Constraining estimates of terrestrial carbon uptake: new opportunities using long-term satellite observations and data assimilation

Abstract

The response of terrestrial carbon uptake to increasing atmospheric [CO₂ ], that is the CO₂ 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 that could improve understanding of CFE and enable more accurate forecasts of terrestrial carbon uptake.

Keywords: CO2 fertilization; Earth System Model; data assimilation; gross primary productivity; light use efficiency; satellite remote sensing; water use efficiency.