The response of terrestrial carbon uptake to increasing atmospheric [CO 2], that is the CO 2 fertilization effect (CFE ), remains a key area of uncertainty in carbon cycle science. Here we provide a perspective on how satellite observations could be better used to understand and constrain CFE . We then highlight data assimilation (DA ) as an effective way to reconcile different satellite datasets and systematically constrain carbon uptake trends in Earth System Models. As a proof‐of‐concept, we show that joint DA of multiple independent satellite datasets reduced model ensemble error by better constraining unobservable processes and variables, including those directly impacted by CFE . DA of multiple satellite datasets offers a powerful technique thatThe  could improve understanding of CFE and enable more accurate forecasts of terrestrial carbon uptake.