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| Titel |
Developing and validating a model for the statistical downscaling of UK daily extreme precipitation |
| VerfasserIn |
D. Maraun, H. W. Rust, T. J. Osborn |
| 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 |
250030243
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| Zusammenfassung |
| Weather in the United Kingdom is dominated by the large scale
atmospheric circulation. To describe the relationship between the
large scale airflow and local scale extreme daily precipitation, we
developed a vector generalised additive model. This model uses airflow
strength, vorticity and direction to predict the extreme value
distribution of monthly maxima of daily precipitation at 689 rain
gauges across the UK. To avoid over-parameterisation, and to ensure a
high predictive power, we cross validated different versions of the
model based on quantile verification scores. We compared linear and
nonlinear versions, separate models for each season versus a model for
the whole year, a model without an explicit annual cycle versus a
model with an explicit annual cycle, and models with only one
predictive airflow variable instead of all three, and investigated the
spatial patterns of the cross validation for all seasons. We found
that relationships are considerably stable throughout the year so that
we could model the whole year using the same statistical model
including an additive annual cycle. Nevertheless, the relative
importance of the different air flow variables changes throughout the
year and spatially. Depending on location and season, linear trends
help to improve the model. |
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