Global-scale multidecadal variability in climate models and observations. Part I: Forced response

Sergey Kravtsov a University of Wisconsin-Milwaukee, Milwaukee, WI
b Shirshov Institute of Oceanology of Russian Academy of Sciences, Moscow, Russia

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Andrew Westgate a University of Wisconsin-Milwaukee, Milwaukee, WI
c Vermont State University - Lyndon, Lyndonville, VT, USA

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Andrei Gavrilov d Gaponov-Grekhov Institute of Applied Physics of Russian Academy of Sciences, Nizhny Novgorod, Russia

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Abstract

Twentieth-century climate variations exhibit, on top of a secular global warming trend, multidecadal variability with globally coherent patterns. Identifying and attributing such patterns requires one to combine modern reanalyses of atmospheric and oceanic observations with estimates of climate response to variable forcings based on ensemble simulations of the twentieth-century climate by the state-of-the-art global coupled models. This contribution is the first installment of the series of papers in which an identical sequence of pattern-recognition methods is applied to a 38-model ensemble of historical simulations within the Coupled Model Intercomparison Project, phases 5 and 6 (CMIP5/6) and to two twentieth-century reanalysis data sets to succinctly describe their global-scale multidecadal variability. The focus here is on characterizing the globally distributed forced response in near-surface air temperature (SAT) and sea-level pressure (SLP) using a combination of the signal-to-noise-maximizing pattern (S/NP) filtering and linear-regression-based rescaling. A particular novel aspect of this work lies in isolating the forced-response structures common across the entire model ensemble versus the residual responses of individual models, thus setting the stage for exploring whether the latter responses can serve as a viable explanation of the observed multidecadal climate teleconnections.

CMIP5/6 models’ common forced response is dominated by two S/NP modes, whose amplitudes differ from model to model. The S/NP-1 describes polar and land-intensified global warming with a slower warming rate prior to mid-60s and a faster warming afterwards. The S/NP-2 component is characterized by a pronounced multidecadal variability without much of a centennial-scale trend and exhibits antisymmetric temperature response between the hemispheres. The two mode’s SLP signature is associated with the downward trend over the Southern Ocean and Antarctica after mid-60s and is much weaker than the SLP background internal variability elsewhere. The CMIP models that have large contributions from S/NP-1 and small contribution from S/NP-2 to their forced response tend to exhibit large twentieth-century global-mean SAT trend, and vice versa. The residual forced responses of individual models unexplained by S/NPs 1 and 2 do exhibit multidecadal variations with the appearance of long-range teleconnections, albeit with a much smaller amplitude than the observed climate’s globally connected deviations from the model estimated forced trends.

© 2025 American Meteorological Society. This is an Author Accepted Manuscript distributed under the terms of the default AMS reuse license. For information regarding reuse and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Sergey Kravtsov, kravtsov@uwm.edu

Abstract

Twentieth-century climate variations exhibit, on top of a secular global warming trend, multidecadal variability with globally coherent patterns. Identifying and attributing such patterns requires one to combine modern reanalyses of atmospheric and oceanic observations with estimates of climate response to variable forcings based on ensemble simulations of the twentieth-century climate by the state-of-the-art global coupled models. This contribution is the first installment of the series of papers in which an identical sequence of pattern-recognition methods is applied to a 38-model ensemble of historical simulations within the Coupled Model Intercomparison Project, phases 5 and 6 (CMIP5/6) and to two twentieth-century reanalysis data sets to succinctly describe their global-scale multidecadal variability. The focus here is on characterizing the globally distributed forced response in near-surface air temperature (SAT) and sea-level pressure (SLP) using a combination of the signal-to-noise-maximizing pattern (S/NP) filtering and linear-regression-based rescaling. A particular novel aspect of this work lies in isolating the forced-response structures common across the entire model ensemble versus the residual responses of individual models, thus setting the stage for exploring whether the latter responses can serve as a viable explanation of the observed multidecadal climate teleconnections.

CMIP5/6 models’ common forced response is dominated by two S/NP modes, whose amplitudes differ from model to model. The S/NP-1 describes polar and land-intensified global warming with a slower warming rate prior to mid-60s and a faster warming afterwards. The S/NP-2 component is characterized by a pronounced multidecadal variability without much of a centennial-scale trend and exhibits antisymmetric temperature response between the hemispheres. The two mode’s SLP signature is associated with the downward trend over the Southern Ocean and Antarctica after mid-60s and is much weaker than the SLP background internal variability elsewhere. The CMIP models that have large contributions from S/NP-1 and small contribution from S/NP-2 to their forced response tend to exhibit large twentieth-century global-mean SAT trend, and vice versa. The residual forced responses of individual models unexplained by S/NPs 1 and 2 do exhibit multidecadal variations with the appearance of long-range teleconnections, albeit with a much smaller amplitude than the observed climate’s globally connected deviations from the model estimated forced trends.

© 2025 American Meteorological Society. This is an Author Accepted Manuscript distributed under the terms of the default AMS reuse license. For information regarding reuse and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Sergey Kravtsov, kravtsov@uwm.edu
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