Constraining respiration flux and carbon pools in a simple ecosystem
carbon model
Abstract
Incorporating observational data in carbon-cycle models provides a
systematic framework for understanding complex ecosystem carbon
dynamics, contributing essential insights for climate change mitigation
and land ability to continue acting as a carbon sink. This study
addresses the challenge of accurately quantifying carbon fluxes and
pools, focusing on the information content of remote sensing
observations. The research explores the impact of assimilating multiple
observational datasets into the CARbon DAta MOdel fraMework (CARDAMOM).
Satellite observations such as solar-induced fluorescence (SIF) and
vegetation optical depth (VOD) are used as proxies for photosynthesis
and aboveground biomass, respectively. The study aims to answer key
questions about the reliability of remote sensing data in constraining
the ecosystem respiration flux and sizes and dynamics of carbon pools
and the relative usefulness of SIF and VOD across five FLUXNET sites. We
conclude that assimilating remote SIF and VOD instead of site-based net
ecosystem exchange did not deteriorate and even improved model
predictions for all metrics except for interannual variability. Notably,
the improved results correspond to a consistent shift in values for
crucial model parameters across all five investigated sites.