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- ItemReliability of regional climate model simulations of extremes and of long-term climate(Göttingen : Copernicus GmbH, 2004) Böhm, U.; Kücken, M.; Hauffe, D.; Gerstengarbe, E.-W.; Werner, P.C.; Flechsig, M.; Keuler, K.; Block, A.; Ahrens, W.; Nocke, T.We present two case studies that demonstrate how a common evaluation methodology can be used to assess the reliability of regional climate model simulations from different fields of research. In Case I, we focused on the agricultural yield loss risk for maize in Northeastern Brazil during a drought linked to an El-Niño event. In Case II, the present-day regional climatic conditions in Europe for a 10-year period are simulated. To comprehensively evaluate the model results for both kinds of investigations, we developed a general methodology. On its basis, we elaborated and implemented modules to assess the quality of model results using both advanced visualization techniques and statistical algorithms. Besides univariate approaches for individual near-surface parameters, we used multivariate statistics to investigate multiple near-surface parameters of interest together. For the latter case, we defined generalized quality measures to quantify the model's accuracy. Furthermore, we elaborated a diagnosis tool applicable for atmospheric variables to assess the model's accuracy in representing the physical processes above the surface under various aspects. By means of this evaluation approach, it could be demonstrated in Case Study I that the accuracy of the applied regional climate model resides at the same level as that we found for another regional model and a global model. Excessive precipitation during the rainy season in coastal regions could be identified as a major contribution leading to this result. In Case Study II, we also identified the accuracy of the investigated mean characteristics for near-surface temperature and precipitation to be comparable to another regional model. In this case, an artificial modulation of the used initial and boundary data during preprocessing could be identified as the major source of error in the simulation. Altogether, the achieved results for the presented investigations indicate the potential of our methodology to be applied as a common test bed to different fields of research in regional climate modeling.
- ItemA new validation scheme for the evaluation of multiparameter fields(Abingdon : Taylor and Francis Ltd., 2005) Gerstengarbe, F.-W.; Kücken, M.; Werner, P.C.On the basis of an extended cluster analysis algorithm, we present a new validation method for the evaluation of simulation experiments characterized by more than one parameter. This method allows the assessment of any parameter combination in space and time. As an example for the effectiveness of the algorithm, the results of two regional climate model runs and observational data have been tested and interpreted.