General circulation models (or global climate models, GCMs) and Earth system models (ESMs) are undoubtedly important tools in the present climate science, and information derived from the GCM/ESM simulations is critical in some occasions such as future climate projections.

The GCMs/ESMs have continuously been improved during the past CMIP cycle, but the pace of the model improvement is not as rapid as we might expect, causing systematic errors in the mean state and processes to remain in many models to date. These errors hinder obtaining robust climate change signals in models, and therefore a comprehensive assessment of the future change associated with global warming, as was done in the IPCC Sixth Assessment Report (AR6), requires combining multiple lines of evidence that act to narrow uncertainties.

Yet, some of the evidence relies on the ensemble of GCM simulations, implying that the value of climate models in robustly estimating climate change signals is not downgraded even in the presence of model errors. Credibility to GCMs is increased when they can reproduce better climate changes observed during the historical period.

It is, however, not straightforward to measure the models’ reproducibility because observed changes are often the results of both externally forced climate response and internally generated climate variability. The separation is difficult with GCMs that contain systematic errors and therefore the attribution of observed climate change remains a challenge despite many attribution studies have been carried.

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