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| Titel |
On the bias correction of forcing global model data for regional climate simulations over West Africa |
| VerfasserIn |
Dominikus Heinzeller, Cornelia Klein, Joel Arnault, Jan Bliefernicht, Luitpold Hingerl, Harald Kunstmann |
| Konferenz |
EGU General Assembly 2014
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 16 (2014) |
| Datensatznummer |
250087082
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| Publikation (Nr.) |
 EGU/EGU2014-1151.pdf |
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| Zusammenfassung |
| With the advances in high-performance computing, regional climate simulations have been
taken to higher and higher resolution over the last decades. Whilst a higher spatial resolution
implies a more accurate representation of the terrain and the land surface properties, it does
not automatically lead to better results of the model. This limitation stems from
several facts: the bias of the driving global model data, the bias inherent in the
regional climate simulation, and the validity of physical parameterizations at high
resolution. These limitations and the high costs associated with an increase of the
resolution of the model have lead to a shift in paradigm towards ensemble modeling and
have highlighted the importance of bias-correction of the driving global model
data.
In this study, we compare the effects of two different bias-correction methods of the
driving global circulation model (GCM) data on the results of regional climate simulations
over West Africa. For both methods, ERA Interim Reanalysis data serves as reference for a
past 10-year period (e. g., 1990–2000). The bias-correction of the GCM data is
applied for the following 10-year period (e. g., 2000–2010). This data is used to drive
regional climate simulations over West Africa at a moderate resolution of 18 km. Data
collected from climate stations in West Africa along with satellite-gauge merged
precipitation products such as the 0.25 x 0.25 degree TRMM (Tropical Rainfall Measuring
Mission, Version 3B43) and the 1 x 1 degree GPCP 1DD (Global Precipitation
Climatology Project) are used to validate the regional climate simulations. Particular
importance is given to the accuracy of the predicted rainfall amount and the onset of the
rainy season, key elements for decision makers and the people of West Africa. |
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