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| Titel |
Reliability of regional climate model simulations of extremes and of long-term climate |
| VerfasserIn |
U. Böhm, M. Kücken, D. Hauffe, F.-W. Gerstengarbe, P. C. Werner, M. Flechsig, K. Keuler, A. Block, W. Ahrens  , Th. Nocke |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1561-8633
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| Digitales Dokument |
URL |
| Erschienen |
In: Natural Hazards and Earth System Science ; 4, no. 3 ; Nr. 4, no. 3 (2004-06-21), S.417-431 |
| Datensatznummer |
250001693
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| Publikation (Nr.) |
 copernicus.org/nhess-4-417-2004.pdf |
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| Zusammenfassung |
| 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. |
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