A new statistical approach to extreme wind speeds in France

Sacre, Christian; Moisselin, Jean‐Marc; Sabre, Maeva; Flori, Jean-Paul; Dubuisson, Brigitte

doi:10.1016/j.jweia.2007.02.013

Cited by 16 publications

(14 citation statements)

References 14 publications

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“…The generalized extreme value (GEV) model is often chosen to describe the extremes of natural agents in wind engineering (Brabson and Palutikof, 2000;Gatey and Miller, 2007;Sacré et al, 2007;Torrielli et al, 2013;Valamanesh et al, 2015) and also in several other branches of civil engineering and geosciences. In line with this, a Poisson-Pareto model (Eq.…”

Section: Analytical Frameworkmentioning

confidence: 99%

The selection of directional sectors for the analysis of extreme wind speed

Folgueras

Solari

Losada

2019

Nat. Hazards Earth Syst. Sci.

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Abstract. This paper presents a rational method for the selection of the most suitable directional sectors in the analysis of extreme wind loads on structures. It takes into consideration the main sources of uncertainty stemming from sector selection and leads to the definition of independent and statistically homogeneous directional sectors. This method is applied to the selection of directional sectors for the calculation of the design wind speed of a structure located at the mouth of the Río de la Plata. The results in the estimated reliability and costs were compared to those obtained with conventional engineering methods, revealing significant differences. It was found that the proposed method is a simple and objective tool for the selection of directional sectors, which comply with the working hypothesis of the directional models, and offers better guarantees for dimensioning than the use of more traditional engineering approaches for sectorial division.

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Section: Analytical Frameworkmentioning

confidence: 99%

The selection of directional sectors for the analysis of extreme wind speed

Folgueras

Solari

Losada

2019

Nat. Hazards Earth Syst. Sci.

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“…(a) [24], (b) [73], (c) [3], (d) [90], (e) [6], ( f ) [10], (g) [12], (h) [4], (i) [75], ( j) [98], (k) [101], (l) [51], (m) [13], (n) [79], (o) [5], (p) [18], (q) [36], (r) [67], (s) [86,87], (t) [83], (u) [46],…”

Section: Roughness Length and Displacement Height: Literature Reviewmentioning

confidence: 99%

“…Also in Table 2.1, there are some values of z 0 and d arising from applications of specific numerical models with their land cover databases. For example, [75] used them in lakes and lagoons; [101] in rocky outcrops and rocks, evergreen forests, salt marshes, wetlands, bare soils, and artificial coverages; [21] in evergreen forests; [57] used in no citrus fruit trees; [82] in grasslands; and [81] in ravine and road, parking or unvegetated pedestrian areas.…”

Section: Roughness Length and Displacement Height: Literature Reviewmentioning

confidence: 99%

Characterization of Geographical and Meteorological Parameters

Montero

Rodríguez

Oliver

2018

Wind Field and Solar Radiation Characterization and Forecasting

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This chapter is devoted to the introduction of some geographical and meteorological information involved in the numerical modeling of wind fields and solar radiation. Firstly, a brief description of the topographical data given by a Digital Elevation Model and Land Cover databases are provided. In particular, the Information System of Land Cover of Spain (SIOSE) is considered. The study is focused in the roughness length and the displacement height parameters that appear in the logarithmic wind profile, as well as in the albedo related to solar radiation computation. An extended literature review and characterization of both parameters are reported. Next, the concept of atmospheric stability is introduced from the Monin-Obukhov similarity theory to the recent revision of Zilitinkevich of the Neutral and Stable Boundary Layers (SBL). The latter considers the effect of the free-flow static stability and baroclinicity on the turbulent transport of momentum and of the Convective Boundary Layers (CBL), more precisely, the scalars in the boundary layer, as well as the model of turbulent entrainment. 2.1 Geographical data The main geographical information for wind and solar radiation modeling may be classified into two general databases, the topographical data related to the orography of the region to be studied and the land cover databases containing the information of the land uses. In this section, both are introduced.

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“…Generally, the average speed of a station tends to smooth observations and on the contrary the only maximum gust tends to exaggerate the phenomena. (18) We tried to determine an intermediate solution by coupling the data of several stations for every department. We thus retain at least three stations for every department.…”

Section: Some Issuesmentioning

confidence: 99%

“…Classical techniques for the prediction of future claim amounts are based solely on companies' information (portfolios and damage), which leads to some typical problems. The insurers keep detailed historical data only for a short span of around [15][16][17][18][19][20] years. This lack of information makes it more difficult to get reliable results, in particular for the most extreme events that are also the least frequent ones.…”

Section: Introductionmentioning

confidence: 99%

Index for Predicting Insurance Claims from Wind Storms with an Application in France

Mornet

Opitz

Luzi³

et al. 2015

Risk Analysis

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For insurance companies, wind storms represent a main source of volatility, leading to potentially huge aggregated claim amounts. In this article, we compare different constructions of a storm index allowing us to assess the economic impact of storms on an insurance portfolio by exploiting information from historical wind speed data. Contrary to historical insurance portfolio data, meteorological variables show fewer nonstationarities between years and are easily available with long observation records; hence, they represent a valuable source of additional information for insurers if the relation between observations of claims and wind speeds can be revealed. Since standard correlation measures between raw wind speeds and insurance claims are weak, a storm index focusing on high wind speeds can afford better information. A storm index approach has been applied to yearly aggregated claim amounts in Germany with promising results. Using historical meteorological and insurance data, we assess the consistency of the proposed index constructions with respect to various parameters and weights. Moreover, we are able to place the major insurance events since 1998 on a broader horizon beyond 40 years. Our approach provides a meteorological justification for calculating the return periods of extreme-storm-related insurance events whose magnitude has rarely been reached.

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A new statistical approach to extreme wind speeds in France

Cited by 16 publications

References 14 publications

The selection of directional sectors for the analysis of extreme wind speed

The selection of directional sectors for the analysis of extreme wind speed

Characterization of Geographical and Meteorological Parameters

Index for Predicting Insurance Claims from Wind Storms with an Application in France

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