We present an atmospheric inverse modeling framework to constrain terrestrial biosphere CO₂ exchange processes at subregional scales. The model is operated at very high spatial and temporal resolution, using the state of Oregon in the northwestern United States as the model domain. The modeling framework includes mesoscale atmospheric simulations coupled...
In recent years, measurements of atmospheric carbon dioxide with high precision and accuracy have become increasingly important for climate change research, in particular to inform terrestrial biosphere models. Anthropogenic carbon dioxide emissions from fossil fuel burning have long been recognized to contribute a significant portion of the carbon dioxide in...
We present an inverse modeling framework designed to constrain CO2 budgets at regional scales. The approach captures atmospheric transport processes in high spatiotemporal resolution by coupling a mesoscale model with Lagrangian Stochastic backward trajectories. Terrestrial biosphere CO₂ emissions are generated through a simple diagnostic flux model that splits the net...