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Abstract

Global mean surface temperature (GMST) fluctuates over decadal to multidecadal time scales. Patterns of internal variability are partly responsible, but the relationships can be conflated by anthropogenically forced signals. Here we adopt a physically based method of separating internal variability from forced responses to examine how trends in large‐scale patterns, specifically the Interdecadal Pacific Oscillation (IPO) and Atlantic Multidecadal Variability (AMV), influence GMST. After removing the forced responses, observed variability of GMST is close to the central estimates of Coupled Model Intercomparison Project phase 5 simulations, but models tend to underestimate IPO variability at time scales >10 years, and AMV at time scales >20 years. Correlations between GMST trends and these patterns are also underrepresented, most strongly at 10‐ and 35‐year time scales, for IPO and AMV, respectively. Strikingly, models that simulate stronger variability of IPO and AMV also exhibit stronger relationships between these patterns and GMST, predominately at the 10‐ and 35‐year time scales, respectively.

Item Type:	Article
Authors/Creators:	Kajtar, JB and Collins, M and Frankcombe, LM and England, MH and Osborn, TJ and Juniper, M
Keywords:	CMIP5, global temperature, climate variability, global mean surface temperature, interdecadal Pacific Oscillation, Atlantic multidecadal variability
Journal or Publication Title:	Geophysical Research Letters
Publisher:	Amer Geophysical Union
ISSN:	0094-8276
DOI / ID Number:	https://doi.org/10.1029/2018GL081462
Copyright Information:	Copyright 2019 American Geophysical Union
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