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| Titel |
Joint probabilities of extreme precipitation and wind gusts in Germany |
| VerfasserIn |
H. von Waldow, O. Martius |
| Konferenz |
EGU General Assembly 2012
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 14 (2012) |
| Datensatznummer |
250070529
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| Zusammenfassung |
| Extreme meteorological events such as storms, heavy rain, floods, droughts and heat waves
can have devastating consequences for human health, infrastructure and ecosystems.
Concomitantly occurring extreme events might interact synergistically to produce a
particularly hazardous impact. The joint occurrence of droughts and heat waves, for example,
can have a very different impact on human health and ecosystems both in quantity and
quality, than just one of the two extreme events.
The co-occurrence of certain types of extreme events is plausible from physical and
dynamical considerations, for example heavy precipitation and high wind speeds in the
pathway of strong extratropical cyclones. The winter storm Kyrill not only caused
wind gust speeds well in excess of 30Â m/s across Europe, but also brought 24Â h
precipitation sums greater than the mean January accumulations in some regions. However,
the existence of such compound risks is currently not accounted for by insurance
companies, who assume independence of extreme weather events to calculate their
premiums.
While there are established statistical methods to model the extremes of univariate
meteorological variables, the modelling of multidimensional extremes calls for an approach
that is tailored to the specific problem at hand. A first step involves defining extreme bivariate
wind/precipitation events. Because precipitation and wind gusts caused by the same cyclone
or convective cell do not occur at exactly the same location and at the same time, it is
necessary to find a sound definition of “extreme compound event” for this case. We present a
data driven method to choose appropriate time and space intervals that define “concomitance”
for wind and precipitation extremes. Based on station data of wind speed and gridded
precipitation data, we arrive at time and space intervals that compare well with the
typical time and space scales of extratropical cyclones, i.e. a maximum time lag of
1Â day and a maximum distance of about 300Â km between associated wind and rain
events.
After modelling extreme precipitation and wind separately, we explore the practicability
of characterising their joint distribution using a bivariate threshold excess model. In
particular, we present different dependence measures and report about the computational
feasibility and available computer codes. |
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