Chinese scientists: Most climate models fail to reproduce global warming slowdown

A new study by a team of Chinese climate scientists and published by Science China Earth Sciences, a journal cosponsored by the Chinese Academy of Sciences and the National Natural Science Foundation of China, reveals the failure of most of the latest climate models to reproduce the global warming slowdown during 1998–2013.

Warming rates during the rapid warming period (1975/01–1997/12) (a) and the warming hiatus period (1998/01–2013/12) (b) and the warming rate change during the hiatus period relative to the rapid warming period (c). Source: Wei et al. (2021)

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


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.

Full paper ($)

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April 24, 2021 at 04:03AM