Can monthly precipitation interpolation error be reduced by adding periphery climate stations? A case study in China's land border areas

Abstract

Minor interpolation error of spatially continuous precipitation is increasingly in demand to support many climate studies. In this paper, based on the thin-plate smoothing splines (ANUSPLIN), we studied the effects of adding periphery stations on monthly precipitation interpolation errors in China with 184 stations from neighboring countries during 1971–2000. Here, we show that with the exception of the northern piedmont of the Himalayas, the interpolation accuracy of monthly precipitation was improved greatly in China's border areas. Mean absolute error was reduced by an average of 2.8 mm month⁻¹ across 21 withheld stations. By incorporating 184 foreign stations into interpolation, the overestimated precipitation in the northern piedmont of the Himalayas can be primarily attributed to the drawback that ANUSPLIN had difficulty estimating sharply varying rain shadows in the Qinghai–Tibetan Plateau. Overall, these results mentioned above emphasized the importance of periphery stations to generate gridded precipitation datasets and the limitation of ANUSPLIN to simulate terrain-induced climate transitions.