Extreme wind speed climatology over Greece

2021 ◽  
Author(s):  
Georgios Blougouras ◽  
Chris G. Tzanis ◽  
Kostas Philippopoulos
Keyword(s):  
Wind Speed ◽  
Confidence Intervals ◽  
Wind Turbines ◽  
Economic Losses ◽  
Return Periods ◽  
Wind Speeds ◽  
Return Levels ◽  
Extreme Wind ◽  
Extreme Wind Speed ◽  
Extreme Wind Speeds

<p>Extreme wind speeds are a multifaceted environmental risk. They may cause considerable damage to infrastructure (e.g., bridges, private property), they can jeopardize maritime and aviation activities, and sometimes even human safety. Furthermore, the design of wind turbines for on and off-shore wind farms requires a study of the return periods of extreme wind speeds in combination with the lifespan of the wind turbines. Windstorms also result in major economic losses and cause up to 80 % of the natural hazards' long term insurance loss in Europe. The scope of this work is to identify location-specific extreme wind speed thresholds and obtain accurate estimates of exceedances for multiple future horizons. In this context, the Extreme Value Analysis framework is used for providing the return periods and the respective return levels of extreme wind speeds. The Peaks Over Threshold method is utilized for the 10 m wind speed for a domain centered over Greece, in Southeastern Mediterranean. Wind speed data at 10 m are extracted from the ERA5 reanalysis dataset that provides hourly estimates of surface wind speed with a horizontal resolution of 0.25°x0.25°, from 1979/01/01 up to 2019/12/31 (i.e., 41 years). The thresholds are selected using the Mean Residual Life plots, which is the most reliable method for identifying accurate threshold values. The seasonal analysis of the exceedances is discussed in terms of the physical mechanisms in the region. The exceedances are modelled using the Generalized Pareto Distribution, whose shape and scale parameters (<em>ξ</em> and <em>σ</em>, respectively) are estimated using the Maximum Likelihood Estimation method. The return levels and their confidence intervals are estimated for return periods up to 100 years. Geographic Information Systems are used for mapping future projections of extreme wind speeds and the corresponding confidence intervals. The results are discussed in terms of identifying high-risk areas and the findings could assist in informed decision-making in the wind energy industry. The proposed methodological framework could be extended to other areas characterized by particularly high wind speeds and the results can contribute towards sustainable investments and support adaptation mechanisms.</p>

scholarly journals Extreme wind speed prediction in mountainous area with mixed wind climates

2022 ◽  
Author(s):  
Teng Ma ◽  
Wei Cui ◽  
Lin Zhao ◽  
Yejun Ding ◽  
Genshen Fang ◽  
...  
Keyword(s):  
Wind Speed ◽  
Mountainous Area ◽  
Construction Site ◽  
Wind System ◽  
Mountainous Areas ◽  
Wind Speeds ◽  
Extreme Wind ◽  
Synoptic Wind ◽  
Extreme Wind Speed ◽  
Extreme Wind Speeds

Abstract In addition to common synoptic wind system, the mountainous terrain forms a local thermally driven wind system, which makes the mountain wind system have strong terrain dependence. Therefore, in order to estimate the reliable design wind speeds for structural safety, the samples for extreme wind speeds for certain return periods at mountainous areas can only come from field measurements at construction site. However, wind speeds measuring duration is usually short in real practice. This work proposes a novel method for calculating extreme wind speeds in mountainous areas by using short-term field measurement data and long-term nearby meteorological observatory data. Extreme wind speeds in mountainous area are affected by mixed climates composed by local-scale wind and large scale synoptic wind. The local winds can be recorded at construction site with short observatory time, while the extreme wind speeds samples from synoptic wind climate from nearby meteorological station with long observatory time is extracted for data augmentation. The bridge construction site at Hengduan Mountains in southwestern China is taken as an example in this study. A 10-month dataset of field measurement wind speeds is recorded at this location. This study firstly provides a new method to extract wind speed time series of windstorms. Based on the different windstorm features, the local and synoptic winds are separated. Next, the synoptic wind speeds from nearby meteorological stations are converted and combined with local winds to derive the extreme wind speeds probability distribution function. The calculation results shows that the extreme wind speed in the short return period is controlled by the local wind system, and the long-period extreme wind speed is determined by the synoptic wind system in the mountain area.

