Abstract
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 the 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.This article is part of a discussion meeting issue ‘Intensification of short-duration rainfall extremes and implications for flash flood risks’.
Highlights
Extreme precipitation at sub-daily scales can have significant flooding impacts in both urban and rural environments
We find little improvement with grid refinement in simulated 3 h extreme precipitation accumulations when held to that expectation, at least over the conterminous United States (CONUS) region
Increasing global atmospheric model horizontal resolution increases the magnitude of simulated extreme sub-daily precipitation
Summary
Extreme precipitation at sub-daily scales can have significant flooding impacts in both urban and rural environments. [26] for extreme daily precipitation and further explored in this paper for extreme sub-daily precipitation, the order of operations in calculating gridded observational metrics can affect their magnitude and the interpretation of model quality In this first evaluation, we confine our analyses to the conterminous United States (CONUS) and the winter (DJF) and summer (JJA). A different reference set must be calculated for each model further adding to the complexity of the evaluation process This order of operation is not always practical, especially for sub-daily extremes due to the high computational cost of regridding and/or the availability of the high-frequency observational data itself. Uncertainty in the error patterns from individual realizations is comparably low
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