Abstract
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.
Highlights
Measurements of atmospheric CO2 mixing ratio contain information about land and ocean carbon sinks, which act as natural buffers against rising fossil fuel emissions
We examine the impact of model differences in moist frontal transport on the inversion of total column CO2 retrievals from satellite remote sensing instruments using Observation System Simulation Experiments, or OSSE’s
Upward and poleward frontal CO2 transport feeds off the background vertical CO2 gradient, which is modulated by sub-grid vertical transport processes such as cumulus convection and turbulent diffusion
Summary
Measurements of atmospheric CO2 mixing ratio contain information about land and ocean carbon sinks, which act as natural buffers against rising fossil fuel emissions. Flux inversion methods combine information from winds, CO2 measurements, and surface flux estimates to infer the size and distribution of these sinks (e.g., Gurney et al, 2002). Model transport error, related to subgrid scale vertical transport, remains a well-known but poorly characterized source of uncertainty in source/sink inversions of surface and column CO2 data (Denning et al, 1999; Yi et al, 2004; Yang et al, 2007; Stephens et al, 2007; Houweling et al, 2010; Chevallier et al, 2010; Liu et al, 2011). Because a significant portion of the synoptic signal is correlated with moist processes and likely to be unobserved by satellites (Parazoo et al, 2011), covariance of moist transport with surface CO2 flux will cause errors in top-down flux estimates if not represented correctly in transport models
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