Comparative validation of statistical and dynamical downscaling models on a dense grid in central Europe: temperature

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67179843%3A_____%2F15%3A00437127" target="_blank" >RIV/67179843:_____/15:00437127 - isvavai.cz</a>
Alternative codes found
RIV/68378289:_____/15:00432098 RIV/00216208:11320/15:10312901 RIV/00216208:11310/15:10312901
Result on the web
<a href="http://dx.doi.org/10.1007/s00704-014-1190-3" target="_blank" >http://dx.doi.org/10.1007/s00704-014-1190-3</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s00704-014-1190-3" target="_blank" >10.1007/s00704-014-1190-3</a>

Result language
angličtina
Original language name
Comparative validation of statistical and dynamical downscaling models on a dense grid in central Europe: temperature
Original language description
Minimum and maximum temperature in two regional climate models and five statistical downscaling models are validated according to a unified set of criteria that have a potential relevance for impact assessments: persistence (temporal autocorrelations), spatial autocorrelations, extreme quantiles, skewness, kurtosis, and the degree of fit to observed data on both short and long times scales. The validation is conducted on two dense grids in central Europe as follows: (1) a station network and (2) a grid with a resolution of 10 km. The gridded dataset is not contaminated by artifacts of the interpolation procedure; therefore, we claim that using a gridded dataset as a validation base is a valid approach. The fit to observations in short time scales is equally good for the statistical downscaling (SDS) models and regional climate models (RCMs) in winter, while it is much better for the SDS models in summer. The reproduction of variability on long time scales, expressed as linear trends, is similarly successful by both SDS models and RCMs. Results for other criteria suggest that there is no justification for preferring dynamical models at the expense of statistical models—and vice versa. The non-linear SDS models do not outperform the linear ones.
Czech name
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Czech description
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Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
DG - Atmospheric sciences, meteorology
OECD FORD branch
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Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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