Spatial and Temporal Variability in Precipitation Concentration over Mainland China, 1961–2017

Abstract

Understanding the patterns and mechanisms of precipitation variations is important for assessing flood and drought risks and for ensuring sustainable water use. Here, we analyzed the characteristics of annual precipitation changes in eight subregions of China using the Mann–Kendall test based on daily precipitation data from 774 rain gauge stations during 1961–2017. Then, we used the monthly precipitation concentration index (PCI) and daily concentration index (CI) to analyze precipitation concentrations. The results are as follows: (1) PCI and CI in northern China generally decreased with time, indicating a uniform precipitation distribution. Notably, the annual precipitation increased significantly in Xinjiang and the Qinghai-Tibet Plateau, which could alleviate future drought. (2) PCI increased and CI decreased in the plain regions of the Yangtze River and Southeast China, exhibiting high CI values with marked increases of annual precipitation. Such heavy rainfall events combined with high rainfall concentrations could increase the flood risk. (3) A significant PCI increase and CI decrease occurred in Southwest China, where annual precipitation decreased significantly. Regular rainfall decreased notably, which could increase the likelihood of drought hazards. (4) Overall, both indices showed negative trends at most stations; precipitation distribution was generally more uniform over China. These findings improve our understanding of extreme rainfall evolution and water resource distribution over China. Furthermore, PCI and CI can serve as warning tools for disaster control and water resource management.

Continued Hydrothermal and Radiative Pressure on Changed Cropland in China

“…We used a stretch display to show the spatial patterns of temperature, precipitation, and solar radiation so as to present more spatial details than the hierarchical maps. The temperature, precipitation, and solar radiation in this study are very consistent with other people's studies in the spatial pattern [40][41][42]. Moreover, the data of this study is expressive in space, which can effectively reflect the elevation and large landform details.…”

Preliminary Utility of the Retrospective IMERG Precipitation Product for Large-Scale Drought Monitoring over Mainland China

“…The daily China Surface Climate Data set version 3.0 (CSCD) possesses the basic meteorological data from 824 ground meteorological stations from 1951 onward, and it can be downloaded from the China Meteorological Data Network (http://data.cma.cn) [53]. The CSCD employs a daily average statistical method to dispose of original data, and it contains diverse precipitation historical records, i.e., 8 p.m. to 8 a.m. (half day), 8 a.m. to 8 p.m. (half day), and 8 p.m. to 8 p.m. (day).…”

“…The CSCD employs a daily average statistical method to dispose of original data, and it contains diverse precipitation historical records, i.e., 8 p.m. to 8 a.m. (half day), 8 a.m. to 8 p.m. (half day), and 8 p.m. to 8 p.m. (day). Moreover, the rigorous quality control method and the Rclimdex software package are utilized to guarantee high CSCD quality [53]. In this study, the observed precipitation dataset was screened and extracted from the CSCD by eliminating certain stations that had >30 days accumulated of missing data in a year and >90 days accumulated of missing data in years.…”

Precipitation Trends and Alteration in Wei River Basin: Implication for Water Resources Management in the Transitional Zone between Plain and Loess Plateau, China

“…where p i is the monthly precipitation in the ith month. According to Equation (1) and referring to the evaluation criteria of PCI, as described by Lu et al [27], if the annual rainfall is concentrated in a single month, the value of PCI will be equal to the maximum of 100. If the annual rainfall is uniformly distributed throughout 12 months in the same year, the PCI values will be less than 10.…”