The influence of mixing on the stratospheric age of air changes in the 21st century
Eichinger, Roland; Dietmüller, Simone; Garny, Hella; Sacha , Petr; Birner, Thomas; Bönisch, Harald; Pitari, Giovanni; Visioni, Daniele; Stenke, Andrea; Rozanov, Eugene; Revell, Laura; Plummer, David A.; Jöckel, Patrick; Oman, Luke; Deushi, Makoto; Kinnison, Douglas E.; Garcia, Rolando; Morgenstern, Olaf; Zeng, Guang; Stone, Kane Adam; Schofield, Robyn
DATE:
2019-01-24
UNIVERSAL IDENTIFIER: http://hdl.handle.net/11093/4057
EDITED VERSION: https://acp.copernicus.org/articles/19/921/2019/
DOCUMENT TYPE: article
ABSTRACT
Climate models consistently predict an acceleration of the
Brewer–Dobson circulation (BDC) due to climate change in the 21st century.
However, the strength of this acceleration varies considerably among
individual models, which constitutes a notable source of uncertainty for
future climate projections. To shed more light upon the magnitude of this
uncertainty and on its causes, we analyse the stratospheric mean age of air
(AoA) of 10 climate projection simulations from the Chemistry-Climate Model
Initiative phase 1 (CCMI-I), covering the period between 1960 and 2100. In
agreement with previous multi-model studies, we find a large model spread in
the magnitude of the AoA trend over the simulation period. Differences
between future and past AoA are found to be predominantly due to differences
in mixing (reduced aging by mixing and recirculation) rather than differences
in residual mean transport. We furthermore analyse the mixing efficiency, a
measure of the relative strength of mixing for given residual mean transport,
which was previously hypothesised to be a model constant. Here, the mixing
efficiency is found to vary not only across models, but also over time in all
models. Changes in mixing efficiency are shown to be closely related to
changes in AoA and quantified to roughly contribute 10 % to the long-term
AoA decrease over the 21st century. Additionally, mixing efficiency
variations are shown to considerably enhance model spread in AoA changes. To
understand these mixing efficiency variations, we also present a consistent
dynamical framework based on diffusive closure, which highlights the role of
basic state potential vorticity gradients in controlling mixing efficiency
and therefore aging by mixing.