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A Quantitative Definition of Global Warming Hiatus and 50-Year Prediction of Global-Mean Surface Temperature

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  • 1 College of Physical and Environment Oceanography, Ocean University of China, and Key Laboratory of Marine Science and Numerical Modeling, and First Institute of Oceanography, State Oceanic Administration, and Meteorology Bureau of Jiaozhou, Qingdao, China
  • | 2 Key Laboratory of Marine Science and Numerical Modeling, and First Institute of Oceanography, State Oceanic Administration, Qingdao, China
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Abstract

Recent global warming hiatus has received much attention; however, a robust and quantitative definition for the hiatus is still lacking. Recent studies by Scafetta, Wu et al., and Tung and Zhou showed that multidecadal variability (MDV) is responsible for the multidecadal accelerated warming and hiatuses in historical global-mean surface temperature (GMST) records, though MDV itself has not received sufficient attention thus far. Here, the authors introduce four key episodes in GMST evolution, according to different phases of the MDV extracted by the ensemble empirical-mode decomposition method from the ensemble HadCRUT4 monthly GMST time series. The “warming (cooling) hiatus” and “typical warming (cooling)” periods are defined as the 95% confidence intervals for the locations of local MDV maxima (minima) and of their derivatives, respectively. Since 1850, the warming hiatuses, cooling hiatuses, and typical warming have already occurred three times and the typical cooling has occurred twice. At present, the MDV is in its third warming-hiatus period, which started in 2012 and would last until 2017, followed by a 30-yr cooling episode, while the trend will sustain the current steady growth in the next 50 years. Their superposition presents steplike rising since 1850. It is currently ascending a new height and will stay there until the next warming phase of the MDV carries it higher.

Denotes Open Access content.

Supplemental information related to this paper is available at the Journals Online website: http://dx.doi.org/10.1175/JAS-D-14-0296.s1.

Corresponding author address: Fangli Qiao, Professor of Physical Oceanography, First Institute of Oceanography, State Oceanic Administration, 6 Xian-Xia-Ling Road, Qingdao 266061, China. E-mail: qiaofl@fio.org.cn

Abstract

Recent global warming hiatus has received much attention; however, a robust and quantitative definition for the hiatus is still lacking. Recent studies by Scafetta, Wu et al., and Tung and Zhou showed that multidecadal variability (MDV) is responsible for the multidecadal accelerated warming and hiatuses in historical global-mean surface temperature (GMST) records, though MDV itself has not received sufficient attention thus far. Here, the authors introduce four key episodes in GMST evolution, according to different phases of the MDV extracted by the ensemble empirical-mode decomposition method from the ensemble HadCRUT4 monthly GMST time series. The “warming (cooling) hiatus” and “typical warming (cooling)” periods are defined as the 95% confidence intervals for the locations of local MDV maxima (minima) and of their derivatives, respectively. Since 1850, the warming hiatuses, cooling hiatuses, and typical warming have already occurred three times and the typical cooling has occurred twice. At present, the MDV is in its third warming-hiatus period, which started in 2012 and would last until 2017, followed by a 30-yr cooling episode, while the trend will sustain the current steady growth in the next 50 years. Their superposition presents steplike rising since 1850. It is currently ascending a new height and will stay there until the next warming phase of the MDV carries it higher.

Denotes Open Access content.

Supplemental information related to this paper is available at the Journals Online website: http://dx.doi.org/10.1175/JAS-D-14-0296.s1.

Corresponding author address: Fangli Qiao, Professor of Physical Oceanography, First Institute of Oceanography, State Oceanic Administration, 6 Xian-Xia-Ling Road, Qingdao 266061, China. E-mail: qiaofl@fio.org.cn

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