Machine learning uncovers a multi-year climate memory in permafrost degradation on the Qinghai–Tibet Plateau: the critical roles of precipitation and lagged temperature
Kunqi Ding(Hohai University), Zhongbo Yu(Hohai University), Tongqing Shen(University of British Columbia), Peng Jiang(Hohai University), Bin Yang(China Geological Survey), Rongrong Zhang(Ningbo University), Jie Ni(Hangzhou First People's Hospital)
Cited by 8
Related Papers
miRTarBase update 2022: an informative resource for experimentally validated miRNA–target interactions
|Nucleic Acids Research|2021|1k
Spatial difference analysis of the runoff evolution attribution in the Yellow River Basin
|Journal of Hydrology|2022|85
Spatial-temporal dynamics of meteorological and soil moisture drought on the Tibetan Plateau: Trend, response, and propagation process
|Journal of Hydrology|2023|72
Development and application of fluorescence sensor and test strip based on molecularly imprinted quantum dots for the selective and sensitive detection of propanil in fish and seawater samples
|Journal of Hazardous Materials|2019|64
Changes in permafrost spatial distribution and active layer thickness from 1980 to 2020 on the Tibet Plateau
|The Science of The Total Environment|2022|52