%0 Dataset
%T Multi-precipitation concentration indicators dataset for mainland China from 1961 to 2100
%J National Cryosphere Desert Data Center
%I National Cryosphere Desert Data Center(www.ncdc.ac.cn)
%U http://www.ncdc.ac.cn/portal/metadata/3b772081-0169-41b2-8c1c-529069194ada
%W NCDC
%R 10.12072/ncdc.precipitation.db7311.2026
%A Zhang Dongyang
%A Li Xuemei
%K Precipitation concentration;CMIP6;Statistical downscaling;SSP;Scenario;China
%X Global climate change intensifies the hydrological cycle, leading to frequent extreme precipitation events. The precipitation concentration index is a key tool for diagnosing the spatiotemporal distribution characteristics of precipitation. The existing research has problems such as fragmented site observations and a disconnect between historical benchmarks and future estimates. This dataset integrates ground observation and grid observation data from China from 1961 to 2022, as well as statistically downscaled CMIP6 estimation data from four SSP scenarios from 2015 to 2100, with a spatial resolution of 0.25 °. It constructs a spatiotemporal continuous dataset (MPCID) that includes four core indicators: precipitation concentration (PCD), precipitation concentration period (PCP), daily precipitation concentration index (DPCI), and monthly precipitation concentration index (MPCI).   Through site data verification, PCD has the smallest error and the best correlation. The dataset can support research on the spatiotemporal distribution of precipitation in China, hydrological and agricultural climate impact assessment, and adaptive management strategy formulation.