Understanding intermodel differences in land carbon sink projections 

<p><span>Over the last decades, land ecosystems have removed from the atmosphere approximately one third of anthropogenic carbon emissions, highlighting the importance of the evolution of the land carbon sink for projected climate change. Nevertheless, the latest land carbon sink projections from multiple Earth system models show large differences, even for a policy-relevant scenario with mean global warming by the end of the century below 2&#176;C relative to preindustrial conditions. We hypothesize that this intermodel uncertainty originates from model differences in the sensitivities of annual net biome production (NBP) to (i) the CO₂ fertilization effect, and to the annual anomalies in growing season (ii) air temperature and (iii) soil moisture, as well as model differences in long-term average (iv) air temperature and (v) soil moisture. Using multiple linear regression and a resampling technique we quantify the individual contributions of these five terms for explaining the cumulative NBP anomaly of each model relative to the ensemble mean. Differences in the three sensitivity terms contribute the most, however, differences in average temperature and soil moisture also have sizeable contributions for some models. We find that the sensitivities of NBP to temperature and soil moisture anomalies, particularly in the tropics, explain approximately half of the deficit relative to the ensemble mean for the two models with the lowest carbon sink (ACCESS-ESM1-5 and UKESM1-0-LL) and half of the surplus for the two models with the highest sink (CESM2 and NorESM2-LM). In addition, year-to-year variations in NBP are more related to variations in soil moisture than air temperature</span> across most models and regions,<span> although</span> several models indicate <span>a stronger relation to</span>temperature <span>variations</span> in the core of the Amazon.<span> Overall, our study advances our understanding of why land carbon sink projections from Earth system models differ globally and across regions, which can guide efforts to reduce the underlying uncertainties.</span></p>