Understanding the characteristics of precipitation datasets in a given region is crucial for hydrological studies. This study focuses on the British Columbia (BC) Province in Canada and evaluates the statistical characteristics of precipitation data from three gridded precipitation datasets: the Pacific Climate Impacts Consortium’s northwestern North America meteorological dataset (PNWNAmet), Global Precipitation Measurement (GPM), and Global Precipitation Climatology Centre (GPCC). These precipitation datasets at both daily and monthly scales were compared with point observation data from the Global Historical Climatology Network (GHCN). For the daily-scale comparison of three precipitation datasets, seven indices of extreme precipitation were computed at ten observation points. Out of eleven locations for the monthly analysis, GPCC showed the lowest RMSE at six locations (five of them were in the northern to central BC), and PNWNAmet showed the lowest RMSE at four locations (three of them were in the southern BC), suggesting GPCC’s superior agreements with GHCN at the northern and central part of BC and PNWNAmet’s better agreements with GHCN at the southern part of BC. The comparison of monthly precipitation averaged over BC showed that PNWNAmet offers higher monthly precipitation than GPCC and GPM, while the variability of annual precipitation among the three datasets is similar. Spatial analysis of precipitation–elevation relationships revealed the value of considering both elevation and distance from the coast in evaluating the precipitation–elevation relationships.
Ogawa et al. (Sun,) studied this question.