This work presents the results of the analysis of cold-season precipitation statistics in simulations from the storm-resolving WRF model at 6-km and 1-h resolution over western United States and south-western Canada. Pseudo-future simulations for the 2041-2080 period, constrained by GCMs under the RCP8.5 scenario, have been compared to the 1981-2020 historical simulation. The analysis focuses on the dynamical properties of hyetographs at subdaily scales and on the morphology of individual storms.

The statistical distribution of precipitation intensities in each pixel of the simulation domain is characterized through non-parametric statistical indicators: frequency of wet hours, mean wet-hour precipitation intensity, and the Gini coefficient as a measure of the temporal concentration of the precipitation volume. Additionally, the temporal Fourier power spectra of the hyetographs and spatial power spectra of hourly precipitation maps are analyzed. The half-power period (HPP) and half-power wavelength (HPW) are defined as spectral measures of the characteristic scales of precipitation’s temporal and spatial patterns.

The results show an increase of the mean wet-hour precipitation intensity and of the Gini coefficient in 99% of the pixels, indicating that the seasonal precipitation volume becomes more concentrated within a smaller number of hours with higher precipitation intensity in the future. The changes in terms of the frequency of wet hours are more contrasted across the simulation domain, with the frequency of wet hours decreasing over the Pacific Northwest and the Northern Rockies, and increasing over the other parts of the simulation domain. The changes in the morphology and dynamics of storms are also reflected in the power spectra, which show the spatial and temporal variability increasing proportionally more at finer spatial and temporal scales. The HPW and HPP decrease in the future as a direct consequence of this change in the Fourier power spectra. These projected changes are expected to have consequences, not only in terms of hydrologic impacts, but also in terms of predictability of precipitation patterns.