A recent study led by Dr Wei and Dr Qiao of the First Institute of Oceanography at the Department of Natural Resources provides an assessment of the performance of recently published CMIP6 models to simulate the slowdown in global warming observed in the early 2000s. This study reveals that the key to simulating and predicting short-term temperate change is to separate and properly simulate the two distinct signals i.e. the human-induced long-term warming trend and natural variabilities, in particular interannual, interdecadal and multidecadal ones. Balance. This work has been published online in Science China Earth Sciences.
After unprecedented warming in the last quarter of the 20th century, global surface temperature growth unexpectedly slowed between 1998 and 2013 despite the sharp increase in greenhouse gas emissions; this phenomenon is called hiatus or slowing down of global warming to be more precise. Slowing global warming challenges existing scientific understanding of the mechanisms of global temperature change, so has been one of the most worrying issues in recent climate research and even the public.
However, the sophisticated and advanced climate models of CMIP5 could not simulate this slowdown in warming. During the period 1998-2013, the models mainly show a rapid warming surge that deviates considerably from the observed flat temperature time series. The models considerably overestimate the rate of warming observed over the recent period. The IPCC AR5 said: “Almost all historical CMIP5 simulations do not reproduce the recent observed warming gap.” As a result, the ability to simulate and predict sophisticated climate models has been called into question.
Now, CMIP6 model data is gradually released since 2020. Newly developed models include a better understanding of the mechanisms of global temperature change, in particular more reasonable physical processes of natural variability. Successful simulations of the global warming slowdown are expected in next-generation models. As data from 28 new models becomes available, there is a need for a timely review of the ability of CMIP6 models to exhibit the recent slowdown in warming.
Against six widely used global surface temperature datasets, the research team at the First Institute of Oceanography at the Department of Natural Resources are evaluating the performance of the 28 newly released CMIP6 models to simulate the recent slowdown in warming and find that the Most CMIP6 models still fail to reproduce. slower warming, although they show encouraging improvements over the CMIP5 models (Figure 1).
In addition, they explored possible reasons for the difficulty of CMIP6 models in simulating the recent slowdown in warming. They reveal that it is associated with model shortcomings in simulating temperature change signals distinct from the long-term human-induced warming trend and / or the three crucial natural variabilities at interannual, interdecadal and multidecadal scales ( Figure 2).
This study reveals that the key to simulating and predicting short-term temperate change is to separate and properly simulate the two distinct signals, i.e. the human-induced long-term warming trend and variability. natural, in particular those at interannual, interdecadal and multidecadal scales. . This suggests that key-scale variabilities require more attention in models, given their vital roles in modulating the change in the rate of warming at decadal to multi-decadal scales. This result can provide important information for simulating and predicting short-term climate change.
Reference: “Could CMIP6 climate models reproduce the slowdown in global warming of the early 2000s?” by Meng Wei, Qi Shu, Zhenya Song, Yajuan Song, Xiaodan Yang, Yongqing Guo, Xinfang Li and Fangli Qiao, April 15, 2021, Science China Earth Sciences.
DOI: 10.1007 / s11430-020-9740-3
This research was funded by the National Natural Science Foundation of China (No. 41806043 and 41821004).