Stable gap-filling for longer eddy covariance data gaps: A globally validated machine-learning approach for carbon dioxide, water, and energy fluxes

作者：Songyan Zhu, Robert Clement, Jon McCalmont, Christian A. Davies, Timothy C. Hill · 发表于：Agricultural and Forest Meteorology · 年份：2021 · DOI：10.1016/j.agrformet.2021.108777 · 被引用次数：69 · 研究领域：Plant Water Relations and Carbon Dynamics、Hydrology and Watershed Management Studies、Climate variability and models