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

Many near-real-time applications such as monitoring flash floods and landslides, scheduling agricultural activities, etc. 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 an intercomparison of forecast and reanalysis precipitation products conducted in this study investigating the statistical accuracy and hydrological utility of three precipitation datasets from ECMWF real-time high-resolution (HRES) forecasts, Ensemble Mean (EM) forecasts, and reanalysis (ERA5) over Türkiye and Germany between 2007 and 2018 using ground-based observed data as truth. ERA5 precipitation 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.