Predictability of the recent slowdown and subsequent recovery of large-scale surface warming using statistical methods

Michael E. Mann, Byron A. Steinman, Sonya K. Miller, Leela M. Frankcombe, Matthew H. England, Anson H. Cheung

Research output: Contribution to journalArticlepeer-review

13 Scopus citations


The temporary slowdown in large-scale surface warming during the early 2000s has been attributed to both external and internal sources of climate variability. Using semiempirical estimates of the internal low-frequency variability component in Northern Hemisphere, Atlantic, and Pacific surface temperatures in concert with statistical hindcast experiments, we investigate whether the slowdown and its recent recovery were predictable. We conclude that the internal variability of the North Pacific, which played a critical role in the slowdown, does not appear to have been predictable using statistical forecast methods. An additional minor contribution from the North Atlantic, by contrast, appears to exhibit some predictability. While our analyses focus on combining semiempirical estimates of internal climatic variability with statistical hindcast experiments, possible implications for initialized model predictions are also discussed.

Original languageEnglish (US)
Pages (from-to)3459-3467
Number of pages9
JournalGeophysical Research Letters
Issue number7
StatePublished - Apr 16 2016

Bibliographical note

Funding Information:
B.A.S. acknowledges support by the U.S. National Science Foundation (EAR-1447048). M.H.E. and L.M.F. acknowledge support from the Australian Research Council (FL100100214). A.H.C. acknowledges support from the U.S. National Science Foundation (AGS-1263225).

Publisher Copyright:
© 2016. American Geophysical Union. All Rights Reserved.


  • climate change
  • global warming
  • internal variability
  • predictability
  • temperature extremes


Dive into the research topics of 'Predictability of the recent slowdown and subsequent recovery of large-scale surface warming using statistical methods'. Together they form a unique fingerprint.

Cite this