Impacts of land cover and climate data selection on understanding terrestrial carbon dynamics and the CO2 airborne fraction

Terrestrial and oceanic carbon cycle processes remove similar to 55% of global carbon emissions, with the remaining 45%, known as the airborne fraction, accumulating in the atmosphere. The long-term dynamics of the component fluxes contributing to the airborne fraction are challenging to interpret, but important for informing fossil-fuel emission targets and for monitoring the trends of biospheric carbon fluxes. Climate and land-cover forcing data for terrestrial ecosystem models are a largely unexplored source of uncertainty in terms of their contribution to understanding airborne fraction dynamics. Here we present results using a single dynamic global vegetation model forced by an ensemble experiment of climate (CRU, ERA-Interim, NCEP-DOE II), and diagnostic land-cover datasets (GLC2000, GlobCover, MODIS). For the averaging period 1996-2005, forcing uncertainties resulted in a large range of simulated global carbon fluxes, up to 13% for net primary production (52.4 to 60.2 Pg C a(-1)) and 19% for soil respiration (44.2 to 54.8 Pg C a(-1)). The sensitivity of contemporary global terrestrial carbon fluxes to climate strongly depends on forcing data (1.2-5.9 Pg C K-1 or 0.5 to 2.7 ppmv CO2 K-1), but weakening carbon sinks in sub-tropical regions and strengthening carbon sinks in northern latitudes are found to be robust. The climate and land-cover combination that best correlate to the inferred carbon sink, and with the lowest residuals, is from observational data (CRU) rather than reanalysis climate data and with land-cover categories that have more stringent criteria for forest cover (MODIS). Since 1998, an increasing positive trend in residual error from bottom-up accounting of global sinks and sources (from 0.03 (1989-2005) to 0.23 Pg C a(-1) (1998-2005)) suggests that either modeled drought sensitivity of carbon fluxes is too high, or that carbon emissions from net land-cover change is too large.