Journal of Hydrometeorology Publication

A new publication in Journal of Hydrometeorology (Alshehri et al., 2024) identifies how weather types, or different synoptic weather systems such as tropical storms, influence the occurrence of extreme rainfall within the continental United States. Congratulations to authors associated with the Center for Hydrologic Innovations!

• Abstract: A critical task to better quantify changes in precipitation (P) mean and extreme statistics due to global warming is to gain insights into the underlying physical generating mechanisms (GMs). Here, the dominant GMs associated with daily P recorded at 2861 gauges in the conterminous United States from 1980 to 2018 were identified from atmospheric reanalyses and publicly available datasets. The GMs include fronts (FRTs), extratropical cyclones (ETCs), atmospheric rivers (ARs), tropical cyclones (TCs), and North American monsoon (NAM). Climatologies of the GM occurrences were developed for the nonzero P (NZP) and annual P maxima (APM) samples, characterizing the marginal and extreme P distributions, respectively. FRT is everywhere the most frequent (45%–75%) GM of NZP followed by ETC (12%–33%). The FRT contribution declines for APM (19%–66%), which are dominated by AR (50%–65%) in western regions and affected by TC (10%–18%) in southern and eastern regions. The GM frequencies exhibit trends with the same signs over large regions, which are not statistically significant except for an increase in FRT (TC) frequency in the northeast (central region). Two-sample tests showed well-defined spatial patterns with regions where 1) both the marginal and extreme P distributions of the two dominant GMs likely belong to different statistical populations and 2) only the marginal or extreme distributions could be considered statistically different. These results were interpreted through L-moments and parametric distributions that adequately model NZP and APM frequency. This work provides useful insights to incorporate mixed populations and nonstationarity in P frequency analyses.