Abstract
AbstractGlobal 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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
