Investigating the comparative utility of ECMWF precipitation forecasts as an alternative to reanalysis data.

Many near-real-time applications require near-real-time precipitation estimates, and in the absence of reanalysis datasets due to their usually delayed release, precipitation forecasts could offer a potential alternative. This motivates the inter-comparison of forecast and reanalysis products conducted in this study investigating the statistical accuracy and hydrological utility of three precipitation datasets from European Centre for Medium-Range Weather Forecasts (ECMWF) [i.e. high-resolution (HRES) forecasts, Ensemble Mean (EM) forecasts, and ECMWF's 5th generation reanalysis (ERA5)] over Türkiye and Germany for 2007–2018 using ground-based observed data as truth. ERA5 has higher bias than HRES and EM in both regions while HRES has the lowest daily correlations. ERA5 (EM) shows the highest hydrological utility in Germany (Türkiye). ERA5 showed improved monthly correlations compared to forecasts; the improvement over Germany (i.e. 0.02) is better than over Türkiye (~0.01). Wetness and topographical complexity of a region affect precipitation estimation uncertainty there. [ABSTRACT FROM AUTHOR]