ACP Atmospheric Chemistry and Physics ACP 1680-7324 Copernicus GmbH Göttingen, Germany 10.5194/acp-10-3107-2010 What can we learn from European continuous atmospheric CO<sub>2</sub> measurements to quantify regional fluxes – Part 1: Potential of the 2001 network Carouge C. 1 Bousquet P. 1 2 Peylin P. 1 3 Rayner P. J. 1 Ciais P. 1 Laboratoire des Sciences du Climat et de l'Environnement, UMR1572 CNRS-CEA-UVSQ, Bât. 701, Orme des Merisiers, 91191 Gif-sur-Yvette, France Université de Versailles Saint-Quentin en Yvelines, Versailles, France Laboratoire de Biogéochimie et Ecologie des Milieux Continentaux, CNRS-UPMC-INRA, Paris, France 31 03 2010 10 6 3107 3117 This is an open-access article ditributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. This article is available from http://www.atmos-chem-phys.net/10/3107/2010/acp-10-3107-2010.html The full text article is available as a PDF file from http://www.atmos-chem-phys.net/10/3107/2010/acp-10-3107-2010.pdf

An inverse model using atmospheric CO<sub>2</sub> observations from a European network of stations to reconstruct daily CO<sub>2</sub> fluxes and their uncertainties over Europe at 40 km resolution has been developed within a Bayesian framework. In this first part, a pseudo-data experiment is performed to assess the potential of continuous measurements over Europe using a network of 10 stations of the AEROCARB project such as in 2001 (<a href="http://www.aerocarb.cnrs-gif.fr/"target="_blank">http://www.aerocarb.cnrs-gif.fr/</a>). Under the assumptions of a small observation noise and a perfect atmospheric transport model, the reconstruction of daily CO<sub>2</sub> fluxes and in particular of their synoptic variability is best over Western Europe where the network is the densest. At least a 10 days temporal and a 1000 km spatial averaging of the inverted daily/40 km fluxes is required in order to obtain a good agreement between the estimated and the "true" fluxes in terms of correlation and variability. The performance of the inversion system rapidly degrades when fluxes are sought for a smaller temporal or spatial averaging.

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