Origin and Limits of Invariant Warming Patterns in Climate Models

TL;DR

This paper explains why climate models show a consistent warming pattern over time and space, and clarifies the conditions under which pattern scaling is valid, addressing apparent contradictions with observed pattern variability.

Contribution

The authors develop a simple energy balance theory that explains the invariance of warming patterns in climate models and delineates conditions where pattern scaling applies or breaks down.

Findings

Pattern invariance arises from exponential forcing, linear feedbacks, and diffusive dynamics.

In Arctic and aerosol-affected regions, nonlinear feedbacks cause deviations from pattern invariance.

Warming pattern changes over time in abrupt CO2 increase experiments due to ocean heat uptake.

Abstract

Climate models exhibit an approximately invariant surface warming pattern in typical end-of-century projections. This observation has been used extensively in climate impact assessments for fast calculations of local temperature anomalies, with a linear procedure known as pattern scaling. At the same time, emerging research has also shown that time-varying warming patterns are necessary to explain the time evolution of effective climate sensitivity in coupled models, a mechanism that is known as the pattern effect and that seemingly challenges the pattern scaling understanding. Here we present a simple theory based on local energy balance arguments to reconcile this apparent contradiction. Specifically, we show that the pattern invariance is an inherent feature of exponential forcing, linear feedbacks, a constant forcing pattern and diffusive dynamics. These conditions are approximately met in most CMIP6 Shared Socioeconomic Pathways (SSP), except in the Arctic where nonlinear feedbacks are important and in regions where aerosols considerably alter the forcing pattern. In idealized experiments where concentrations of CO2 are abruptly increased, such as those used to study the pattern effect, the warming pattern can change considerably over time because of spatially inhomogeneous ocean heat uptake, even in the absence of nonlinear feedbacks. Our results illustrate why typical future projections are amenable to pattern scaling, and provide a plausible explanation of why more complicated approaches, such as nonlinear emulators, have only shown marginal improvements in accuracy over simple linear calculations.