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.

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.

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 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 Extreme wind speeds for various return periods during rainfall

1986 ◽  
Vol 1986 (27) ◽  
pp. 65-74
Author(s):  
Shuzo MURAKAMI ◽  
Yoshiteru IWASA ◽  
Yasushige MORIKAWA ◽  
Noriko CHINO
Keyword(s):  
Return Periods ◽  
Wind Speeds ◽  
Extreme Wind ◽  
Extreme Wind Speeds

Forecasting of Tornadoes and Downbursts

2020 ◽  
Author(s):  
Djordje Romanic
Keyword(s):  
Chaos Theory ◽  
Prediction Models ◽  
Weather Prediction ◽  
Small Scale ◽  
Weather Forecasts ◽  
Wind Speeds ◽  
The Past ◽  
Extreme Wind ◽  
Extreme Wind Speeds ◽  
Numerical Weather Prediction Models

Tornadoes and downbursts cause extreme wind speeds that often present a threat to human safety, structures, and the environment. While the accuracy of weather forecasts has increased manifold over the past several decades, the current numerical weather prediction models are still not capable of explicitly resolving tornadoes and small-scale downbursts in their operational applications. This chapter describes some of the physical (e.g., tornadogenesis and downburst formation), mathematical (e.g., chaos theory), and computational (e.g., grid resolution) challenges that meteorologists currently face in tornado and downburst forecasting.

Midlatitude cyclones in convection permitting climate simulations: the added value offered for extreme wind speeds and sting-jets

2021 ◽  
Author(s):  
Colin Manning ◽  
Elizabeth Kendon ◽  
Hayley Fowler ◽  
Nigel Roberts ◽  
Segolene Berthou ◽  
...  
Keyword(s):  
Climate Model ◽  
Surface Wind ◽  
Added Value ◽  
Large Contribution ◽  
High Wind ◽  
Wind Speeds ◽  
Wind Gusts ◽  
Climate Simulations ◽  
Extreme Wind ◽  
Extreme Wind Speeds

<p>Extra-tropical windstorms are one of the costliest natural hazards affecting Europe, and windstorms that develop a phenomenon known as a sting-jet account for some of the most damaging storms. A sting-jet (SJ) is a mesoscale core of high wind speeds that occurs in particular types of cyclones, specifically Shapiro-Keyser (SK) cyclones, and can produce extremely damaging surface wind gusts. High-resolution climate models are required to adequately model SJs and so it is difficult to gauge their contribution to current and future wind risk. In this study, we develop a low-cost methodology to automate the detection of sting jets, using the characteristic warm seclusion of SK cyclones and the slantwise descent of high wind speeds, within pan-European 2.2km convection-permitting climate model (CPM) simulations. Following this, we quantify the contribution of such storms to wind risk in Northern Europe in current and future climate simulations, and secondly assess the added value offered by the CPM compared to a traditional coarse-resolution climate model. This presentation will give an overview of the developed methods and the results of our analysis.</p><p>Comparing with observations, we find that the representation of wind gusts is improved in the CPM compared to ERA-Interim reanalysis data. Storm severity metrics indicate that SK cyclones account for the majority of the most damaging windstorms. The future simulation produces a large increase (>100%) in the number of storms exceeding high thresholds of the storm metric, with a large contribution to this change (40%) coming from windstorms in which a sting-jet is detected. Finally, we see a systematic underestimation in the GCM compared to the CPM in the frequency of extreme wind speeds at 850hPa in the cold sector of cyclones, likely related to better representation of sting-jets and the cold conveyor belt in the CPM. This underestimation is between 20-40% and increases with increasing wind speed above 35m/s. We conclude that the CPM adds value in the representation of severe surface wind gusts, providing more reliable future projections and improved input for impact models.</p>

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