CO₂ flux estimation errors associated with moist atmospheric processes

Abstract. Vertical transport by moist sub-grid scale processes such as deep convection is a well-known source of uncertainty in CO₂ source/sink inversion. However, a dynamical link between vertical transport, satellite based retrievals of column mole fractions of CO₂, and source/sink inversion has not yet been established. By using the same offline transport model with meteorological fields from slightly different data assimilation systems, we examine sensitivity of frontal CO₂ transport and retrieved fluxes to different parameterizations of sub-grid vertical transport. We find that frontal transport feeds off background vertical CO₂ gradients, which are modulated by sub-grid vertical transport. The implication for source/sink estimation is two-fold. First, CO₂ variations contained in moist poleward moving air masses are systematically different from variations in dry equatorward moving air. Moist poleward transport is hidden from orbital sensors on satellites, causing a sampling bias, which leads directly to small but systematic flux retrieval errors in northern mid-latitudes. Second, differences in the representation of moist sub-grid vertical transport in GEOS-4 and GEOS-5 meteorological fields cause differences in vertical gradients of CO₂, which leads to systematic differences in moist poleward and dry equatorward CO₂ transport and therefore the fraction of CO₂ variations hidden in moist air from satellites. As a result, sampling biases are amplified and regional scale flux errors enhanced, most notably in Europe (0.43 ± 0.35 PgC yr⁻¹). These results, cast from the perspective of moist frontal transport processes, support previous arguments that the vertical gradient of CO₂ is a major source of uncertainty in source/sink inversion.