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CAMELS Report Summary

Project ID: EVK2-CT-2002-00151
Funded under: FP5-EESD
Country: Germany

D 4.2 Estimates of the contemporary European land carbon sink, and its causes

CAMELS is a project on "Carbon Assimilation and Modelling of the European Land Surface" and primarily aims at producing best estimates and uncertainty bounds for the contemporary and historical land carbon sinks in Europe and elsewhere, isolating the effects of direct land-management.

CAMELS combine top-down and bottom up approaches. The assumption used in CAMELS is that the best way to spatially extrapolate the results from the flux measurements is not through fluxes, but through parameter values that describe the underlying processes in terrestrial ecosystem models. Within CAMELS these parameters are constrained by measurements on a suite of scales ranging from the laboratory to stand and global scales.

The Bayesian framework for inversion allows combining observational information with prior knowledge on parameters in a consistent way. Not only does the Bayesian approach provide the most likely parameter values, it also delivers uncertainty bounds on the parameters. Weakly constrained parameters are thus given an appropriate uncertainty range instead of being excluded a priori from the optimisation. The method is applied on global scale using satellite observed vegetation colour and atmospheric carbon dioxide (Kaminski et al. 2002, Rayner et al., 2004) and on the stand scale, i.e. using flux measurements as observational constraint (Knorr and Kattge, 2004).

The parameter values optimised on the stand scale are used as a priori values in a global carbon Cycle Data Assimilation System (CCDAS). CAMELS has so far produced one prototype CCDAS based on the ecosystem model BETHY: in a first data assimilation step, BETHY takes satellite-observed values of "greenness" to optimise parameters related to water status, phenology, and total plant cover. Next, observed atmospheric carbon dioxide provided by the GLOBALVIEW sampling network is used to constrain 58 parameters in the physiological and energy-balance parts of BETHY (carbon-BETHY). The latter assimilation step uses an efficient variational approach, based on the adjoint (the first derivative of the code with respect to model parameters) of carbon-BETHY coupled to the atmospheric transport model TM2. Uncertainties of optimised model parameters are derived from the Hessian (the second derivative of the carbon-BETHY code with respect to the parameters). These parameter uncertainties, that reflect both the prior information (in a Bayesian context) as well as the large-scale information from the atmospheric carbon dioxide are finally translated to uncertainty bounds for CO2 fluxes and any other model diagnostic by means of the Jacobian of the carbon-BETHY code. All derivative code (adjoint, Hessian, and Jacobian) is generated automatically by FastOpt's compiler tool TAF. Automatic generation ensures that improvements of BETHY can be used in the assimilation scheme without delay.

First output of CCDAS using 20 years of atmospheric CO2 observations obtains a considerable reduction in uncertainty for about 12 of the 58 parameters that enter the optimisation. Results derived from the optimised carbon-BETHY, while still somewhat preliminary, clearly show that interannual fluctuations of terrestrial CO2 fluxes are dominated by the El Nino-Southern Oscillation (ENSO) cycle, except for the time after the Pinatubo eruption (Scholze, 2003). During El Nino (warm) pacific conditions, large parts of the tropical ecosystem come under water stress with reduced photosynthesis. The spatial distribution of the long-term mean net flux of CO2 shows a relatively large uptake over the northern hemisphere continents, and uptake over the tropical continents, which partly balances the large background source from land use change. In general the uncertainties are relatively low compared to equivalent uncertainties from direct inversions. Still, high uncertainties are found in tropical America and Africa, mainly due to the lack of observation stations in that areas. Summarizing the results for different regions, we find a terrestrial sink for Europe (excl. Russia) that is around a third of the fossil fuel emissions of the area, but with uncertainty bounds of the same size as the fluxes themselves. The country analysed that has the largest uncertainty in terrestrial CO2 fluxes is Brazil.

Building on the experience gained with CCDAS, CAMELS is currently working on a series of historical ecosystem model simulations that span the entire 20th century and that include further processes, such as land management, nitrogen deposition, and fire.
The final aim is to present a concept for an operational system that is capable to optimally combine all relevant large-scale observations to deliver the best possible estimates of European and global CO2 fluxes on a routine basis. Further information about CAMELS is available form; for CCDAS please check the website

Related information


Ernst-Detlef SCHULZE, (Professor)
Tel.: +49-364-1643642
Fax: +49-364-1643665
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