The return period of wind storms over Europe

Abstract

Accurate assessment of the magnitude and frequency of extreme wind speed is of fundamental importance for many safety, engineering and reinsurance applications. We utilize the spatial and temporal consistency of the European Centre for Medium Range Forecasts ERA-40 reanalysis data to determine the frequency of extreme winds associated with wind storms over the eastern North Atlantic and Europe. Two parameters are investigated: 10-m wind gust and 10-m wind speed. The analysis follows two different view-points: In a spatially distributed view, wind-storm statistics are determined individually at each grid-point. In an integral, more generalized view, the wind-storm statistics are determined from extreme wind indices (EWI) that summarize storm magnitude and spatial extent. We apply classical peak over threshold (POT) extreme value analysis techniques (EVA) to the EWI and grid-point wind data. As a reference, a catalogue of the 200 most prominent European storms has been compiled based on available literature. The EWI-based return periods (RP) estimates of catalogue wind storms range from approximately 0.1 to 300 years, whereas grid-point-based RP estimates range from 0.1 to 500+ years. EWIs sensitive to the absolute magnitude of wind speed rank the RP of wind storms in the 1989/1990 and 1999/2000 extended winter season similarly to the RP derived from the distributed approach. The RP estimates derived from EWIs are generally higher when calculated using only land grid-points compared to RPs derived using whole domain. Both the uncertainties in EWIs and grid-point-based RPs show a greater dependence on the wind parameter used than on the uncertainty associated with the EVA for RPs less than 10 years, whereas for RPs greater than 10 years the effect of the different datasets is lower. The EWIs share up to approximately 50% of the variability of the local grid-point RPs.

Characterising the relationship between weather extremes in Europe and synoptic circulation features

“…For instance, Pfahl and Wernli (2012a) found a good correspondence between the timing of precipitation extremes in ERA-Interim and in the CMORPH satellite data set (see Joyce et al, 2004). Della-Marta et al (2009) analysed the representation of 200 severe European wind storms compiled from different observational sources in the ERA40 reanalysis, the predecessor of ERA-Interim. They found problems in the reanalysis wind gust data only in regions with high surface roughness, which were caused by a parameterisation issue that has been eliminated in ERA-Interim (cf.…”

“…Dee et al, 2011). An advantage of using wind data from reanalysis is the improved temporal homogeneity compared to many measurement time series (Della-Marta et al, 2009;Pfahl et al, 2009). …”

European extra-tropical storm damage risk from a multi-model ensemble of dynamically-downscaled global climate models

“…While using instantaneous values created the possibility of aliasing of the maximum wind field, whereby a storm front moved more than one grid box in six hours, this was preferable to using the six-hourly maximum 10 m gust, which is problematic in areas of high surface roughness (Della-Marta et al, 2009).…”

“…Many similar SSIs have been used previously in the literature (Della-Marta et al, 2009;Donat et al, 2010;Leckebusch et al, 2008) as well as in defining financial contracts based on parameters of observed or modelled wind speed (usually referred to as "Catastrophe Bonds"). Our SSI is similar to that of Leckebusch et al (2008) who used cubed wind speeds normalised by a local quantile.…”

A test for network‐wide trends in rainfall extremes

“…Extreme value theory (EVT) is widely used in climatology to estimate return periods of extreme events (van den Brink et al, 2005;Della-Marta et al, 2009) and in conjunction with risk assessment. It is also applied to homogenise climate data (Della-Marta and Wanner, 2006).…”