Warming of the climate is now unequivocal. The water holding capacity of the atmosphere increases by about 7% per °C of warming, which in turn raises the expectation of more intense extreme rainfall events. Meeting the demand for robust projections for extreme short-duration rainfall is challenging, however, because of our poor understanding of its past and future behaviour. The characterization of past changes is severely limited by the availability of observational data. Climate models, including typical regional climate models, do not directly simulate all extreme rainfall producing processes, such as convection. Recently developed convection-permitting models better simulate extreme precipitation, but simulations are not yet widely available due to their computational cost, and they have their own uncertainties. Attention has thus been focused on precipitation–temperature relationships in the hope of obtaining more robust extreme precipitation projections that exploit higher confidence temperature projections. However, the observed precipitation–temperature scaling relationships have been established almost exclusively by linking precipitation extremes with day-to-day temperature variations. These scaling relationships do not appear to provide a reliable basis for projecting future precipitation extremes. Until better methods are available, the relationship of the atmosphere's water holding capacity with temperature provides better guidance for planners in the mid-latitudes, albeit with large uncertainties.
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We thank J. Fyfe and K. Anderson for helpful comments on the manuscript.
The authors declare no competing financial interests.
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Zhang, X., Zwiers, F., Li, G. et al. Complexity in estimating past and future extreme short-duration rainfall. Nature Geosci 10, 255–259 (2017). https://doi.org/10.1038/ngeo2911
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