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Detecting regional variability in sources and sinks of carbon dioxide: a synthesis

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http://pubman.mpdl.mpg.de/cone/persons/resource/persons62381

Gerbig,  C.
Airborne Trace Gas Measurements and Mesoscale Modelling, Dr. habil. C. Gerbig, Department Biogeochemical Systems, Prof. M. Heimann, Max Planck Institute for Biogeochemistry, Max Planck Society;

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Citation

Dolman, A. J., Gerbig, C., Noilhan, J., Sarrat, C., & Miglietta, F. (2009). Detecting regional variability in sources and sinks of carbon dioxide: a synthesis. Biogeosciences, 6(6), 1015-1026. doi:10.5194/bg-6-1015-2009.


Cite as: http://hdl.handle.net/11858/00-001M-0000-000E-D7EB-5
Abstract
The current paper reviews the experimental setup of the CarboEurope Experimental Strategy (CERES) campaigns with the aim of providing an overview of the instrumentation used, the data-set and associated modelling. It then assesses progress in the field of regional observation and modelling of carbon fluxes, bringing the papers of this special issue into a somewhat broader context of analysis. Instrumental progress has been obtained in the field of remotely monitoring from tall towers and the experimental planning. Flux measurements from aircraft are now capable, within some constraints, to provide regular regional observations of fluxes of CO2, latent and sensible heat. Considerable effort still needs to be put into calibrating the surface schemes of models, as they have direct impact on the input of energy, moisture and carbon fluxes in the boundary layer. Overall, the mesoscale models appear to be capable of simulating the large scale dynamics of the region, but in the fine detail, like the precise horizontal and vertical CO2 field differences between the models still exist. These errors translate directly into transport uncertainty, when the forward simulations are used in inverse mode. Quantification of this uncertainty, including that of inadequate boundary layer height modelling, still remains a major challenge for state of the art mesoscale models. Progress in inverse models has been slow, but has shown that it is possible to estimate some of the errors involved, and that using the combination of observations. Overall, the capability to produce regional, high-resolution estimates of carbon exchange, exist in potential, but the routine application will require considerable effort, both in the experimental as in the modelling domain. [References: 35]