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What have we learned from intensive atmospheric sampling field programmes of CO2?

MPG-Autoren
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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Zitation

Lin, J. C., Gerbig, C., Wofsy, S. C., Daube, B. C., Matross, D. M., Chow, V. Y., et al. (2006). What have we learned from intensive atmospheric sampling field programmes of CO2? Tellus, Series B - Chemical and Physical Meteorology, B58(5), 331-343. doi:10.3402/tellusb.v58i5.16900.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-000E-D449-9
Zusammenfassung
The spatial and temporal gradients in atmospheric CO2 contain signatures of carbon fluxes, and as part of inverse studies, these signatures have been combined with atmospheric models to infer carbon sources and sinks. However, such studies have yet to yield finer-scale, regional fluxes over the continent that can be linked to ecosystem processes and ground-based observations. The reasons for this gap are twofold: lack of atmospheric observations over the continent and model deficiencies in interpreting such observations. This paper describes a series of intensive atmospheric sampling field programmes designed as pilot experiments to bridge the observational gap over the continent and to help test and develop models to interpret these observations. We summarize recent results emerging from this work, outlining the role of the intensive atmospheric programmes in collecting CO2 data in both the vertical and horizontal dimensions. These data: (1) quantitatively establish the spatial variability of CO2 and the associated errors from neglecting this variability in models; (2) directly measure regional carbon fluxes from airmass-following experiments and (3) challenge models to reduce and account for uncertainties in atmospheric transport. We conclude with a look towards the future, outlining ways in which intensive atmospheric sampling can contribute towards advancing carbon science. [References: 47]