scholarly journals An Improved Typhoon Simulation Method Based On Latin Hypercube Sampling Method

2021 ◽  
Author(s):  
Jianpeng Sun ◽  
Guanjun Lv ◽  
Wenfeng Huang ◽  
Rong Wang ◽  
Xiaogang Ma
Keyword(s):  
Sampling Method ◽  
Correlation Coefficients ◽  
Latin Hypercube Sampling ◽  
Simulation Method ◽  
Return Periods ◽  
Latin Hypercube ◽  
Wind Speeds ◽  
Extreme Wind ◽  
Extreme Wind Speed ◽  
Extreme Wind Speeds

Abstract In order to further improve the prediction accuracy of typhoon simulation method for extreme wind speed in typhoon prone areas, an improved typhoon simulation method is proposed by introducing the Latin hypercube sampling method into the traditional typhoon simulation method. In this paper, the improved typhoon simulation method is first given a detailed introduction. Then, this method is applied to the prediction of extreme wind speeds under various return periods in Hong Kong. To validate this method, two aspects of analysis is carried out, including correlation analysis among typhoon key parameters and prediction of extreme wind speeds under various return periods. The results show that the correlation coefficients among typhoon key parameters can be maintained satisfactorily with this improved typhoon simulation method. Compared with the traditional typhoon simulation method, extreme wind speeds under various return periods obtained with this improved typhoon simulation method are much closer to the results obtained with historical typhoon wind data.

scholarly journals The Compound Inverse Rayleigh as an Extreme Wind Speed Distribution and its Bayes Estimation

2021 ◽  
Author(s):  
Elio Chiodo ◽  
Maurizio Fantauzzi ◽  
Giovanni Mazzanti
Keyword(s):  
Wind Speed ◽  
Prior Information ◽  
Extreme Values ◽  
Rayleigh Distribution ◽  
Bayes Estimation ◽  
Large Set ◽  
Wind Speeds ◽  
Extreme Wind ◽  
Extreme Wind Speed ◽  
Extreme Wind Speeds

The paper deals with the Compound Inverse Rayleigh distribution, shown to constitute a proper model for the characterization of the probability distribution of extreme values of wind-speed, a topic which is gaining growing interest in the field of renewable generation assessment, both in view of wind power production evaluation and the wind-tower mechanical reliability and safety. The first part of the paper illustrates such model starting from its origin as a generalization of the Inverse Rayleigh model - already proven to be a valid model for extreme wind-speeds - by means of a continuous mixture generated by a Gamma distribution on the scale parameter, which gives rise to its name. Moreover, its validity to interpret different field data is illustrated, also by means of numerous numerical examples based upon real wind speed measurements. Then, a novel Bayes approach for the estimation of such extreme wind-speed model is proposed. The method relies upon the assessment of prior information in a practical way, that should be easily available to system engineers. In practice, the method allows to express one’s prior beliefs both in terms of parameters, as customary, and/or in terms of probabilities. The results of a large set of numerical simulations – using typical values of wind-speed parameters - are reported to illustrate the efficiency and the accuracy of the proposed method. The validity of the approach is also verified in terms of its robustness with respect to significant differences compared to the assumed prior information.

Extreme wind speeds for various return periods during rainfall

1987 ◽  
Vol 26 (1) ◽  
pp. 105-125 ◽  
Author(s):  
Shuzo Murakami ◽  
Yoshiteru Iwasa ◽  
Yasushige Morikawa ◽  
Noriko Chino
Keyword(s):  
Return Periods ◽  
Wind Speeds ◽  
Extreme Wind ◽  
Extreme Wind Speeds

scholarly journals Improvement of typhoon wind hazard model and its sensitivity analysis

2019 ◽  
Author(s):  
Yunxia Guo ◽  
Yijun Hou ◽  
Peng Qi
Keyword(s):  
Wind Speed ◽  
Pressure Profile ◽  
Hazard Model ◽  
Extreme Value ◽  
Return Periods ◽  
Extreme Value Distributions ◽  
Extreme Wind ◽  
Wind Hazard ◽  
Extreme Wind Speed ◽  
Typhoon Wind

