Seasonal representation of extreme precipitation indices over the United States in CMIP6 present-day simulations

Phase 6 (CMIP6) models. We separately evaluate summer and winter precipitation over the United States (US) with a comprehensive set of extreme precipitation indices, including an assessment of precipitation frequency, intensity and spatial structure. The observations exhibit significant differences in their estimates of area-average intensity distributions and spatial patterns of the mean and extremes of precipitation over the US.

In general, the CMIP6 multi-model mean performs better than most individual models at capturing daily precipitation distributions and extreme precipitation indices, particularly in comparison to gauge-based data. Also, the representation of the extreme precipitation indices by the CMIP6 models is better in the summer than winter. Although the 'standard' horizontal-resolution can vary significantly across CMIP6 models, from similar to 0.7 degrees to similar to 2.8 degrees, we find that resolution is not a good indicator of model performance.

Overall, our results highlight common biases in CMIP6 models and demonstrate that no single model is consistently the most reliable across all indices.