LAUSR

Precipitation is the fundamental source for various research areas, including hydrology, climatology, geomorphology, and ecology, serving essential roles in modelling, distribution, and process analysis. However, the accuracy and precision of spatially distributed precipitation estimates is a critical issue, particularly for daily scale and topographically complex areas. Although many datasets have been developed based on different algorithms and sources are developed for this purpose, determining which of these datasets best reflects actual conditions is quite challenging. This study, hence, aims to compare the 25 global distributed precipitation estimates (gridded, satellite, model, and fused) concerning 221 ground‐based observations based on the ranking of 18 continuous (evaluation statistics), eight categorical (precipitation indices), and two seasonality metric (high and low precipitation). Upon examining the results, gridded and model precipitation data including APHRODITE (Asian Precipitation—Highly‐Resolved Observational Data Integration Towards Evaluation), CPC (Global Unified Gauge‐Based Analysis of Daily Precipitation), ERA5‐Land (ECMWF Reanalysis 5th Generation for Lands), and CFSR (Climate Forecast System Reanalysis) occupy the top four positions in continuous metrics. In contrast, satellite data such as PERSIANN‐PDIR (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks), CMORPH (Climate Prediction Center morphing method), IMERG (The Integrated Multi‐Satellite Retrievals for GPM), and TRMM‐TMPA (Tropical Rainfall Measuring Mission/Multi‐satellite Precipitation Analysis) dominate in the top four positions in categorical metrics. For seasonality of high and low precipitation, fused, gridded, and reanalyses products such as CPC, MSWEP (Multi‐Source Weighted‐Ensemble Precipitation, version 2), HydroGFD (Hydrological Global Forcing Data), CFSR rank among top four. Based on the first five rankings of all metrics, fused (multiple sourced) and gridded datasets accurately reflect the actual situations compared to other precipitation products. Reanalysis (model) and satellite‐based follow this rank, respectively. The results clearly indicate that fused precipitation derived products from multiple sources offer better accuracy and precision in representing the spatial distribution of precipitation on a daily scale.