TY  - JOUR
A1  - Böhm, Uwe
A1  - Kucken, M.
A1  - Hauffe, D.
A1  - Gerstengarbe, F. W.
A1  - Werner, P. C.
A1  - Flechsig, M.
A1  - Keuler, K.
A1  - Block, A.
A1  - Ahrens, W.
A1  - Nocke, T.
T1  - Reliability of regional climate model simulations of extremes and of long-term climate
N2  - 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-Nino 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
Y1  - 2004
SN  - 1561-8633
ER  - 
TY  - JOUR
A1  - Nocke, T.
A1  - Schumann, H.
A1  - Böhm, Uwe
T1  - Methods for the visualization of clustered climate data
N2  - Increasing amounts of large climate data require new analysis techniques. The area of data mining investigates new paradigms and methods including factors like scalability, flexibility and problem abstraction for large data sets. The field of visual data mining in particular offers valuable methods for analyzing large amounts of data intuitively. In this paper we describe our approach of integrating cluster analysis and visualization methods for the exploration of climate data. We integrated cluster algorithms, appropriate visualization techniques and sophisticated interaction paradigms into a general framework
Y1  - 2004
SN  - 0943-4062
ER  -