scholarly journals Confidence Bounds for Extreme Wind Speed Estimates: A Comparison For the Gumbel - Burr XII Distribution and Classical Extreme Value Distributions wind speeds

2017 ◽  
Vol 4 (1) ◽  
pp. 259-271
Author(s):  
Patrick Osatohanmwen ◽  
Francis O Oyegue ◽  
Sunday Martins Ogbonmwan
Keyword(s):  
Wind Speed ◽  
Extreme Value ◽  
Extreme Value Distributions ◽  
Confidence Bounds ◽  
Burr Xii Distribution ◽  
Wind Speeds ◽  
Extreme Wind ◽  
Extreme Wind Speed

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.

Global Trends in Extreme Wind Speed and Wave Height

2013 ◽  
Author(s):  
I. R. Young ◽  
S. Zieger ◽  
J. Vinoth ◽  
A. V. Babanin
Keyword(s):  
Wind Speed ◽  
Wave Height ◽  
Global Climate ◽  
Extreme Value ◽  
Global Perspective ◽  
Ocean Engineering ◽  
Change Analysis ◽  
Data Set ◽  
Wind Speeds ◽  
Extreme Wind

Satellite observations of the ocean surface provide a powerful method for acquiring global data on wind speed and wave height. Radar altimeters have now been in operation for more than 25 years, providing a reasonably long term data set with global coverage. This paper presents data from a fully calibrated and validated altimeter dataset. The dataset provides the basis for obtaining a global perspective of a number of parameters critical to ocean engineering design, ship operations and global climate change. Analysis of the data provides ocean climatology of mean monthly values of wind speed and wave height useful for ship operations. The data set is also sufficiently long to provide extreme value (i.e. 100-year return period) estimates of wind speed and wave height. The paper presents such values and describes the approaches most appropriate to obtain statistically significant extreme value estimates from such satellite data. With a data set of this length, it is possible to investigate whether there have been statistically significant changes in the wind and wave climates over the period. Careful trend analysis of the extensive data set shows that there has been a statistically significant increasing trend in mean wind speed over the period. The corresponding increase in wave height is less clear. There is also evidence to suggest that extreme wind speeds and wave heights are increasing and the data set is analysed to investigate these trends. The paper clearly shows the value of this dataset and its application to a range of engineering problems.

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.

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 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.

scholarly journals Downslope windstorms and associated extreme wind speed statistics evaluation according to the COSMO-CLM Russian Arctic hindcast, ASR reanalysis and observations

2021 ◽  
Author(s):  
Vladimir Platonov ◽  
Anna Shestakova
Keyword(s):  
Wind Speed ◽  
Surface Wind ◽  
Temperature Fields ◽  
The Arctic ◽  
Russian Arctic ◽  
Novaya Zemlya ◽  
Wind Speeds ◽  
Extreme Wind ◽  
Extreme Wind Speed ◽  
Downslope Windstorms

<p>The number of severe weather events at the Arctic region increased significantly. Its formation related generally to the mesoscale processes including downslope windstorms over Novaya Zemlya, Svalbard, Tiksi bay accompanied by strong winds. Therefore, its investigation required detailed hydrometeorological and climatic information with a horizontal resolution of at least several kilometers. This work aims to investigate extreme wind speeds statistics associated with downslope windstorms and evaluate it according to the COSMO-CLM Russian Arctic hindcast, ASR reanalysis, stations and satellite data.</p><p>COSMO-CLM Russian Arctic hindcast created in 2020 covers the 1980–2016 period with grid size ~12 km and 1-hour output step, containing approximately a hundred hydrometeorological characteristics, as well at surface, as on the 50 model levels. The primary assessments of the surface wind speed and temperature fields showed good agreement with ERA-Interim reanalysis in large-scale patterns and many added values in the regional mesoscale features reproduction according to the coastlines, mountains, large lakes, and other surface properties.</p><p>Mean values, absolute and daily maxima of wind speed, high wind speed frequencies were estimated for the COSMO-CLM Russian Arctic hindcast and the well-known Arctic System Reanalysis (ASRv2) for a 2000-2016 period. COSMO-CLM showed higher mean and daily maximal wind speed areas concerned to coastal regions of Svalbard and Scandinavia, over the northern areas of Taymyr peninsula. At the same time, the absolute wind speed maxima are significantly higher according to ASRv2, specially over the Barents Sea, near the Novaya Zemlya coast (differences are up to 15-20 m/s). The same pattern observed by a number of days with wind speed above the 30 m/s threshold. Compared with station data, the ASRv2 reproduced mean wind speeds better at most coastal and inland station, MAE are within 3 m/s. For absolute wind speed maxima differences between two datasets get lower, the COSMO-CLM hindcast is quite better for inland stations.</p><p>Model capability to reproduce strong downslope windstorms evaluated according to the observations timeseries over Novaya Zemlya, Svalbard and Tiksi stations during bora conditions. Generally, the ASRv2 reproduced the wind direction closer to observations and the wind speed worser than COSMO-CLM. The extreme wind speed frequencies during bora cases have less errors according to COSMO-CLM hindcast (up to ~5%) compared to the ASRv2 data (up to 10%). At the same time, moderate wind speed frequencies are reproduced by ASRv2 better.</p><p>Five specific Novaya Zemlya bora cases were evaluated according to SAR satellite wind speed data. Both ASRv2 and COSMO-CLM overestimated mean wind speed (MAE 0.5-6 m/s), maximal wind speed bias has different signs, however, the COSMO-CLM is better in most cases. Extreme percentiles biases (99 and 99.9%), correlation, structure and amplitude (according to the SAL method) are closer to observations by the COSMO-CLM hindcast.</p>

scholarly journals A Novel Sea Surface Roughness Parameterization Based on Wave State and Sea Foam

2021 ◽  
Vol 9 (3) ◽  
pp. 246
Author(s):  
Difu Sun ◽  
Junqiang Song ◽  
Xiaoyong Li ◽  
Kaijun Ren ◽  
Hongze Leng
Keyword(s):  
Surface Roughness ◽  
Wind Speed ◽  
Drag Coefficient ◽  
Sea Surface ◽  
High Wind Speed ◽  
Wave State ◽  
Wind Speeds ◽  
Sea Surface Roughness ◽  
Extreme Wind ◽  
The Impact

A wave state related sea surface roughness parameterization scheme that takes into account the impact of sea foam is proposed in this study. Using eight observational datasets, the performances of two most widely used wave state related parameterizations are examined under various wave conditions. Based on the different performances of two wave state related parameterizations under different wave state, and by introducing the effect of sea foam, a new sea surface roughness parameterization suitable for low to extreme wind conditions is proposed. The behaviors of drag coefficient predicted by the proposed parameterization match the field and laboratory measurements well. It is shown that the drag coefficient increases with the increasing wind speed under low and moderate wind speed conditions, and then decreases with increasing wind speed, due to the effect of sea foam under high wind speed conditions. The maximum values of the drag coefficient are reached when the 10 m wind speeds are in the range of 30–35 m/s.

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