Assessing the Importance of Prior Biospheric Fluxes on Inverse Model Estimates of CO2

Atmospheric mixing ratios of carbon dioxide (CO₂) are largely controlled by anthropogenic emissions and biospheric sources/sinks. The processes controlling terrestrial biosphere-atmosphere carbon exchange are currently not fully understood, resulting in models having significant differences in the quantification of biospheric CO₂ fluxes. Currently, atmospheric chemical transport models (CTM) and global climate models (GCM) use multiple different biospheric CO₂ flux models resulting in large differences in simulating the global carbon cycle. The Orbiting Carbon Observatory 2 (OCO-2) satellite mission was designed to allow for the improved understanding of the processes involved in the exchange of carbon between terrestrial ecosystems and the atmosphere, and therefore allowing for more accurate assessment of the seasonal/inter-annual variability of CO₂. OCO-2 provides much-needed CO₂ observations in data-limited regions allowing for the evaluation of model simulations of greenhouse gases (GHG) and facilitating global/regional estimates of “top-down” CO₂ fluxes. We conduct a 4-D Variation (4D-Var) data assimilation with the GEOS-Chem (Goddard Earth Observation System–Chemistry) CTM using 1) OCO-2 land nadir and land glint retrievals and 2) global in situ surface flask observations to constrain biospheric CO₂ fluxes. We apply different state-of-the-science year-specific CO₂ flux models (e.g., NASA-CASA (NASA-Carnegie Ames Stanford Approach), CASA-GFED (Global Fire Emissions Database), Simple Biosphere Model version 4 (SiB-4), and LPJ (Lund-Postdam-Jena) model) to assess the impact of “a priori” flux predictions to “a posteriori” estimates. We will present the “top-down” CO₂ flux estimates for the year 2015 using OCO-2 and in situ observations, and a complete indirect evaluation of the a priori and a posteriori flux estimates using independent in situ observations. We will also present our assessment of the variability of “top-down” CO₂ flux estimates when using different biospheric CO₂ flux models. This work will improve our understanding of the global carbon cycle, specifically, how OCO-2 observations can be used to constrain biospheric CO₂ flux model estimates.