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    Enhancing the efficiency of terrestrial biosphere model simulations by reducing the redundancy in global forcing data sets
    (2005-01-10T19:51:15Z) Kleidon, Axel
    Data 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.
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    Hyperdiffusion, maximum entropy production, and the simulated equator-pole temperature gradient in an atmospheric general circulation model
    (2005-01-10T19:47:03Z) Kleidon, Axel
    Hyperdiffusion 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.