B. Nemry

The interannual change of atmospheric CO2: Contribution of subtropical ecosystems?

The global terrestrial carbon cycle model CARAIB (CARbon Assimilation In the Biosphere) is used to study the response of the terrestrial ecosystems to the large scale climate variations over the period 1980–1993. The global net carbon exchange flux with the atmosphere is calculated and compared with the terrestrial contribution derived from the deconvolution of the atmospheric CO2 and δ13C measurements. A fairly large CO2 biospheric source is predicted during the strong El Nino events of 1982–83 and 1986–87 as a consequence of the induced global warming. The direct and indirect temperature controls of the primary production and respiration dominate the CO2 anomaly. An analysis of the relative contribution by latitudinal bands and ecosystems shows that low-latitude vegetation dominates the variability at the El Nino time scale. In savannas, the model indicates that the interannual changes result, to a large extent, from the control of soil water content on gross primary production (GPP). In the tropical rain forests, both respiration and GPP contribute to the response of the net biospheric flux.

The seasonality of the CO2 exchange between the atmosphere and the land biosphere: A study with a global mechanistic vegetation model

Two simulations of the seasonal variation of the global atmospheric CO2 distribution are obtained by combining an atmospheric transport model, two parameterizations of soil heterotrophic respiration (SHR), and a mechanistic model of carbon assimilation in the biosphere (CARAIB) that estimates the net primary production (NPP) of continental vegetation. The steady state hypothesis of the biosphere allows the spatial distribution and the global content of the soil carbon to be expressed as a function of the root fractions of soil respiration under forested and herbaceous vegetation covers. The sensitivity of the modeled CO2 signal to the wind field does not exceed the observed interannual variability. The influence of the various vegetation zones is quantified by the Fourier analysis of the modeled atmospheric signal. In the northern hemisphere, the temperate ecosystems dominate the seasonal atmospheric signal of the extratropical latitudes. The ecosystems of the tropical northern zone determine the local signal, while the southern tropical ecosystems influence largely the signal in the whole southern hemisphere. The results give credence to the mechanistic modeling of NPP since the simulated atmospheric signal is comparable with that obtained with normalized difference vegetation index (NDVI) based diagnostic models coupled with a parameterization of SHR fitted to optimize the atmospheric signal.

Seasonal and interannual influences of the terrestrial ecosystems on atmospheric CO2: a model study

Abstract The prognostic CARAIB (Carbon Assimilation In the Biosphere) model has been used in conjunction with the Max-Planck Institut TM2 atmospheric transport model to calculate the atmospheric CO 2 fluctuations at the global scale. Two applications are briefly described. In the first one, the seasonal CO 2 variation is calculated and a Fourier analysis is performed to determine the relative contributions of the various vegetation types. It is found that the seasonal signal is dominated by the grasslands and needle leaf forests in the northern boreal and temperate zones. In the southern hemisphere, tropical deciduous forests and grasslands make the primary contribution. In the second application, the net primary productivity (NPP), soil heterotrophic respiration (SHR) and net ecosystem productivity (NEP) are calculated for years 1987 and 1988 with the model driven by observed climatic variables. Preliminary results indicate that the NEP variations between these two years are strongly dominated by tropical ecosystems. However, it is shown that the results are strongly dependent on the dataset used for the 1987-88 temperature record, raising the question of reliability of such modelling studies of the interannual variability of the biosphere.