Serial clustering of intense European storms

Vitolo, Renato; Stephenson, David B.; Cook, Ian; Mitchell-Wallace, Kirsten

doi:10.1127/0941-2948/2009/0393

Cited by 134 publications

(173 citation statements)

References 15 publications

Supporting

Mentioning

148

Contrasting

Order By: Relevance

“…If the coefficient of dispersion is different from 1, it would point to violations of the Poisson assumptions (Smith and Karr, 1983;Karr, 1991;Mailier et al, 2006;Vitolo et al, 2009). For each of the stations, the coefficient of dispersion from the data is computed.…”

Section: Poisson Modelling and Impact Of Naomentioning

confidence: 99%

“…Even though the theoretical Poisson distribution has a coefficient of dispersion equal to 1, it is often the case that the data exhibits a variance that is larger than the mean (overdispersion), implying violation of the Poisson assumptions and pointing to clustering (Smith and Karr, 1983;Karr, 1991;Mailier et al, 2006;Vitolo et al, 2009). Assessment of these assumptions is performed by computing the coefficient of dispersion of the POT data for each station.…”

Section: Poisson Regression Modelmentioning

confidence: 99%

See 1 more Smart Citation

Analyses of extreme flooding in Austria over the period 1951–2006

Villarini

Smith

Serinaldi

et al. 2011

Intl Journal of Climatology

View full text Add to dashboard Cite

ABSTRACT:Analyses of extreme flooding in Austria is performed using daily discharge time series from 27 stations over the period . The main research questions revolve around: (1) temporal non-stationarities in the flood record, (2) upper tail and scaling properties of the flood peak records, and (3) relation between magnitude and frequency of flooding and the North Atlantic Oscillation (NAO). Two datasets are derived from the daily discharge time series: annual maximum daily discharge and peaks-over-threshold (POT) data. The validity of the stationarity assumption in the annual maximum discharge record is assessed by investigating the presence of abrupt and slowly varying changes using nonparametric tests. The time series are tested for abrupt changes both in the mean and variance of the flood peak distributions by means of the Pettitt test. The presence of monotonic trends is investigated by means of the Mann-Kendall and Spearman tests. Violations of the stationarity assumption are associated with abrupt rather than gradual changes. These step changes generally involve river regulation through construction of dams or other major engineering works. It is not possible to make conclusive statements about the presence of an anthropogenic climate change signal in the flood peak record. Similar conclusions are obtained when focussing on the frequency of POT floods. The Generalised Extreme Value distribution is used to study the upper tail and scaling properties of annual maximum daily discharge records. The location and scale parameters exhibit power-law behaviour as a function of drainage area. The shape parameters indicate that the flood peak distributions for Austria have a heavy tail. Non-stationary modelling of the annual maximum daily discharge and POT time series is used to explore the relation between flood magnitude and frequency and NAO. The results indicate that NAO is a significant covariate in explaining the magnitude and frequency of occurrence of flooding over a large part of Austria.

show abstract

Section: Poisson Modelling and Impact Of Naomentioning

confidence: 99%

Section: Poisson Regression Modelmentioning

confidence: 99%

Analyses of extreme flooding in Austria over the period 1951–2006

Villarini

Smith

Serinaldi

et al. 2011

Intl Journal of Climatology

View full text Add to dashboard Cite

show abstract

“…from an homogeneous Poisson 10 process (Mailier et al 2006). Furthermore, clustering was also found to increase for more extreme wind speeds (Vitolo et al 2009), in contradiction to the assumption often made by actuaries suitable for identically distributed variables. This research raised much awareness about clustering in the natural catastrophe insurance industry that has led to major developments in windstorm catastrophe models (Khare et al 2014).…”

Section: Uncertainty Quantification In Windstorm Hazard Estimationmentioning

confidence: 60%

Epistemic uncertainties and natural hazard risk assessment. 1. A review of different natural hazard areas

Beven¹,

Almeida²,

Aspinall³

et al. 2017

Preprint

Self Cite

View full text Add to dashboard Cite

This paper discusses how epistemic uncertainties are considered in a number of different natural hazard areas including floods, landslides and debris flows, dam safety, droughts, earthquakes, tsunamis, volcanic ash clouds and pyroclastic flows, and wind storms. In each case it is common practice to treat most uncertainties in the form of aleatory 20 probability distributions but this may lead to an underestimation of the resulting uncertainties in assessing the hazard, consequences and risk. It is suggested that such analyses might be usefully extended by looking at different scenarios of assumptions about sources of epistemic uncertainty, with a view to reducing the element of surprise in future hazard occurrences. Since every analysis is necessarily conditional on the assumptions made about the nature of sources of epistemic uncertainty it is also important to follow the guidelines for good practice suggested in the companion Part 2. 25

show abstract

“…For example European windstorm Daria (24-26 January 1990), the most damaging event on record, incurred USD 8.2 billion of insured loss (indexed to 2012, Roberts et al, 2014). In addition, windstorms often arrive in quick succession, increasing the risk of large aggregate losses (Vitolo et al, 2009). Indeed, windstorms Vivian, Herta and Wiebke occurred closely after windstorm Daria, in February 1990, costing the insurance industry an additional USD 5.6 billion, USD 1.5 billion and USD 1.4 billion respectively (indexed to 2012, Roberts et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

The 21st century decline in damaging European windstorms

Dawkins

Stephenson

Lockwood

et al. 2016

Nat. Hazards Earth Syst. Sci.

Self Cite

View full text Add to dashboard Cite

Abstract. A decline in damaging European windstorms has led to a reduction in insured losses in the 21st century. This decline is explored by identifying a damaging windstorm characteristic and investigating how and why this characteristic has changed in recent years. This novel exploration is based on 6103 high-resolution model-generated historical footprints , representing the whole European domain.The footprint of a windstorm is defined as the maximum wind gust speed to occur at a set of spatial locations over the duration of the storm. The area of the footprint exceeding 20 ms −1 over land, A 20 , is shown to be a good predictor of windstorm damage. This damaging characteristic has decreased in the 21st century, due to a statistically significant decrease in the relative frequency of windstorms exceeding 20 ms −1 in north-western Europe, although an increase is observed in southern Europe. This is explained by a decrease in the quantiles of the footprint wind gust speed distribution above approximately 18 ms −1 at locations in this region. In addition, an increased variability in the number of windstorm events is observed in the 21st century.Much of the change in A 20 is explained by the North Atlantic Oscillation (NAO). The correlation between winter total A 20 and winter-averaged mean sea-level pressure resembles the NAO pattern, shifted eastwards over Europe, and a strong positive relationship (correlation of 0.715) exists between winter total A 20 and winter-averaged NAO. The shifted correlation pattern, however, suggests that other modes of variability may also play a role in the variation in windstorm losses.

show abstract

Serial clustering of intense European storms

Cited by 134 publications

References 15 publications

Analyses of extreme flooding in Austria over the period 1951–2006

Analyses of extreme flooding in Austria over the period 1951–2006

Epistemic uncertainties and natural hazard risk assessment. 1. A review of different natural hazard areas

The 21st century decline in damaging European windstorms

Contact Info

Product

Resources

About