Geography Research Works
Permanent URI for this collectionhttp://hdl.handle.net/1903/1641
Browse
Search Results
Item Simulated impact of global climatic change on the geographic distribution of plant diversity(2005-01-13T14:03:37Z) Kleidon, AxelElevated concentrations of atmospheric carbon dioxide (pCO2) are likely to lead to substantial warming in the coming century with altered hydrological regimes, thereby affecting the distribution of plant species. Here I use an individual-based modeling approach to plant diversity to estimate the impact of global climatic change on the geographic distribution of plant diversity. Differences in temperature, precipitation, and light use efficiency (to represent stimulation of photosynthesis due to higher pCO2) are used in isolation and in combination in order to investigate the role of these drivers. I find that the general warming associated with elevated pCO2 leads to profoundly different responses of simulated diversity in temperature-limited and tropical environments. While the growing season is lengthened in northern latitudes and therefore enables more plant growth strategies to be successful, elevated autotrophic respiration rates lead to higher mortality during plant establishment in the tropics, therefore reducing the range of successful plant growth strategies. The overall impact of elevated pCO2 on plant diversity will clearly be a combination of various factors. What these model results nevertheless point out is that global climatic change may alter plant diversity patterns disproportionally by reducing the overall success of plant establishment.Item Enhancing the efficiency of terrestrial biosphere model simulations by reducing the redundancy in global forcing data sets(2005-01-10T19:51:15Z) Kleidon, AxelData sets of climatic variables and other geographic characteristics are becoming available in increasingly higher resolutions, resulting in substantial computing burdens for simulation models of the terrestrial biosphere. But by how much do higher resolutions of forcing data actually contribute to higher accuracy in model predictions? I investigated this question using the Cramer-Leemans climatology as an example for a high resolution forcing data set and a model of net primary productivity (NPP). I first used cluster analysis to reduce the complete grid of the climatology to a few grid points, each representative of regions with similar values. A global map of NPP was reconstructed by using the simulated values of the representative grid points for the respective regions. I then compared the reconstructed map of NPP to the one obtained from all grid points. The results show that a high accuracy in simulating the high resolution pattern and magnitude can be achieved by only considering a comparatively small subset of representative grid points. What this suggests is that, while high resolution data sets provide the necessary means to determine the typical regions, they do not add much accuracy to the overall outcome of model simulations because they contain many grid points with similar values. By reducing this redundancy, the methodology used here allows model simulations to be considerably more computing-time efficient while still retaining the accuracy in predicted quantities.Item Hyperdiffusion, maximum entropy production, and the simulated equator-pole temperature gradient in an atmospheric general circulation model(2005-01-10T19:47:03Z) Kleidon, AxelHyperdiffusion is used in atmospheric General Circulation Models to account for turbulent dissipation at subgrid scale and its intensity affects the efficiency of poleward heat transport by the atmospheric circulation. We perform sensitivity simulations with a dynamic-core GCM to investigate the effects of different intensities of hyperdiffusion and different model resolutions on the simulated equator-pole temperature gradient. We examine the different simulations using entropy production as a measure of baroclinic activity and show that there is a maximum in entropy production. In comparison to the climate at a state of maximum entropy production, every other simulated climate at a given resolution leads to an increased equator-pole temperature gradient. We then demonstrate that maximum entropy production can be used to tune low-resolution models to closely resemble the simulated climate of a high-resolution simulation. We conclude that tuning a GCM to a state of maximum entropy production is an efficient tool to tune low-resolution climate system models to adequately simulate the equator-pole temperature gradient.