Abstract
Quantifying the relative contributions of external forcing and internal variability to North Atlantic Sea Surface Temperature (NASST) has important implications for attributing and predicting climate changes around the North Atlantic basin. Many previous methods have approached this problem by estimating the externally forced signal directly, making assumptions about forced variability for which there is no consensus. In this work, the separation of variability is approached in a fundamentally different way that does not specify the forced response’s temporal evolution. We propose a dynamical adjustment method in which the internal, spatially uniform component of NASST is predicted based on patterns of NASST that are orthogonal to the spatially uniform pattern. When applied to preindustrial simulations, the dynamical adjustment demonstrates skill in reconstructing the NASST basin mean variability. Applying the dynamical adjustment to historical simulations demonstrates skill in a majority of climate models, although the skill is reduced relative to preindustrial simulations because external variability partly contaminates the predictors. The dynamical adjustment is compared to several other methods which directly estimate the externally forced signal. We find that dynamical adjustment performs similarly to these comparative methods, despite the fundamentally different prediction method. However, methods based on different principles yield considerably different estimates of external and internal variability.
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