Origin and Limits of Invariant Warming Patterns in Climate Models
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clim-JCLI-D-24-0683.1.pdf
Description
Published version
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16.28 MB
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Adobe PDF
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Author(s)
Giani, Paolo
Fiore, Arlene M
Flierl, Glenn
Ferrari, Raffaele
Selin, Noelle E
Date Issued
April 1, 2026
Journal
Journal of Climate
Publisher
American Meteorological Society
Citation
Giani, P., A. M. Fiore, G. Flierl, R. Ferrari, and N. E. Selin, 2026: Origin and Limits of Invariant Warming Patterns in Climate Models. J. Climate, 39, 1681–1701.
Version
Final published version
Abstract
Climate models exhibit an approximately invariant surface warming pattern in typical end-of-century projections. This feature 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 arises from the combination of exponential forcing, linear feedbacks, a constant forcing pattern, and linear changes in heat transport. These conditions are approximately met in typical Coupled Model Intercomparison Project phase 6 (CMIP6) shared socioeconomic pathways (SSPs), except in the Arctic where nonlinear feedbacks are important and in regions where different aerosol projections alter the forcing pattern. In idealized experiments where concentrations of carbon dioxide (CO2) are abruptly increased, such as those used to study the pattern effect, the warming pattern evolves 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.
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DOI of Published Version
https://doi.org/10.1175/JCLI-D-24-0683.1
