# Evaluation of Global Precipitation Products over Wabi Shebelle River Basin, Ethiopia
## 5 Conclusions  
In the current study, a total of six GPPs, three from raw global precipitation products (CHIRPSv2, TAMSATv3, and PERSIANN_CDR) and three from downscaled global precipitation products (CHIRPS_D, TAMSAT_D, and PERSIANN_CDR_D), were used. A bilinear method was applied to downscale the coarse spatial resolution of GPPs to 1 km resolution pixels. Categorical and quantitative evaluation index techniques were applied to WSRB, Ethiopia. The primary objective of the study was to assess the performance of the global precipitation products and their downscaled versions at different temporal scales compared to ground gauge stations.  
The results indicated that the performance of global precipitation products is affected by factors such as the gauge density, spatiotemporal scale, and type of satellite algorithm. The daily evaluations were executed poorly in the majority of gauge stations. According to the evaluation parameters at the daily timescale, the downscaled GPPs performed best in terms of all statistical indicators. The evaluation assessment clearly indicated that TAMSAT_D was the best performer in terms of RMSE, CC, and scatter plots (\(R^{2}\)). On the other hand, PERSIANN_CDR_D showed a relatively good performance with a lower, positive Pbias and higher POD values compared to other products. CHIRPSv2 showed the worst performance at a daily timescale. The results indicated that the performance of the GPPs and their downscaled versions increased when daily data were aggregated to monthly data. Therefore, CHIRPS-D performed better than other products with a minimum error value (RMSE) and higher CC and \(R^{2}\). However, PERSIANN_CDR_D presented a low Pbias and the highest POD values on daily and monthly timescales. In spatial mismatch analysis, the bias and RMSE estimated using rainfall data from individual rain gauges exhibited different magnitudes over the spatial average for PERSIANN_CDR, indicating that individual gauge data could not accurately estimate the product.  
Overall, the performance of downscaled global precipitation products was better than that of the coarser-resolution products according to all statistical parameters. TAMSAT-D and CHIRPS-D products were the best-performing GPPs in reproducing the daily and monthly rainfall data, respectively. PERSIANN_CDR also accurately captured the extreme rainfall over the study area. This study provides a relatively long consistent and homogeneous timeseries rainfall dataset for climatology analysis and hydrological applications with a 1 km resolution for the study area. Although satellite precipitation products provide information at a high spatial resolution, they are lower in precision. On the other hand, gauges provide accurate point measurements but have limited spatial representativity. Therefore, for future studies, we recommend merging the downscaled product to improve the data availability in terms of accuracy, spatial distribution, and accumulated rainfall volume over the data-scarse Wabi Shebelle River Basin, Ethiopia, with a complex terrain, as well as other regions with a similar climate and topographical location.  
[PERSON] and [PERSON] conceptualized the study, framed the design, conducted data analysis, and wrote the manuscript. [PERSON], [PERSON] and A.A. conceptualized the study and provided satellite data. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
All data models and code generated or used during the paper in the summited article.  
This research was financially supported by the Africa Center of Excellence for Water Management (ACEWM) hosted by Addis Ababa University. The authors acknowledge the National Meteorological Agency (NMA) for providing a relevant data.