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| Titel |
A pragmatic approach for the downscaling and bias correction of regional climate simulations: evaluation in hydrological modeling |
| VerfasserIn |
T. Marke, W. Mauser, A. Pfeiffer, G. Zängl |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1991-959X
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| Digitales Dokument |
URL |
| Erschienen |
In: Geoscientific Model Development ; 4, no. 3 ; Nr. 4, no. 3 (2011-09-07), S.759-770 |
| Datensatznummer |
250001785
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| Publikation (Nr.) |
 copernicus.org/gmd-4-759-2011.pdf |
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| Zusammenfassung |
| The present study investigates a statistical approach for the downscaling of
climate simulations focusing on those meteorological parameters most
commonly required as input for climate change impact models (temperature,
precipitation, air humidity and wind speed), including the option to correct
biases in the climate model simulations. The approach is evaluated by the
utilization of a hydrometeorological model chain consisting of (i) the
regional climate model MM5 (driven by reanalysis data at the boundaries of
the model domain), (ii) the downscaling and model interface SCALMET, and (iii)
the physically based hydrological model PROMET. The results of different
hydrological model runs set up for the historical period 1971–2000 are
compared to discharge recordings at the gauge of the Upper Danube Watershed
(Central Europe) on a daily time basis. To avoid "in-sample" evaluation, a
cross-validation approach is followed splitting the period in two halves of
15 yr. While one half is utilized to derive the downscaling functions
based on spatially distributed observations (e.g. 1971–1985), the other is
used for the application of the downscaling functions within the
hydrometeorological model chain (e.g. 1986–2000). By alternately using both
parts for the generation and the application of the downscaling functions,
discharge simulations are generated for the whole period 1971–2000. The
comparison of discharge simulations and observations reveals that the
presented approaches allow for a more accurate simulation of discharge in
the catchment of the Upper Danube Watershed and the considered gauge at the
outlet in Achleiten. The correction for subgrid-scale variability is shown
to reduce biases in simulated discharge compared to the utilization of
bilinear interpolation. Further enhancements in model performance could be
achieved by a correction of biases in the RCM data within the downscaling
process. These findings apply to the cross-validation experiment as well as
to an "in-sample" application, where the whole period 1971–2000 is used for
the generation and the application of the downscaling functions. Although
the presented downscaling approach strongly improves the performance of the
hydrological model, deviations from the observed discharge conditions
persist that are not found when driving the hydrological model with
spatially distributed meteorological observations. |
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