatively weak UV forcing. The SOR in the CMIP6 ozone database is therefore implicitly more similar to the SOR in the CCMI-1 models than to the CMIP5 ozone database, which shows a greater resemblance in amplitude and structure to the SOR in the Bodeker database. The latitudinal structure of the annual mean SOR in the CMIP6 ozone database and CCMI-1 models is considerably smoother than in the CMIP5 database, which shows strong gradients in the SOR across the midlatitudes owing to the paucity of observations at high latitudes. The SORs in the CMIP6 ozone database and in the CCMI-1 models show a strong seasonal dependence, including large meridional gradients at mid to high latitudes during winter; such seasonal variations in the SOR are not included in the CMIP5 ozone database. Sensitivity experiments with a global atmospheric model without chemistry (ECHAM6.3) are performed to assess the impact of changes in the representation of the SOR and SSI forcing between CMIP5 and CMIP6. The experiments show that the smaller amplitude of the SOR in the CMIP6 ozone database compared to CMIP5 causes a decrease in the modelled tropical stratospheric temperature response over the solar cycle of up to 0.6 K, or around 50 % of the total amplitude. The changes in the SOR explain most of the difference in the amplitude of the tropical stratospheric temperature response in the case with combined changes in SOR and SSI between CMIP5 and CMIP6. The results emphasise the importance of adequately representing the SOR in climate models to capture the impact of solar variability on the atmosphere. Since a number of limitations in the representation of the SOR in the CMIP5 ozone database have been identified, CMIP6 models without chemistry are encouraged to use the CMIP6 ozone database to capture the climate impacts of solar variability.

Domains: Atmospheric and Oceanic Physics [physics.ao-ph]

Amanda C. Maycock, Katja Matthes, Susann Tegtmeier, Hauke Schmidt, Rémi Thiéblemont, et al.. The representation of solar cycle signals in stratospheric ozone – Part 2: Analysis of global models. Atmospheric Chemistry and Physics, 2018, 18, pp.11323-11343. ⟨10.5194/acp-18-11323-2018⟩. ⟨insu-01531574⟩