Abstract: Precipitation concentration is an important component of precipitation structure. The present study uses daily precipitation data from 1960—2017 to calculate the precipitation concentration index Q and investigate in detail the spatial and temporal characteristics of precipitation concentration in China. In particular, this analysis considers how precipitation concentration is related to both precipitation amount and maritime conditions. The results indicate that China's yearly mean Q value is 0.38, with Q values highest in central China and lower in northern and southern China. Precipitation concentration is higher in winter and autumn, with mean Q values of 0.53 and 0.51, respectively; in contrast, the mean Q values for summer and spring are 0.39 and 0.48, respectively. For China as a whole, the yearly mean Q value is increasing slowly with time; however, yearly mean Q trends exhibit regional variation, with positive and negative temporal trends in southeastern and northwestern China, respectively. The results indicate a negative correlation between precipitation concentration and precipitation amount at both annual and seasonal scales (correlation coefficient of-0.71 at the annual scale). This correlation is strongest in autumn and weakest in winter (correlation coefficients of -0.89 and-0.70, respectively). Moreover, both precipitation concentration and precipitation amount control the area affected by flood and drought. The correlation coefficient between yearly Q and the NINO3.4 index increases and then decreases with increasing lag time, with the strongest correlation (coefficient:0.13) found for a lag time of 2 months. This correlation also exhibits a distinct spatial pattern, with a "-+-" distribution from north to south. Similarly, the correlation coefficient between yearly Q and the Pacific Decadal Oscillation increases and then decreases with increasing lag time; this correlation is strongest (coefficient:0.12) for a lag time of 4 months. This relationship exhibits a negative correlation across most of China.