Publications by Duncan Watson-Parris


Efficacy of climate forcings in PDRMIP models

Journal of Geophysical Research: Atmospheres American Geophysical Union 124 (2019) 12824-12844

TB Richardson, PM Forster, CJ Smith, AC Maycock, T Wood, T Andrews, O Boucher, G Faluvegi, D Flaeschner, O Hodnebrog, M Kasoar, A Kirkevåg, J-F Lamarque, J Mülmenstädt, G Myhre, D Olivié, RW Portmann, BH Samset, D Shawki, D Shindell, P Stier, T Takemura, A Voulgarakis, D Watson-Parris

Quantifying the efficacy of different climate forcings is important for understanding the real‐world climate sensitivity. This study presents a systematic multi‐model 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. Multi‐model mean efficacies based on ERF are close to one for global perturbations of methane, sulphate, black carbon and insolation, but there is notable inter‐model spread. We do not find robust evidence that the geographic location of sulphate 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 (ECS) when estimated using the historical GSAT trend.


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