A Model for Predicting Wind Speed and the Probability of a Wind Gust

2021 ◽  
Author(s):  
Vladimir Victorovich Dotsenko ◽  
Evgeny Victorovich Sentsov ◽  
Alexander Mikhailovich Litvinenko ◽  
Victor Nikolaevich Mesherekov ◽  
Stanimir Valtchev
Keyword(s):  
Wind Speed ◽  
Wind Gust

scholarly journals The XWS open access catalogue of extreme European windstorms from 1979 to 2012

2014 ◽  
Vol 14 (9) ◽  
pp. 2487-2501 ◽  
Author(s):  
J. F. Roberts ◽  
A. J. Champion ◽  
L. C. Dawkins ◽  
K. I. Hodges ◽  
L. C. Shaffrey ◽  
...  
Keyword(s):  
Wind Speed ◽  
Grid Point ◽  
Storm Track ◽  
Wind Gust ◽  
Pressure Gradients ◽  
Valuable Resource ◽  
Model Bias ◽  
Severe Storms ◽  
High Loss ◽  
Catastrophe Models

Abstract. The XWS (eXtreme WindStorms) catalogue consists of storm tracks and model-generated maximum 3 s wind-gust footprints for 50 of the most extreme winter windstorms to hit Europe in the period 1979–2012. The catalogue is intended to be a valuable resource for both academia and industries such as (re)insurance, for example allowing users to characterise extreme European storms, and validate climate and catastrophe models. Several storm severity indices were investigated to find which could best represent a list of known high-loss (severe) storms. The best-performing index was Sft, which is a combination of storm area calculated from the storm footprint and maximum 925 hPa wind speed from the storm track. All the listed severe storms are included in the catalogue, and the remaining ones were selected using Sft. A comparison of the model footprint to station observations revealed that storms were generally well represented, although for some storms the highest gusts were underestimated. Possible reasons for this underestimation include the model failing to simulate strong enough pressure gradients and not representing convective gusts. A new recalibration method was developed to estimate the true distribution of gusts at each grid point and correct for this underestimation. The recalibration model allows for storm-to-storm variation which is essential given that different storms have different degrees of model bias. The catalogue is available at http://www.europeanwindstorms.org .

scholarly journals Drifting-snow studies over an instrumented mountainous site: II. Measurements and numerical model at small scale

2001 ◽  
Vol 32 ◽  
pp. 175-181 ◽  
Author(s):  
Jean-Luc Michaux ◽  
Florence Naaim-Bouvet ◽  
Mohamed Naaim
Keyword(s):  
Wind Speed ◽  
Numerical Model ◽  
Small Scale ◽  
Wind Gust ◽  
Strong Wind ◽  
Experimental Site ◽  
In Situ Data ◽  
Drifting Snow ◽  
Mean Wind Speed ◽  
Gust Factors

AbstractThe Érosion torrentielle, neige et avalanche (Etna) unit of CEMAGREF and the Centre d’Etudes de la Neige of Météo-France have been working on snowdrift for 10 years. A numerical model was developed at CEMAGREF to simulate snowdrift (Naaim and others, 1998). To validate this model on in situ data, a high-altitude experimental site was developed, located at 2700 m a.s.l. at the Lac Blanc Pass near the Alpe d’Huez ski resort. It is a nearly flat area and faces winds primarily from north and south. After describing the experimental site, we present the processed data of winter 1998/99. First, we analyze the data from CEMAGREF’s acoustic snowdrift sensor. It is sensitive to snow depth and snow-particle type, so additional calibration is necessary. Nevertheless, it allowed us to study non- stationary aspects of drifting snow. An analysis of gust factors for wind and drifting snow indicates that strong wind-gust factors exist in the mountains, and that drifting snow is more important during a regular and strong wind episode than during high wind-gust periods. Therefore, the numerical model presented here uses only the recorded mean wind speed. The model, which attempts to reproduce several days of storm, takes into account the modification of input parameters (e.g wind speed) as a function of time. The comparison between numerical results and measurements for a given meteorological event shows good agreement.

