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Abstract The patterns associated with the top-of-the-atmosphere radiative responseRto surface temperatureTare typically explored through two relationships: 1) the spatially varying radiative response to spatially varying changes in temperature (ΔR_i/ΔT_i) and 2) the spatially varying radiative response to global-mean changes in temperature (ΔR_i/ΔT). Here, we explore the insights provided by an alternative parameter: the global-mean radiative response to changes in spatially varying temperature (ΔR/ΔT_i). The pattern ΔR/ΔT_iindicates regions where surface temperature covaries withRand thus provides a statistical analog to the causal response functions derived from atmospheric Green’s function experiments. The pattern can be transformed so that it can be globally averaged and thus indicates the local contribution to the global feedback parameter. The transformed version of ΔR/ΔT_icorresponds to the pattern in surface temperature whose expansion coefficient time series explains the maximum fraction of the covariance betweenRandT_i. It explains roughly the same fraction of internal variability inRas that explained by the Green’s function approach. We focus on the physical insights provided by ΔR/ΔT_iwhen it is estimated from regression analyses of monthly mean observations. Consistent with the results of Green’s function experiments, the observational analyses indicate negative contributions to the global internal feedback parameter over the western Pacific and positive contributions over the southeastern tropical Pacific. Unlike the results of such experiments, the analyses indicate notable negative contributions to the global feedback parameter over land areas. When estimated from observations, temperature variability over the land areas accounts for ∼70% of the negative global internal feedback, whereas variability over the southeastern tropical Pacific reduces the global-mean negative internal feedback by ∼10%.