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A two‐fold enhancement in the sensitivity of atmospheric CO2 growth rate (CGR) to tropical temperature interannual variability () till early 2000s has been reported, which suggests a drought‐induced shift in terrestrial carbon cycle responding temperature fluctuations, thereby accelerating global warming. However, using six decades long atmospheric CO2 observations,...
Accurate quantification of vegetation carbon turnover time (τveg) is critical for reducing uncertainties in terrestrial vegetation response to future climate change. However, in the absence of global information of litter production, τveg could only be estimated based on net primary productivity under the steady‐state assumption. Here, we applied a machine‐learning approach to derive a global dataset...
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