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https://egusphere.copernicus.org/preprints/2023/egusphere-2023-2427/

*Authors*
Olaf Morgenstern <[email protected]>
*Received: 19 Oct 2023 – Discussion started: 18 Dec 2023*

Abstract. The most recent generation of climate models that has informed
the 6th Assessment Report (AR6) of IPCC is characterized by the presence of
several models with anomalously large equilibrium climate sensitivities
(ECSs) relative to the previous generation. Partly as a result, AR6 did not
use any direct quantifications of ECSs based on 4xCO2 simulations and
relied on other evidence when assessing the Earth’s actual ECS. Here I use
the historical observed global-mean surface air temperature and simulations
produced under the Detection and Attribution Model Intercomparison Project
to constrain the ECS and historical aerosol-related cooling. Based on 15
largely independent models I obtain an average adjusted ECS of 3.4±0.8 K
(at 68 % confidence), which is very consistent with the AR6 estimate.
Furthermore, importantly I find that the optimal cooling due to
anthropogenic aerosols consistent with the observed temperature record
should on average be about 34±31 % of what these models simulate, yielding
a multi-model-mean, global-, and annual-mean aerosol-related cooling for
2000–2014, relative to 1850–1899, of -0.19±0.14 K (at 68 % confidence),
when these models simulate on average -0.63±0.28 K. For 12 models the
reduction in aerosol-related cooling equals or exceeds 50 %. There is a
correlation between the models’ ECS and their aerosol-related cooling,
whereby large-ECS models tend to be associated also with large
aerosol-related cooling. The results imply that a large reduction of the
aerosol-related cooling, along with a more moderate adjustment of the
greenhouse-gas related warming, for most models would bring the historical
global mean temperature simulated by these models into better agreement
with observations.
How to cite. Morgenstern, O.: Using historical temperature to constrain the
climate sensitivity and aerosol-induced cooling, EGUsphere [preprint],
https://doi.org/10.5194/egusphere-2023-2427, 2023.
*Source: EGUsphere*

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