CO 2 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 CO 2 source/sink inversion. However, a dynamical link between vertical transport, satellite based retrievals of column mole fractions of CO 2, 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 CO 2 transport and retrieved fluxes to different parameterizations of sub-grid vertical transport. We find that frontal transport feeds off background vertical CO 2 gradients, which are modulated by sub-grid vertical transport. The implication for source/sink estimation is two-fold. First, CO 2 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 CO 2, which leads to systematic differences in moist poleward and dry equatorward CO 2 transport and therefore the fraction of CO 2 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 CO 2 is a major source of uncertainty in source/sink inversion. © Author(s) 2012.