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- Title
Daily evaluation of 26 precipitation datasets using Stage-IV gauge-radar data for the CONUS.
- Authors
Beck, Hylke E.; Ming Pan; Roy, Tirthankar; Weedon, Graham P.; Pappenberger, Florian; van Dijk, Albert I. J. M.; Huffman, George J.; Adler, Robert F.; Wood, Eric F.
- Abstract
New precipitation (P) datasets are released regularly, following innovations in weather forecasting models, satellite retrieval methods, and multi-source merging techniques. Using the conterminous US as a case study, we evaluated the performance of 26 gridded (sub-)daily P datasets to obtain insight in the merit of these innovations. The evaluation was performed at a daily timescale for the period 2008--2017 using the Kling-Gupta Efficiency (KGE), a performance metric combining correlation, bias, and variability. As reference, we used the high-resolution (4 km) Stage-IV gauge-radar P dataset. Among the three KGE components, the P datasets performed worst overall in terms of correlation (related to event identification). In terms of improving KGE scores for these datasets, improved P totals (affecting the bias score) and improved distribution of P intensity (affecting the variability 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 and accounting for gauge reporting times. Several uncorrected P datasets outperformed gauge-corrected ones. Among the 15 uncorrected P datasets, the best performance was obtained by the fourth-generation reanalysis ERA5-HRES, reflecting the significant advances in earth system modeling during the last decade. IMERGHH V05 performed substantially better than TMPA-3B42RT V7, attributable to the many improvements 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-EDA ensemble average exhibited higher correlations than the ERA5- HRES deterministic run, highlighting the value of ensemble modeling. The regional convection-permitting climate model WRF showed considerably more accurate P totals over the mountainous west and performed best among the uncorrected datasets in terms of variability, suggesting there is merit in using high-resolution models to obtain climatological P statistics. Our findings can be used as a guide to choose the most suitable P dataset for a particular application.
- Subjects
METEOROLOGICAL precipitation; GREEN technology; HYDRAULIC models; HYDROLOGIC models; CLIMATE change
- Publication
Hydrology & Earth System Sciences Discussions, 2018, p1
- ISSN
1812-2108
- Publication type
Article
- DOI
10.5194/hess-2018-481