PNNL

Abstract

Inquiry into the climate response to external forcing perturbations has been at the center stage of climate dynamics. But the understanding of two important aspects of climate change response—nonlinearity and regionality—has progressed slowly, owing partly to the lack of a multivariate framework for quantifying forcing-response relationships. Here we develop a Green’s function approach to retrieve the linear response functions (LRFs) for both the linear and nonlinear response in a state-of-the-art climate model, whereby the most excitable temperature modes, aka the neutral modes, can be identified for the current Earth climate. The derived leading nonlinear mode is characterized by a polar-amplified global cooling pattern, unveiling an intrinsic propensity of the modern climate towards cooling. Moreover, the Maritime Continents and the eastern Australian coast are identified as locations where forcing perturbations can more effectively excite global cooling. In a solar engineering thought experiment in which the ocean heat flux is reduced everywhere, the LRF matrices skillfully predict the pattern of the temperature response simulated by the climate model. The framework developed herein can be utilized to determine the optimal forcing patterns to inform solar geoengineering experiments and to interpret regional climate response and feedback in general.