## 5 Conclusions  
The performance of four gridded precipitation products, namely, CRU TS, ERA-5, IMERG7, and MSWEP2.8, was evaluated in this study. The data validation assessment was performed using four statistical matrices, time series graphs, and interpolation of the precipitation spatial distribution patterns. The precipitation products' skills were evaluated on a temporal scale, and then provincial and elevation gradient-based assessments were conducted to address the spatial performance of each dataset. The results revealed the clear superiority of IMERG7 products over the other datasets across the study region, with consistently higher CC and KGE and lower RMSE across all the provinces and elevation-based regions. MSWE2.8 also closely followed IMERG7 in precipitation estimation. In contrast, ERA-5 exhibited comparatively poorer performance in GB and KPK provinces, and CRU TS showed a lack of skills in Punjab, Sindh, and Balochistan provinces. The deviation of the precipitation estimates of the datasets from the RG records was observed, with the tendency of overestimations; however, CRU TS exhibited underestimations in Punjab, Sindh, and Balochistan, while MSWEP2.8 showed a similar tendency in KPK, Punjab, and Sindh provinces. Furthermore, the influence of the elevation gradients and climatic conditions on the product performance was evident in this study. All the GPPs except CRU TS, whose performance was not consistent, performed well in the southern plains (0-500 m elevation) and considerably overestimated in the northern high-elevation and glacier-rich regions. According to the temporal scale analysis, IMERG7, MSWEP2.8 and ERA-5 demonstrated better precipitation detection skills at a monthly scale, followed by the winter season, pre-monsoon, and monsoon season, respectively, while CRU-TS showed relatively better performance in the monsoon season than the pre-monsoon. However,during the post-monsoon season, all the datasets showed weak alignment with the reference data, with considerable overestimations. Based on detailed analysis, we advocate the use of the monthly precipitation estimates of IMERG7 and MSWEP2.8 for hydro-climatic studies in this region and other parts that feature the same climatic and topographic conditions.  
Conceptualization, H.A. and W.S.; data curation, H.A. and W.S.; formal analysis, H.A., K.X., Y.W., W.S., L.C., T.F., S.L. and M.A.; methodology, H.A. and W.S.; funding acquisition, W.S.; writing--original draft, H.A. and W.S.; and writing--review and editing, W.S. and H.A. All authors have read and agreed to the published version of the manuscript.  
Supported by the Hunan Province Water Conservancy Science and Technology Project (No. XSKJ2023059-04).  
All satellite remote sensing data used in this study are openly and freely available and their sources are mentioned in the datasets section of the methodology, while the ground observation data can only be acquired from the Pakistan Meteoritical Department.  
We are grateful to the Pakistan Meteorological Department for providing selected ground station data and the developers of selected global precipitation datasets for making them easily accessible.  
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.