Quantifying Observational Constraints in Top-Down Estimation of Terrestrial Biosphere Carbon Fluxes by CO2 Concentration and Eddy Covariance Flux Measurement Based on EnSRF and CMAQ

Abstract

Top-down methods commonly use atmospheric CO₂ concentration observations to constrain carbon source and sinks. Despite the increase in spaceborne and ground-based concentration measurements, atmospheric inversions are usually limited by uncertainties in chemical transport models (CTMs) when relating fluxes to observed CO₂ mole fractions. CO₂ eddy covariance (EC) flux measurements have been widely used to directly measure CO₂ fluxes over various ecosystems, but they have rarely been used as constraints in top-down estimations. In this study, we focused on the development of a novel fluxes assimilation scheme through direct flux observations within an Ensemble Square Root Filter assimilation framework. The assimilation scheme avoided some of complexities of concentration observation assimilations. The methodology was primarily applied to typical regions in west China, taking advantage of eight long-term ecosystem EC sites. Moreover, four sets of assimilation experiments were designed to quantify the impacts of observational constraints by flux and concentration measurements. Generally, results indicate that the monthly and hourly statistics of the a posteriori fluxes constrained by flux observations agreed well with flux measurements, demonstrating reasonable performance in seasonal and diurnal variations. Specifically, assimilation results demonstrated the advantage of a posteriori estimates inferred from flux measurements during growing season, as compared to results inferred from concentrations, while some limitation still exists in monthly budget estimates. Nevertheless, it is important to note that current results are only a mathematical optimum. CO₂ biospheric fluxes can be estimated more reliably and robustly at the regional scale given considerably more flux observations for efficient constraint.