Projected Impact of the GOSAT Observations on Regional CO₂ Flux Estimations as a Function of Total Retrieval Error

Abstract

We studied the impact of the planned atmospheric CO₂ observations by GOSAT (Greenhouse gases Observing SATellite) on the inverse model estimate of monthly and annual mean regional CO₂ fluxes, using the inverse models of the CO₂ fluxes for 22 large regions of a globe. The inverse model of the atmospheric transport uses monthly and annual means of simulated GOSAT CO₂ observation data, which were aggregated to grid cells with the size of 7.5°×7.5° (horizontal), and surface-station observations as formulated in Transcom-3 inverse modelling inter-comparison. The observation frequency of GOSAT in our analysis was corrected for simulated probability of clear-sky conditions, assuming global mean clear sky probability of 11%. Our results demonstrate that the mean regional flux uncertainty can be reduced by about 50% by adding satellite observations with single shot precision of 5ppm and randomly-distributed retrieval bias of 0.5ppm.