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Publication Date
1 March 2021

Evaluation of extreme subdaily precipitation in high-resolution global climate model simulations

Subtitle
Simulated extreme precipitation increases as horizontal resolution increases but appropriately constructed model skill metrics do not significantly change.
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Science

We examine the resolution dependence of errors in extreme sub-daily precipitation in available high-resolution climate models. We find that simulated extreme precipitation increases as horizontal resolution increases but that appropriately constructed model skill metrics do not significantly change. We find little evidence that simulated extreme winter or summer storm processes significantly improve with resolution because the model performance changes identified are consistent with expectations from scale-dependence arguments alone. We also discuss the implications of these scale-dependent limitations on the interpretation of simulated extreme precipitation.

Impact

Horizontal resolution in the CMIP6 HighResMIP models does not improve the simulation of sub-daily extreme precipitation in the winter and summer seasons over the CONUS region nearly as much as expected. This is revealed when one considers that metrics of extreme precipitation for model evaluation must be resolution-dependent. On the other hand, these resolution-dependent metrics reveal that the model performance is not generally biased dry as is commonly believed. While this complication makes model intercomparison more tedious and is recommended as a best practice, it also serves as the basis for a scaling factor that can bring the magnitude of model projections to much finer resolutions even to a pointwise scale.

Summary

Despite the enhanced realism of extreme storms in models at high resolution, extreme precipitation magnitudes are not greatly affected except by that predicted by resolution scaling expectations. Admittedly this is not fully understood and requires further examination.

Point of Contact
Michael Wehner
Institution(s)
Lawrence Berkeley National Laboratory (LBNL)
Funding Program Area(s)
Publication