Nonlocal, Pattern-aware Response and Feedback Framework for Regional Climate Change

TL;DR

This paper introduces a pattern-aware feedback framework and reduced-order model to better understand and predict regional climate change responses, capturing nonlocal effects and feedback mechanisms from Green's function experiments.

Contribution

It develops a comprehensive linear response function that incorporates pattern-aware feedbacks and nonlocal effects, enabling improved regional climate response modeling.

Findings

The CLRF captures polar amplified climate responses.

The ROM accurately predicts climate responses to various forcings.

Pattern-aware feedbacks improve regional climate change understanding.

Abstract

We devise a pattern-aware feedback framework for representing the forced climate response using a suite of Green's function experiments with solar radiation perturbations. By considering the column energy balance, a comprehensive linear response function (CLRF) forimportant climate variables and feedback quantities such as moist static energy, sea surface temperature, albedo, cloud optical depth, and lapse rate is learned from Green's function data. The learned CLRF delineates the effects of the energy diffusion in both the ocean and atmosphere and the pattern-aware feedbacks from the aforementioned radiatively active processes. The CLRF can then be decomposed into forcing-response mode pairs which are in turn used to construct a reduced-order model (ROM) describing the dominant dynamics of climate responses. These mode pairs capture nonlocal effects and teleconnections in the climate and thus, make the ROM apt for capturing regional features of climate change response. A key observation is that the CLRF captures the polar amplified response as the most excitable mode of the climate system and this mode is explainable in the data-learned pattern-aware feedback framework. The ROM can be used for predicting the response for a given forcing and for reconstructing the forcing from a given response; we demonstrate these capabilities for independent forcing pattern.