The existence and magnitude of the recently suggested global warming hiatus, or slowdown, have been strongly debated1,2,3. Although various physical processes4,5,6,7,8 have been examined to elucidate this phenomenon, the accuracy and completeness of observational data that comprise global average surface air temperature (SAT) datasets is a concern9,10. In particular, these datasets lack either complete geographic coverage or in situ observations over the Arctic, owing to the sparse observational network in this area9. As a consequence, the contribution of Arctic warming to global SAT changes may have been underestimated, leading to an uncertainty in the hiatus debate. Here, we constructed a new Arctic SAT dataset using the most recently updated global SATs2 and a drifting buoys based Arctic SAT dataset11 through employing the ‘data interpolating empirical orthogonal functions’ method12. Our estimate of global SAT rate of increase is around 0.112 °C per decade, instead of 0.05 °C per decade from IPCC AR51, for 1998–2012. Analysis of this dataset shows that the amplified Arctic warming over the past decade has significantly contributed to a continual global warming trend, rather than a hiatus or slowdown.
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We thank the National Oceanographic and Atmospheric Administration (NOAA) and the National Centers for Environmental Information (NCEI) for providing the updated global surface air temperature dataset; and the International Arctic Buoy Programme (IABP) and the NASA EOS program Polar Exchange at the Sea Surface (POLES) for making available the Arctic temperature dataset. Special thanks also go to L. Bian and X. Shao for their comments on this research. We also thank the ‘Explorer 100’ cluster system of Tsinghua National Laboratory for Information Science and Technology for computation support. This work was supported by the State Key Development Program for Basic Research of China (grant no. 2013CBA01805), by the National Science Foundation for Young Scientists of China (grant no. 41305054), the Tsinghua University Initiative Scientific Research Program (grant no. 20131089356) and by the China Meteorological Administration Special Public Welfare Research Fund (GYHY201306019) as well as the Tsinghua Global Scholars Fellowship Program. X.Z. was supported by the US NSF (grant numbers ARC-1023592 and ARC-1107509).