Including the efficacy of land ice changes in deriving climate sensitivity from paleodata

The equilibrium climate sensitivity (ECS) of climate models is calculated as the equilibrium global
mean surface air warming resulting from a simulated doubling of the atmospheric CO2 concentration. In these
simulations, long-term processes in the climate system, such as land ice changes, are not incorporated. Hence,
climate sensitivity derived from paleodata has to be compensated for these processes, when comparing it to the
ECS of climate models. Several recent studies found that the impact these long-term processes have on global
temperature cannot be quantified directly through the global radiative forcing they induce. This renders the
prevailing approach of deconvoluting paleotemperatures through a partitioning based on radiative forcings inaccurate. Here, we therefore implement an efficacy factor ε[LI]
that relates the impact of land ice changes on global
temperature to that of CO2 changes in our calculation of climate sensitivity from paleodata. We apply our refined
approach to a proxy-inferred paleoclimate dataset, using ε[LI] = 0.45+0.34
−0.20 based on a multi-model assemblage of
simulated relative influences of land ice changes on the Last Glacial Maximum temperature anomaly. The implemented ε[LI]
is smaller than unity, meaning that per unit of radiative, forcing the impact on global temperature is
less strong for land ice changes than for CO2 changes. Consequently, our obtained ECS estimate of 5.8 ± 1.3 K,
where the uncertainty reflects the implemented range in ε[LI]
, is ∼ 50 % higher than when differences in efficacy
are not considered.