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. New precipitation ( P ) datasets are released regularly, followinginnovations in weather forecasting models, satellite retrieval methods, andmulti-source merging techniques. Using the conterminous US as a case study,we evaluated the performance of 26 gridded (sub-)daily P datasets to obtaininsight into the merit of these innovations. The evaluation was performed ata daily timescale for the period 2008–2017 using the Kling–Gupta efficiency(KGE), a performance metric combining correlation, bias, and variability. Asa reference, we used the high-resolution (4 km) Stage-IV gauge-radar P dataset. Among the three KGE components, the P datasets performed worstoverall in terms of correlation (related to event identification). In termsof improving KGE scores for these datasets, improved P totals (affectingthe bias score) and improved distribution of P intensity (affecting thevariability score) are of secondary importance. Among the 11 gauge-corrected P datasets, the best overall performance was obtained by MSWEP V2.2,underscoring the importance of applying daily gauge corrections andaccounting for gauge reporting times. Several uncorrected P datasetsoutperformed gauge-corrected ones. Among the 15 uncorrected P datasets, thebest performance was obtained by the ERA5-HRES fourth-generation reanalysis,reflecting the significant advances in earth system modeling during the lastdecade. The (re)analyses generally performed better in winter than in summer,while the opposite was the case for the satellite-based datasets. IMERGHH V05performed substantially better than TMPA-3B42RT V7, attributable to the manyimprovements implemented in the IMERG satellite P retrieval algorithm.IMERGHH V05 outperformed ERA5-HRES in regions dominated by convective storms,while the opposite was observed in regions of complex terrain. The ERA5-EDAensemble average exhibited higher correlations than the ERA5-HRESdeterministic run, highlighting the value of ensemble modeling. The WRFregional convection-permitting climate model showed considerably moreaccurate P totals over the mountainous west and performed best among theuncorrected datasets in terms of variability, suggesting there is merit inusing high-resolution models to obtain climatological P statistics. Ourfindings provide some guidance to choose the most suitable P dataset for aparticular application.

Daily evaluation of 26 precipitation datasets using Stage-IV gauge-radar data for the CONUS