4.6 Article

Could CMIP6 climate models reproduce the early-2000s global warming slowdown?

Journal

SCIENCE CHINA-EARTH SCIENCES
Volume 64, Issue 6, Pages 853-865

Publisher

SCIENCE PRESS
DOI: 10.1007/s11430-020-9740-3

Keywords

CMIP6 climate models; Global warming; Global warming slowdown; Hiatus; Climate natural variability; Anthropogenic warming trend

Funding

  1. National Natural Science Foundation of China [41806043, 41821004, 41906029]
  2. Basic Scientific Fund for National Public Research Institutes of China [2019Q08]
  3. Basic Scientific Fund for National Public Research Institute of China [2019S06]
  4. National Program on Global Change and Air-Sea Interaction [GASI-IPOVAI-06]

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The study found that although there have been some improvements in the CMIP6 models compared to CMIP5, most models still fail to reproduce the global warming slowdown. However, the models that were able to successfully reproduce the slowdown demonstrated relatively high skills in simulating the long-term warming trend and three key-scale natural variabilities.
The unexpected global warming slowdown during 1998-2013 challenges the existing scientific understanding of global temperature change mechanisms, and thus the simulation and prediction ability of state-of-the-art climate models since most models participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5) cannot simulate it. Here, we examine whether the new-generation climate models in CMIP6 can reproduce the recent global warming slowdown, and further evaluate their capacities for simulating key-scale natural variabilities which are the most likely causes of the slowdown. The results show that although the CMIP6 models present some encouraging improvements when compared with CMIP5, most of them still fail to reproduce the warming slowdown. They considerably overestimate the warming rate observed in 1998-2013, exhibiting an obvious warming acceleration rather than the observed deceleration. This is probably associated with their deficiencies in simulating the distinct temperature change signals from the human-induced long-term warming trend and or the three crucial natural variabilities at interannual, interdecadal, and multidecadal scales. In contrast, the 4 models that can successfully reproduce the slowdown show relatively high skills in simulating the long-term warming trend and the three key-scale natural variabilities. Our work may provide important insight for the simulation and prediction of near-term climate changes.

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