Assessment of different metrics for physical climate feedbacks

Daniel Klocke,Bjorn Stevens,Johannes Quaas

doi:10.1007/s00382-013-1757-1

Abstract

We quantify the feedbacks from the physical climate system on the radiative forcing for idealized climate simulations using four different methods. The results differ between the methods and differences are largest for the cloud feedback. The spatial and temporal variability of each feedback is used to estimate the averaging scale necessary to satisfy the feedback concept of one constant global mean value. We find that the year-to-year variability, combined with the methodological differences, in estimates of the feedback strength from a single model is comparable to the model-to-model spread in feedback strength of the CMIP3 ensemble. The strongest spatial and temporal variability is in the short-wave component of the cloud feedback. In our simulations, where many sources of natural variability are neglected, long-term averages are necessary to get reliable feedback estimates. Considering the large natural variability and relatively small forcing present in the real world, as compared to the forcing imposed by doubling CO2 concentrations in the simulations, implies that using observations to constrain feedbacks is a challenging task and requires reliable long-term measurements.

Highlights

Climate models still give a wide range of surface temperature responses to the same idealized external forcing, for example a doubling of the atmospheric CO2 concentration (Solomon et al 2007)
We quantify the feedbacks from the physical climate system on the radiative forcing for idealized climate simulations using four different methods
We find that the year-to-year variability, combined with the methodological differences, in estimates of the feedback strength from a single model is comparable to the model-to-model spread in feedback strength of the CMIP3 ensemble

Summary

Introduction

Climate models still give a wide range of surface temperature responses to the same idealized external forcing, for example a doubling of the atmospheric CO2 concentration (Solomon et al 2007). Most of these differences arise from physical processes, which are usefully conceptualized as feedbacks and can be isolated through a feedback analysis (Cess et al 1990; Colman 2003; Soden and Held 2006). If those processes in turn have an effect on the radiation budget (and on temperature), they are referred to as climate ‘‘feedbacks’’, analogously to the feedback definition in electronic circuits Those feedbacks can have amplifying (positive feedback) and dampening (negative feedback) effects on the initial perturbation of the ToA radiation budget. For a forcing from a doubling of the atmospheric CO2 concentration, the equilibrium temperature change is often referred to as the equilibrium climate sensitivity

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Methods

Conclusion