1Laboratoire des Sciences du Climat et de l'Environnement, Commissariat à l'Energie Atomique, LSCE-Orme, Orme des Merisiers, 91191 Gif-sur-Yvette CEDEX, France
2School of Engineering and Applied, Pierce Hall G3H, Harvard University, Cambridge MA 02138, USA
Received: 11 Oct 2009 – Discussion started: 12 Feb 2010
Abstract. Our ability to predict future climate change relies on our understanding of current and future CO2 fluxes, particularly on a regional scale (100–1000 km). CO2 regional sources and sinks are still poorly understood. Inverse transport modeling, a method often used to quantify these fluxes, relies on atmospheric CO2 measurements. One of the main challenges for the transport models used in the inversions is to properly reproduce CO2 vertical gradients between the boundary layer and the free troposphere, as these gradients impact on the partitioning of the calculated fluxes between the different model regions. Vertical CO2 profiles are very well suited to assess the performances of the models. In this paper, we conduct a comparison between observed and modeled CO2 profiles recorded during two CAATER campaigns that occurred in May 2001 and October 2002 over Western Europe, as described in a companion paper. We test different combinations between a global transport model (LMDZt), a mesoscale transport model (CHIMERE), and different sets of biospheric fluxes, all chosen with a diurnal cycle (CASA, SiB2 and ORCHIDEE). The vertical profile comparison shows that: 1) in most cases the influence of the biospheric flux is small but sometimes not negligible, ORCHIDEE giving the best results in the present study; 2) LMDZt is most of the time too diffuse, as it simulates a too high boundary layer height; 3) CHIMERE better reproduces the observed gradients between the boundary layer and the free troposphere, but is sometimes too variable and gives rise to incoherent structures. We conclude there is a need for more vertical profiles to conduct further studies to improve the parameterization of vertical transport in the models used for CO2 flux inversions.
Revised: 30 Jul 2010 – Accepted: 24 Aug 2010 – Published: 20 Jun 2011
Furthermore, we use a modeling method to quantify CO2 fluxes at the regional scale from a chosen observing point, coupling influence functions from the transport model LMDZt (that works quite well at the synoptic scale) with information on the space-time distribution of fluxes. This modeling method is compared to a dual tracer method (the so-called Radon method) for a case study on 25 May 2001 during which simultaneous well-correlated in situ CO2 and Radon 222 measurements have been collected. Both methods give a similar result: a flux within the Radon 222 method uncertainty (35%), that is an atmospheric CO2 sink of −4.2 to −4.4 gC m−2 day−1. We have estimated the uncertainty of the modeling method to be at least 33% on average, and even more for specific individual events. This method allows the determination of the area that contributed to the CO2 observed concentration. In our case, the observation point located at 1700 m a.s.l. in the north of France, is influenced by an area of 1500×700 km2 that covers the Benelux region, part of Germany and western Poland. Furthermore, this method allows deconvolution between the different contributing fluxes. In this case study, the biospheric sink contributes 73% of the total flux, fossil fuel emissions for 27%, the oceanic flux being negligible. However, the uncertainties of the influence function method need to be better assessed. This could be possible by applying it to other cases where the calculated fluxes can be checked independently, for example at tall towers where simultaneous CO2 and Radon 222 measurements can be conducted. The use of optimized fluxes (from atmospheric inversions) and of mesoscale models for atmospheric transport may also significantly reduce the uncertainties.
Xueref-Remy, I., Bousquet, P., Carouge, C., Rivier, L., and Ciais, P.: Variability and budget of CO2 in Europe: analysis of the CAATER airborne campaigns – Part 2: Comparison of CO2 vertical variability and fluxes between observations and a modeling framework, Atmos. Chem. Phys., 11, 5673-5684, doi:10.5194/acp-11-5673-2011, 2011.