Abstract. Typhoons are one of the most serious natural disasters that occur annually on China’s southeast coast. This paper describes a technique for analyzing the typhoon wind hazard based on the empirical track model. Existing simplified and non-simplified typhoon empirical track models are improved, and the improved tracking models are shown to significantly increase the correlation in regression analysis. We also investigate quantitatively the sensitivity of the typhoon wind hazard model. The effects of different typhoon decay models, the simplified and non-simplified typhoon tracking models, different statistical models for the radius to maximum winds (Rmax) and Holland pressure profile parameter (B), and different extreme value distributions on the predicted extreme wind speed of different return periods are all investigated. Comparisons of estimated typhoon wind speeds for 50-year and 100-year return periods under the influence of different factors are presented. The different models of Rmax and B are found to have greatest impact on the prediction of extreme wind speed, followed by the extreme value distributions, typhoon tracking models, and typhoon decay models. This paper constitutes a useful reference for predicting extreme wind speed using the empirical track model.

Extreme Wind Speeds and Their Prediction for Wind Turbines

2013 ◽  
Vol 37 (6) ◽  
pp. 595-603 ◽  
Author(s):  
Janardan Rohatgi ◽  
Alex Araújo ◽  
Ana Rosa Primo
Keyword(s):  
Wind Turbines ◽  
Wind Speeds ◽  
Extreme Wind ◽  
Extreme Wind Speeds

scholarly journals Wind storm loss estimations in the Canton of Vaud (Western Switzerland)

2012 ◽  
Vol 12 (12) ◽  
pp. 3789-3798 ◽  
Author(s):  
C. Etienne ◽  
M. Beniston
Keyword(s):  
Population Data ◽  
Geographic Area ◽  
Economic Losses ◽  
Daily Maximum ◽  
Insurance Company ◽  
Wind Speeds ◽  
Extreme Wind ◽  
Storm Duration ◽  
Extreme Wind Speed ◽  
Weather Stations

Abstract. A storm loss model that was first developed for Germany is applied to the much smaller geographic area of the canton of Vaud, in Western Switzerland. 24 major wind storms that struck the region during the period 1990–2010 are analysed, and outputs are compared to loss observations provided by an insurance company. Model inputs include population data and daily maximum wind speeds from weather stations. These measured wind speeds are regionalised in the canton of Vaud following different methods, using either basic interpolation techniques from Geographic Information Systems (GIS), or by using an existing extreme wind speed map of Switzerland whose values are used as thresholds. A third method considers the wind power, integrating wind speeds temporally over storm duration to calculate losses. Outputs show that the model leads to similar results for all methods, with Pearson's correlation and Spearman's rank coefficients of roughly 0.7. Bootstrap techniques are applied to test the model's robustness. Impacts of population growth and possible changes in storminess under conditions of climate change shifts are also examined for this region, emphasizing high shifts in economic losses related to small increases of input wind speeds.

scholarly journals Wavelet Scale Variance Analysis of Wind Extremes in Mountainous Terrains

Energies ◽  
2019 ◽  
Vol 12 (16) ◽  
pp. 3048 ◽  
Author(s):  
Telesca ◽  
Guignard ◽  
Helbig ◽  
Kanevski
Keyword(s):  
Wind Speed ◽  
Average Wind Speed ◽  
Wind Speeds ◽  
Speed Distribution ◽  
Average Wind ◽  
Wind Speed Distribution ◽  
Extreme Wind ◽  
Wavelet Variance ◽  
Extreme Wind Speeds ◽  
Wind Extremes

The 10-min average wind speed series recorded at 130 stations distributed rather homogeneously in the territory of Switzerland are investigated. Fixing a percentile-based threshold of the wind speed distribution, a wind extreme is defined as the duration of the sequence of consecutive wind values above the threshold. This definition allows to analyze the sequence of extremes as a temporal point process marked by their duration. Representing the sequence of wind extremes by the inter-extreme interval series, the wavelet variance, a useful tool to investigate the variance of a time series across scales, was applied in order to find a link between the wavelet scales and several topographic parameters. Our findings suggest that the mean duration of wind extremes and mean inter-extreme time are positively correlated and that such relationship depends on the threshold of the wind speed. Furthermore, the threshold of the wind speed distribution correlates best with a terrain parameter related to the Laplacian of terrain elevations; and, in particular, for wavelet scales less than 3, the terrain exposure may explain the formation of extreme wind speeds.

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