An Assessment of Direct Radiative Forcing, Radiative Adjustments, and Radiative Feedbacks in Coupled Ocean–Atmosphere Models*

Author:

Chung Eui-Seok1,Soden Brian J.1

Affiliation:

1. Rosenstiel School of Marine and Atmospheric Science, University of Miami, Miami, Florida

Abstract

Abstract In this study, radiative kernels are used to separate direct radiative forcing from radiative adjustments to that forcing to quantify the magnitude and intermodel spread of tropospheric and stratospheric adjustments in coupled ocean–atmosphere climate models. Radiative feedbacks are also quantified and separated from radiative forcing by assuming that feedbacks are a linear response to changes in global-mean surface temperature. The direct radiative forcing due to a quadrupling of CO2 is found to have an intermodel spread of ~3 W m−2. In contrast to previous studies, relatively small estimates of cloud adjustments are obtained, which are both positive and negative. This discrepancy is at least partially attributable to small, but nonnegligible, global-mean surface warming in fixed sea surface temperature experiments, which aliases a surface-driven feedback response into estimates of the adjustments. This study suggests that correcting for the bias induced from this global-mean surface warming offers a more accurate estimate of tropospheric adjustments. It is shown that the regional patterns in the tropospheric adjustments tend to oppose the radiative feedback. This compensation is closely tied to spatial inhomogeneities in the initial rate of surface warming, suggesting that a substantial part of the spatial variation in the estimated tropospheric adjustment is an artifact of the linear regression methodology. Even when assuming that the global-mean estimates of the tropospheric adjustments are valid, neglecting them introduces little uncertainty in estimates of the total forcing, feedback, or effective climate sensitivity relative to the intermodel spread in these values.

Publisher

American Meteorological Society

Subject

Atmospheric Science

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