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(State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering), Bin Yang(China Geological Survey), Rongrong Zhang(Ningbo University), Jie Ni(Jiangsu Cancer 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