Abstract
Abstract. The sensitivity of the process parameters of the Biosphere Energy Transfer HYdrology (BETHY) model to choices of atmospheric concentration network, high frequency terrestrial fluxes, and the choice of flux measurement network is investigated by using a carbon cycle data assimilation system. We use BETHY-generated fluxes as a proxy of flux measurements. Results show that monthly mean or low-frequency observations of CO2 concentration provide strong constraints on parameters relevant for net flux (NEP) but only weak constraints for parameters controlling gross fluxes. The use of high-frequency CO2 concentration observations, which has led to great refinement of spatial scales in inversions of net flux, adds little to the observing system in the Carbon Cycle Data Assimilation System (CCDAS) case. This unexpected result is explained by the fact that the stations of the CO2 concentration network we use are not well placed to measure such high frequency signals. Indeed, CO2 concentration sensitivities relevant for such high frequency fluxes are found to be largely confined in the vicinity of the corresponding fluxes, and are therefore not well observed by background monitoring stations. In contrast, our results clearly show the potential of flux measurements to better constrain the model parameters relevant for gross primary productivity (GPP) and net primary productivity (NPP). Given uncertainties in the spatial description of ecosystem functions, we recommend a combined observing strategy.
Highlights
Uncertainties in the distribution of the carbon flux in the atmosphere limit both the skill of predictive models and the application of carbon accounting using measurements
The different configurations of model/data used to study the sensitivity of the parameters to (i) high frequency observations of CO2 concentrations and (ii) temporal resolution of meteorological and phenological data used to force Biosphere Energy Transfer HYdrology (BETHY) are first defined
The smallest reduction (75 %) is found for the β parameter relevant for swamp vegetation (Wetl plant functional type (PFT)). These results agree with those reported in Ziehn et al (2011), who investigated the sensitivity of the uncertainty reductions in BETHY parameters to the spatial variations of the PFTs
Summary
Uncertainties in the distribution of the carbon flux in the atmosphere limit both the skill of predictive models and the application of carbon accounting using measurements. There are two main approaches: the simplest are direct inversion systems in which atmospheric transport models and Bayesian estimation methods are used to infer surface fluxes from atmospheric CO2 concentrations. These have been broadly used but their estimates vary widely due to differences in setup, observational data, prior estimates of the fluxes and transport models (e.g., Gurney et al, 2002, 2004; Law et al, 2003; Baker et al, 2006; Rayner et al, 2008; Chevallier et al, 2010). A second approach uses a range of observations to constrain the possible trajectories of dynamical models of the carbon cycle.
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