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| Titel |
A comprehensive sensitivity analysis of high resolution regional climate simulations with WRF in the European Alpine region |
| VerfasserIn |
N. K. Awan, A. Gobiet |
| Konferenz |
EGU General Assembly 2009
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 11 (2009) |
| Datensatznummer |
250026248
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| Zusammenfassung |
| A high resolution (10km grid–spacing) mixed–physics ensemble is analyzed to investigate
the errors associated with the choice of physical parameterization and its impact on the
downscaling ability of a non-hydrostatic mesoscale-scale regional climate model in the
European Alpine region.
The National Center for Environmental Prediction /National Center for Atmospheric
Research (NCEP/NCAR) next generation Weather Research and Forecasting (WRF)
mesoscale model is applied in a two–step nesting setup to dynamically downscale the
ERA–40 re-analysis dataset of European Center for Medium-Range Weather Forecasts
(ECMWF). A total of sixteen one year simulations with varying physical parameterization
were carried out. The analysis is focused on the near–surface air–temperature and
precipitation over land. The precipitation is compared with a daily precipitation dataset
provided by the Swiss Federal Institute of Technology Zürich (ETH Zürich). The
near–surface air–temperature is compared with a recently published daily dataset
by the European Climate Assessment & Dataset (ECA& D). The seasonal model
error–characteristics are analyzed in nine climatological sub–regions defined by applying a
clustering method on the ETH dataset.
The analysis is focused on the ensemble’s range of errors, on temporal correlation,
normalized standard deviation and median deviation. The annual errors were found to be in
the range of 1.3 -C to -1.1 -C and 1.4 mm/day to 0.1 mm/day for temperature and surface
precipitation amount respectively. The results presented in this study provide an insight into
the model errors associated with physical parameterization and its consequent impact on the
model’s downscaling ability on regional and subregional scale. The analysis indicates that the
WRF model has a strong sensitivity to the choice of physical parameterization schemes and
significant improvements can be achieved by a suitable model configuration. This study can
be used as a guideline for setting up long term regional climate simulations with WRF. |
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