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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:	Refereed Article
Keywords:	CMIP5, global temperature, climate variability, global mean surface temperature, interdecadal Pacific Oscillation, Atlantic multidecadal variability
Research Division:	Earth Sciences
Research Group:	Atmospheric sciences
Research Field:	Atmospheric dynamics
Objective Division:	Environmental Policy, Climate Change and Natural Hazards
Objective Group:	Understanding climate change
Objective Field:	Climate variability (excl. social impacts)
UTAS Author:	Kajtar, JB (Dr Jules Kajtar)
ID Code:	133144
Year Published:	2019
Web of Science® Times Cited:	20
Deposited By:	Oceans and Cryosphere
Deposited On:	2019-06-13
Last Modified:	2019-07-23
Downloads:	20 View Download Statistics