 |
| Titel |
Future changes in European winter storm losses and extreme wind speeds inferred from GCM and RCM multi-model simulations |
| VerfasserIn |
M. G. Donat, G. C. Leckebusch, S. Wild, U. Ulbrich |
| Medientyp |
Artikel
|
| Sprache |
Englisch
|
| ISSN |
1561-8633
|
| Digitales Dokument |
URL |
| Erschienen |
In: Natural Hazards and Earth System Science ; 11, no. 5 ; Nr. 11, no. 5 (2011-05-12), S.1351-1370 |
| Datensatznummer |
250009417
|
| Publikation (Nr.) |
 copernicus.org/nhess-11-1351-2011.pdf |
|
|
|
|
|
| Zusammenfassung |
| Extreme wind speeds and related storm loss potential in Europe have
been investigated using multi-model simulations from global (GCM) and regional
(RCM) climate models. Potential future changes due to anthropogenic climate
change have been analysed from these simulations following the IPCC SRES A1B
scenario. The large number of available simulations allows an estimation of
the robustness of detected future changes. All the climate models reproduced
the observed spatial patterns of wind speeds, although some models displayed
systematic biases. A storm loss model was applied to the GCM and RCM
simulated wind speeds, resulting in realistic mean loss amounts calculated
from 20th century climate simulations, although the inter-annual variability
of losses is generally underestimated. In future climate simulations,
enhanced extreme wind speeds were found over northern parts of Central and
Western Europe in most simulations and in the ensemble mean (up to 5%).
As a consequence, the loss potential is also higher in these regions,
particularly in Central Europe. Conversely, a decrease in extreme wind
speeds was found in Southern Europe, as was an associated reduction in loss
potential. There was considerable spread in the projected changes of
individual ensemble members, with some indicating an opposite signature to
the ensemble mean. Downscaling of the large-scale simulations with RCMs has
been shown to be an important source of uncertainty. Even RCMs with identical
boundary forcings can show a wide range of potential changes. The robustness
of the projected changes was estimated using two different measures. First,
the inter-model standard deviation was calculated; however, it is sensitive
to outliers and thus displayed large uncertainty ranges. Second, a
multi-model combinatorics approach considered all possible sub-ensembles from
GCMs and RCMs, hence taking into account the arbitrariness of model
selection for multi-model studies. Based on all available GCM and RCM
simulations, for example, a 25% mean increase in risk of loss for Germany
has been estimated for the end of the 21st century, with a 90% confidence range
of +15 to +35%. |
| |
|
| Teil von |
|
|
|
|
|
|
|
|