Scaling of Extreme Precipitation with Temperature Based on the CONUS404 Data
How the hydrological cycle and extreme precipitation respond to variations and changes in temperature is a question central to both the research community and decision-makers in multiple sectors. Conventional climate and numerical weather prediction models struggle to reproduce how extreme precipitation intensity scales with temperature at the weather timescale, likely due to parameterized convection in coarse-resolution models. Multiple lines of evidence suggest that convection-permitting (km scale) models can improve the simulation of extreme precipitation, but it is not clear whether such improvements can propagate or translate to improved simulation of the extreme precipitation–temperature scaling relationship. An opportunity to address this question arises with the recent availability of the CONUS404 data from a convection-permitting (4-km grid spacing) WRF downscaling simulation driven by ERA5 over the conterminous US in the past 40-plus years (Oct. 1979 to Sep. 2021). Taking advantage of this dataset, we investigate the summertime extreme precipitation–temperature scaling relationship in the convection-permitting WRF model by comparing it with the relationship obtained from observational data and ERA5. We also explore whether the extreme precipitation–temperature scaling relationship at the weather timescale may offer relevant information on how precipitation extremes may change with temperature at the climate timescale. Based on high-frequency hourly data, we employ binned scaling analysis to examine how extreme precipitation varies with temperature and its dependence on atmospheric moisture limitation (as reflected by the atmospheric saturation deficit). We select six national climate assessment regions and compare the relationship in WRF simulations with NASA’s Integrated Multi-satellitE Retrievals for GPM (IMERG) observations and the ERA5 data. Similar to findings from previous studies, extreme precipitation generally exhibits a monotonic increase with temperature when conditioned on saturation deficit, and negative scaling at high temperature can be attributed to the increase of saturation deficit with temperature. Under saturated conditions, the simulated scaling relationship shows a much higher degree of regional dependence than in observations, despite improved extreme precipitation representation in the convection-permitting WRF simulations. Focusing on conditions in saturated atmospheres, we compare the extreme precipitation–temperature scaling ratio (at the weather timescale) with changes of extreme precipitation intensity at the decadal timescale. Preliminary results show a moderate degree of correlation between the two, suggesting the relevance of the weather-scale extreme metrics as a potential constraint for climate-induced changes.