Using a Model-Data Fusion Approach to Better Understand the Fate of Terrestrial Carbon in the Southern Sierras.

Abstract:

Quantifying the dynamic nature of the terrestrial carbon cycle is crucial for mitigating the effects of anthropogenic carbon emissions. While our ability to monitor carbon flux in ecosystems has increasingly advanced over the past few decades, uncertainty remains on the fate, partitioning and residence times of carbon assimilated by plants. Using a model-data fusion approach, the CARbon DAta MOdel fraMework (CARDAMOM) has paved the way for retrieving carbon state and process variables at individual sites and at a global scale. We intend to fill in the spatiotemporal gap and present our findings on the carbon balance of the Southern Sierra Critical Zone Observatory using long-term datasets. In particular, we will highlight key differences in CARDAMOM simulations constrained by satellite and flux tower data to quantify plant carbon allocation, pools and residence times. Measurements from satellites include leaf area index, above-ground biomass and gross primary productivity (inferred from solar-induced fluorescence). We will also show how environmental factors can affect forest carbon cycling and discuss its implications in the context of climate change.