What can we learn from European continuous atmospheric CO_{2} measurements to quantify regional fluxes  Part 2: Sensitivity of flux accuracy to inverse setup
Abstract
An inverse model using atmospheric CO_{2} observations from a European network of stations to reconstruct daily CO_{2} fluxes and their uncertainties over Europe at 50 km resolution has been developed within a Bayesian framework. We use the pseudodata approach in which we try to recover known fluxes using a range of perturbations to the input. In this study, the focus is put on the sensitivity of flux accuracy to the inverse setup, varying the prior flux errors, the pseudodata errors and the network of stations. We show that, under a range of assumptions about prior error and data error we can recover fluxes reliably at the scale of 1000 km and 10 days. At smaller scales the performance is highly sensitive to details of the inverse setup. The use of temporal correlations in the flux domain appears to be of the same importance as the spatial correlations. We also note that the use of simple, isotropic correlations on the prior flux errors is more reliable than the use of apparently physicallybased errors. Finally, increasing the European atmospheric network density improves the area with significant error reduction in the flux retrieval.
 Publication:

Atmospheric Chemistry & Physics
 Pub Date:
 March 2010
 DOI:
 10.5194/acp1031192010
 Bibcode:
 2010ACP....10.3119C