For the estimation of surface CO₂ fluxes from atmospheric concentration measurements, most often Bayesian approaches have been adopted. As with all Bayesian techniques the definition of prior probability distributions is a critical step in the analysis. However, practical considerations usually guide the definition of prior information rather than objective criterions. In this paper, in situ CO₂ flux pointwise measurements made by the eddy-covariance technique are used to estimate the errors of prior fluxes provided by the prognostic carbon-water-energy model ORCHIDEE. The results contradict the usual convenient assumption of a multivariate Gaussian distribution. The errors of ORCHIDEE have a heavier-tail distribution with a linear temporal dependency after the second lag day and no particular spatial structure. Such error distribution significantly complicates the inversion of CO₂ surface fluxes.