%0 Dataset
%T Long-term daily snow water equivalent dataset for the Three-River Source region from 1980 to 2020
%J National Cryosphere Desert Data Center
%I National Cryosphere Desert Data Center(www.ncdc.ac.cn)
%U http://www.ncdc.ac.cn/portal/metadata/83dac452-a702-47a6-92e9-6cda097bb863
%W NCDC
%R 10.12072/ncdc.nieer-snow.db6815.1
%A Zhao Zisheng
%A Xiaohua Hao 
%A Li Hangxuan
%A Zhong Xinyue
%A Wu Xiaodong
%K Snow water equivalent;long-term time series;snow density;passive microwave
%X High spatial resolution snow water equivalent (SWE) is critical for hydrological, ecological, and disaster research. However, passive microwave SWE products (10/25 km) with coarse spatial resolution can no longer meet modern demands for high precision and fine resolution. This study integrated newly calibrated enhanced-resolution brightness temperature data with optical snow area fraction and snow cover days, employing the deep learning FT-Transformer model to retrieve daily snow depth data at 5 km spatial resolution during the snow cover period (October to April) in the Three-River Source Region. The snow depth was subsequently converted into 5 km spatial resolution SWE data using monthly averaged snow density. This work establishes a robust data foundation for snow resource monitoring in the Three-River Source Region.