  Stochastic schemes, designed to represent unresolved sub-grid scale
variability, are frequently used in short and medium-range weather forecasts,
where they are found to improve several aspects of the model. In recent years,
the impact of stochastic physics has also been found to be beneficial for the
model's long term climate. In this paper, we demonstrate for the first time
that the inclusion of a stochastic physics scheme can notably affect a model's
projection of global warming, as well as its historical climatological global
temperature. Specifically, we find that when including the 'stochastically
perturbed parametrisation tendencies' scheme (SPPT) in the fully coupled
climate model EC-Earth v3.1, the predicted level of global warming between 1850
and 2100 is reduced by 10% under an RCP8.5 forcing scenario. We link this
reduction in climate sensitivity to a change in the cloud feedbacks with SPPT.
In particular, the scheme appears to reduce the positive low cloud cover
feedback, and increase the negative cloud optical feedback. A key role is
played by a robust, rapid increase in cloud liquid water with SPPT, which we
speculate is due to the scheme's non-linear interaction with condensation.
