A protocol for developing a carbon stock product based on the OCO-2 MIP activities

Brendan Byrne,  Jet Propulsion Laboratory,  brendan.k.byrne@jpl.nasa.gov (Presenter)
David F Baker,  Colorado State University,  dfbaker66@gmail.com
David Crisp,  JPL/Caltech,  david.crisp@jpl.nasa.gov

The OCO-2 flux inversion model intercomparison project (MIP) is an effort to estimate CO2 fluxes from space-based atmospheric CO2 measurements, while also attempting to account for the effects of transport model error, inversion method issues, and retrieval biases. MIP flux products are produced across a variety of flux inversion systems using different transport schemes (GEOS-CHEM, LMDz, TM5, GEOS5, PCTM) driven by different meteorological fields (MERRA-2, ERA-interim, GEOS-FP) using different inverse methods (4D-Var, Bayesian synthesis, EnKF). The MIP also estimates fluxes using different subsets of atmospheric CO2 data – just in situ CO2 data (from GLOBALVIEW+ 5.0 and ObsPack ; IS), just OCO-2 Land Nadir plus Land Glint (LNLG) data, just OCO-2 ocean glint (OG) data, and these three sources together (LNLGOGIS) – to help assess relative biases between them.

Still, these products are not designed for stocktake activities, since atmospheric fluxes are estimated rather than changes in carbon stocks. To estimate stock changes, the fluxes must be modified to account for the lateral transfer of carbon at the surface – transfers which include the natural flow of carbon from the land biosphere into rivers, coastal zones, and oceans, as well as the anthropogenic transfers of agricultural and forest products to the populated areas where they are consumed. The impact of these lateral flows are best modeled as part of the a priori fluxes, in a manner similar to the way fossil fuel and biomass burning fluxes have been modeled (explicitly) previously. Here we describe a protocol for creating a carbon stock change product based on the MIP fluxes. We describe how we account for lateral fluxes of carbon, propagate uncertainties, and create well documented dataset for use in the 2023 Global Stocktake activities.

Poster: Poster_Byrne__132_25.pdf 

Presentation Type: Poster

Session: 2.5b Results expected from future missions

Session Date: Tuesday (6/15) 12:00 PM