The linear response function of an idealized atmosphere. Part 2: Implications for the practical use of the Fluctuation-Dissipation Theorem and the role of operator's non-normality

TL;DR

This paper investigates why the Fluctuation-Dissipation Theorem often performs poorly in climate models by analyzing the impact of operator non-normality and dimension-reduction techniques on the accuracy of linear response functions.

Contribution

It demonstrates that dimension-reduction by EOFs and operator non-normality are key factors causing errors in FDT-based LRF calculations in climate models.

Findings

FDT-based LRFs perform poorly for some test cases.

Dimension-reduction via EOFs introduces significant errors.

Operator non-normality is a primary source of these errors.

Abstract

A linear response function (LRF) relates the mean-response of a nonlinear system to weak external forcings and vice versa. Even for simple models of the general circulation, such as the dry dynamical core, the LRF cannot be calculated from first principles due to the lack of a complete theory for eddy-mean flow feedbacks. According to the Fluctuation-Dissipation Theorem (FDT), the LRF can be calculated using only the covariance and lag-covariance matrices of the unforced system. However, efforts in calculating the LRFs for GCMs using FDT have produced mixed results, and the reason(s) behind the poor performance of the FDT remains unclear. In Part 1 of this study, the LRF of an idealized GCM, the dry dynamical core with Held-Suarez physics, is accurately calculated using Green's functions. In this paper (Part 2), the LRF of the same model is computed using FDT, which is found to perform poorly for some of the test cases. The accurate LRF of Part 1 is used with a linear stochastic equation to show that dimension-reduction by projecting the data onto leading EOFs, which is commonly used for FDT, can alone be a significant source of error. Simplified equations and examples of 2 x 2 matrices are then used to demonstrate that this error arises because of the non-normality of the operator. These results suggest that errors caused by dimension-reduction are a major, if not the main, contributor to the poor performance of the LRF calculated using FDT, and that further investigations of dimension-reduction strategies with a focus on non-normality are needed.