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Quantifying the efficacy of different climate forcings is important for understanding the real‐world climate sensitivity. This study presents a systematic multimodel analysis of different climate driver efficacies using simulations from the Precipitation Driver and Response Model Intercomparison Project (PDRMIP). Efficacies calculated from instantaneous radiative forcing deviate considerably from unity across forcing agents and models. Effective radiative forcing (ERF) is a better predictor of global mean near‐surface air temperature (GSAT) change. Efficacies are closest to one when ERF is computed using fixed sea surface temperature experiments and adjusted for land surface temperature changes using radiative kernels. Multimodel mean efficacies based on ERF are close to one for global perturbations of methane, sulfate, black carbon, and insolation, but there is notable intermodel spread. We do not find robust evidence that the geographic location of sulfate aerosol affects its efficacy. GSAT is found to respond more slowly to aerosol forcing than CO2 in the early stages of simulations. Despite these differences, we find that there is no evidence for an efficacy effect on historical GSAT trend estimates based on simulations with an impulse response model, nor on the resulting estimates of climate sensitivity derived from the historical period. However, the considerable intermodel spread in the computed efficacies means that we cannot rule out an efficacy‐induced bias of ±0.4 K in equilibrium climate sensitivity to CO2 doubling when estimated using the historical GSAT trend. Plain Language Summary: Does the climate respond in the same way to carbon dioxide as it does to methane or aerosol changes? The simple way of thinking about forcing and response in the Earth system assumes that it does, such that, a Watt per square meter forcing from CO2 has the same response as an equivalent forcing from aerosols. Recent work has suggested that this might not be true and that differences in how effective different forcings are at increasing surface temperature (their efficacy) may account for a low estimate of climate sensitivity when examining historical change. We show this all depends on how you estimate your Watts per meter squared forcing in the first place. Using the effective radiative forcing concept to estimate forcing strength makes temperature changes far more predictable, and a lot of these issues with efficacy variation are not as pronounced as they were with earlier definitions. Key Points: Multimodel mean efficacies computed using effective radiative forcing are close to one for major anthropogenic drivers, but there is notable intermodel spreadSurface temperature‐driven radiative feedbacks are generally not constant through time across forcing experimentsPDRMIP results suggest that the efficacy impact on equilibrium climate sensitivity derived from the historical period is limited to ±0.4 °C or better [ABSTRACT FROM AUTHOR]

Abstract: Future projections of east Amazonian precipitation indicate drying, but they are uncertain and poorly understood. In this study we analyze the Amazonian precipitation response to individual atmospheric forcings using a number of global climate models. Black carbon is found to drive reduced precipitation over the Amazon due to temperature‐driven circulation changes, but the magnitude is uncertain. CO2 drives reductions in precipitation concentrated in the east, mainly due to a robustly negative, but highly variable in magnitude, fast response. We find that the physiological effect of CO2 on plant stomata is the dominant driver of the fast response due to reduced latent heating and also contributes to the large model spread. Using a simple model, we show that CO2 physiological effects dominate future multimodel mean precipitation projections over the Amazon. However, in individual models temperature‐driven changes can be large, but due to little agreement, they largely cancel out in the model mean. [ABSTRACT FROM AUTHOR]