Abstract

Abstract Spatial unevenness, especially local unevenness, is a key characteristic of precipitation and has the potential to be a metric to gauge the performance of high-resolution models. In this paper, a local unevenness index (LUI) is proposed to quantify the heterogeneity of precipitation in central and eastern China. The local unevenness of precipitation is dominantly influenced by local topography, and high LUIs spatially correspond to high local terrain relief. Along 30°N, the correlation coefficient between the LUI and local relief reaches 0.893. Stations with large enhancement and steep gradients in precipitation are identified as local maximum (LM) stations. According to the distinct impacts of various scales of terrain, all 59 LM stations are categorized into three groups: the high-elevation group, the edge group, and the eastern isolated-mountain group. The three groups present different distributions of precipitation with altitude: a double-peak pattern in the high-elevation group, a low-altitude peak in the edge group, and a high-altitude peak in the eastern isolated-mountain group. The seasonal variations in all groups are characterized by relatively more precipitation occurring at higher (lower) elevations in the warm (cold) season. The high-elevation group shows a general increasing (decreasing) frequency tendency with altitude in the warm (cold) season. The low-altitude (high-altitude) frequency peak in the edge (eastern isolated-mountain) group is more prominent in the cold (warm) season. The LUI and LM can be used as straightforward and quantified metrics to measure the performance of high-resolution models in reproducing the local-scale features of precipitation and their seasonal variations. Significance Statement The purpose of this study is to promote the knowledge of precipitation unevenness on a local scale. This is important to hydrological processes and water resource management. Our results provide LUI and LM to quantify the spatial unevenness of precipitation on a local scale and further analyze the climatic characteristics and the seasonal variations of precipitation unevenness over central and eastern China. These metrics can be used as quantitative criteria to evaluate the performance of high-resolution models.

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