Spatio-temporal evaluation of gridded precipitation products over Balochistan province in Pakistan

Abstract

Gridded precipitation (P) products provide a promising substitute for ground-based measurements in data-scarce regions such as Balochistan province in Pakistan. This study evaluated the performance of five state-of-the-art gridded P products (CHIRPSv2, MSWEPv2.2, PERSIANN-CDR, ERA5, and 5-KM) in the study area. The P products were evaluated through a point-to-pixel comparison at the monthly, annual, and seasonal temporal scales using data from 13 gauges. The modified Kling-Gupta efficiency (KGE’), along with its individual components, the linear correlation (r), bias ratio (β), and variability ratio (γ), and the root mean square error (RMSE), were used as statistical indices to evaluate the performance of the P products. The results of the study revealed that generally, MSWEPv2.2 (daily gauge-corrected) presented the best spatio-temporal KGE’ performance over most of the stations and across the province. The reanalysis dataset of ERA5 closely followed MSWEPv2.2 and was the best-performing product at the annual temporal scale. CHIRPSv2 (monthly gauge-corrected), PERSIANN-CDR (relies on secondary sources of gauge data), and 5-KM (daily gauge-based gridded product) showed relatively poor KGE’ performance. However, 5-KM presented the best performance for the β component of the KGE’, overall. RMSE results were different than those of the KGE’. Generally, CHIRPSv2 and PERSIANN-CDR outperformed MSWEPv2.2 and ERA5 at the temporal scales. Similar results were obtained for the spatial scale at the wetter stations that are located in eastern Balochistan. However, MSWEPv2.2 and ERA5 presented better spatial RMSE performance in the western drier stations. As far as 5-KM is concerned, it generally showed the weakest RMSE performance at all the spatio-temporal scales across the province. The results of this study confirm that it is difficult to point out a single best-performing P product that performs the best across regions with different climates and topographical gradients and at different temporal scales. However, overall, MSWEPv2.2 and ERA5 are found to be most acceptable in the study area.