2000, Franck, S., Block, A., Von Bloh, W., Bounama, C., Schellnhuber, H.J., Svirezhev, Y.

The long-term co-evolution of the geosphere-biosphere complex from the Proterozoic up to 1.5 billion years into the planet's future is investigated using a conceptual earth system model including the basic geodynamic processes. The model focusses on the global carbon cycles as mediated by life and driven by increasing solar luminosity and plate tectonics. The main CO2 sink, the weathering of silicates, is calculated as a function of biologic activity, global run-off and continental growth. The main CO2 source, tectonic processes dominated by sea-floor spreading, is determined using a novel semi-empirical scheme. Thus, a geodynamic extension of previous geostatic approaches can be achieved. As a major result of extensive numerical investigations, the 'terrestrial life corridor', i.e., the biogeophysical domain supporting a photosynthesis-based ecosphere in the planetary past and in the future, can be identified. Our findings imply, in particular, that the remaining life-span of the biosphere is considerably shorter (by a few hundred million years) than the value computed with geostatic models by other groups. The 'habitable-zone concept' is also revisited, revealing the band of orbital distances from the sun warranting earth-like conditions. It turns out that this habitable zone collapses completely in some 1.4 billion years from now as a consequence of geodynamics.

2006, Franck, S., Bounama, C., von Bloh, W.

We present a minimal model for the global carbon cycle of the Earth containing the reservoirs mantle, ocean floor, continental crust, biosphere, and the kerogen, as well as the combined ocean and atmosphere reservoir. The model is specified by introducing three different types of biosphere: procaryotes, eucaryotes, and complex multicellular life. During the entire existence of the biosphere procaryotes are always present. 2 Gyr ago eucaryotic life first appears. The emergence of complex multicellular life is connected with an explosive increase in biomass and a strong decrease in Cambrian global surface temperature at about 0.54 Gyr ago. In the long-term future the three types of biosphere will die out in reverse sequence of their appearance. We show that there is no evidence for an implosion-like extinction in contrast to the Cambrian explosion. In dependence of their temperature tolerance complex multicellular life and eucaryotes become extinct in about 0.8–1.2 Gyr and 1.3–1.5 Gyr, respectively. The ultimate life span of the biosphere is defined by the extinction of procaryotes in about 1.6 Gyr.

2009, Jung, M., Reichstein, M., Bondeau, A.

Global, spatially and temporally explicit estimates of carbon and water fluxes derived from empirical up-scaling eddy covariance measurements would constitute a new and possibly powerful data stream to study the variability of the global terrestrial carbon and water cycle. This paper introduces and validates a machine learning approach dedicated to the upscaling of observations from the current global network of eddy covariance towers (FLUXNET). We present a new model TRee Induction ALgorithm (TRIAL) that performs hierarchical stratification of the data set into units where particular multiple regressions for a target variable hold. We propose an ensemble approach (Evolving tRees with RandOm gRowth, ERROR) where the base learning algorithm is perturbed in order to gain a diverse sequence of different model trees which evolves over time. We evaluate the efficiency of the model tree ensemble (MTE) approach using an artificial data set derived from the Lund-Potsdam-Jena managed Land (LPJmL) biosphere model. We aim at reproducing global monthly gross primary production as simulated by LPJmL from 1998–2005 using only locations and months where high quality FLUXNET data exist for the training of the model trees. The model trees are trained with the LPJmL land cover and meteorological input data, climate data, and the fraction of absorbed photosynthetic active radiation simulated by LPJmL. Given that we know the "true result" in the form of global LPJmL simulations we can effectively study the performance of the MTE upscaling and associated problems of extrapolation capacity. We show that MTE is able to explain 92% of the variability of the global LPJmL GPP simulations. The mean spatial pattern and the seasonal variability of GPP that constitute the largest sources of variance are very well reproduced (96% and 94% of variance explained respectively) while the monthly interannual anomalies which occupy much less variance are less well matched (41% of variance explained). We demonstrate the substantially improved accuracy of MTE over individual model trees in particular for the monthly anomalies and for situations of extrapolation. We estimate that roughly one fifth of the domain is subject to extrapolation while MTE is still able to reproduce 73% of the LPJmL GPP variability here. This paper presents for the first time a benchmark for a global FLUXNET upscaling approach that will be employed in future studies. Although the real world FLUXNET upscaling is more complicated than for a noise free and reduced complexity biosphere model as presented here, our results show that an empirical upscaling from the current FLUXNET network with MTE is feasible and able to extract global patterns of carbon flux variability.

2008, Döll, P., Berkhoff, K., Bormann, H., Fohrer, N., Gerten, D., Hagemann, S., Krol, M.

Large-scale hydrological modelling has become increasingly wide-spread during the last decade. An annual workshop series on large-scale hydrological modelling has provided, since 1997, a forum to the German-speaking community for discussing recent developments and achievements in this research area. In this paper we present the findings from the 2007 workshop which focused on advances and visions in large-scale hydrological modelling. We identify the state of the art, difficulties and research perspectives with respect to the themes "sensitivity of model results", "integrated modelling" and "coupling of processes in hydrosphere, atmosphere and biosphere". Some achievements in large-scale hydrological modelling during the last ten years are presented together with a selection of remaining challenges for the future.