Improved Estimates of Equilibrium Climate Sensitivity From Non‐Equilibrated Climate Simulations

Calculating equilibrium climate sensitivity (ECS) requires simulations of a thousand years or more for the climate to re‐establish equilibrium, but most ECS estimates are derived from shorter model integrations. The widely used “Gregory method” for such estimates systematically underestimates ECS, a bias previously attributed to the time‐dependence of climate feedbacks. Here we demonstrate this underestimate instead arises primarily from an underestimate of radiative forcing. We present a modified method that corrects for the underestimate in forcing, producing ECS estimates that closely align with results from “long‐run” millennium‐scale simulations. This method is robust across models and offers an easily obtainable estimate of ECS with significantly higher accuracy. It enables reliable ECS estimates for full CMIP model ensembles, including models without millennium‐scale simulations. Using this method, we show one of every three CMIP6 climate models has an ECS greater than 5K—the upper bound of the “very likely” range in prior assessments. To further verify this method, we introduce an “integrated feedback parameter” which provides a more physically‐meaningful way to average a time‐evolving climate sensitivity by weighting the differential feedback in consecutive, non‐overlapping time segments by the fraction of energy imbalance that each segment restores. This parameter agrees well with that derived from our modified method, lending further credibility to this simplified approach.