Vertical profiles of wind gust statistics from a regional reanalysis using multivariate extreme value theory

2020 ◽  
Author(s):  
Julian Steinheuer ◽  
Petra Friederichs
Keyword(s):  
Wind Speed ◽  
Land Surface ◽  
Prediction Models ◽  
Weather Prediction ◽  
Value Theory ◽  
Extreme Value ◽  
Horizontal Wind ◽  
Wind Gust ◽  
Post Processing ◽  
Regional Reanalysis

<div>Wind and gust statistics at the hub height of a wind turbine are important parameters for the planning in the renewable energy sector. However, reanalyses based on numerical weather prediction models typically only give estimates for wind gusts at the standard measurement height of 10 m above the land surface. We present here a statistical post-processing that gives a conditional distribution for hourly peak wind speeds as a function of height. The conditioning variables are provided by the regional reanalysis COSMO-REA6. The post-processing is developed on the basis of observations of the peak wind speed in five vertical layers between 10 m and 250 m of the Hamburg Weather Mast. The statistical post-processing is based on a censored generalized extreme value (cGEV) distribution with non-stationary parameters. To select the most meaningful variables we use a least absolute shrinkage and selection operator. The vertical variation of the cGEV parameters is approximated using Legendre polynomials, allowing gust prediction at any desired height within the training range. Furthermore, the Pickands dependence function is used to investigate dependencies between gusts at different heights. The main predictors are the 10 m gust diagnosis, the barotropic and baroclinic modes of absolute horizontal wind speed, the mean absolute horizontal wind in 700 hPa, the surface pressure tendency and the lifted index. Proper scores show improvements of up to 60 %, especially at higher vertical levels when compared to climatology. The post-processing model with a Legendre approximation is able to provide reliable predictions of gust statistics at unobserved intermediate levels. The strength of the dependence between the gusts at different levels is not stationary and strongly modulated by the vertical stability of the atmosphere.</div>

scholarly journals Overview of the IBER-STILLING project: Assessment and attribution of wind speed and wind gust variability

2020 ◽  
Author(s):  
Cesar Azorin-Molina ◽  
Manola Brunet ◽  
Enric Aguilar ◽  
Jose A. Guijarro ◽  
Amir A. Safaei Pirooz ◽  
...  
Keyword(s):  
Wind Speed ◽  
Global Climate ◽  
Global Analysis ◽  
Scientific Evidence ◽  
Wind Gust ◽  
Climate Data ◽  
Climate Trend ◽  
Project Assessment ◽  
Underlying Causes ◽  
Science Innovation

<p>In a context of global climate change, the scientific community has evidenced a significant decrease in wind speed, a phenomenon known as «stilling». This climate trend has mainly been observed over mid-latitude continental surfaces since the 1980s. On the contrary, other studies have detected an increase in wind speed over ocean surfaces; and there is little conclusive scientific evidence on trends in wind speed across the troposphere. Furthermore, a reversal in global terrestrial stilling has recently been documented in few regional and global studies since the 2010s. The causes associated with the climate variability of wind speed have not yet been resolved and there are many uncertainties behind the «stilling» and «recovery» phenomenon because neither the quantity nor the quality of wind speed observations is adequate. This contribution shows an overview of the IBER-STILLING project (RTI2018-095749-A-I00) funded by the Spanish Ministry of Science, Innovation and Universities.  This project aims to move forward on the assessment of wind speed and wind gusts variability and underlying causes globally, with emphasis on the Spanish territory and surrounding ocean (Atlantic) and sea (Mediterranean) surfaces. The IBER-STILLING project will collect and generate climate information of wind speed from different data sources; climate data will be subject to a comprehensive protocol for quality control and homogenization. The statistical analysis of these climate databases will allow characterizing trends and climatic cycles of wind speed, allowing a pioneering global analysis of wind speed over continental and ocean surfaces, and across the boundary layer and the entire troposphere. The project will also conduct wind-tunnel experiments to quantify biases introduced by anemometers devices. </p>

scholarly journals Vertical profiles of wind gust statistics from a regional reanalysis using multivariate extreme value theory

2019 ◽  
Author(s):  
Julian Steinheuer ◽  
Petra Friederichs
Keyword(s):  
Wind Speed ◽  
Land Surface ◽  
Prediction Models ◽  
Weather Prediction ◽  
Value Theory ◽  
Extreme Value ◽  
Horizontal Wind ◽  
Wind Gust ◽  
Post Processing ◽  
Regional Reanalysis

Abstract. Many applications require wind gust estimates at very different atmospheric height levels. For example, the renewable energy sector is interested in wind and gust predictions at the hub height of a wind power plant. However, numerical weather prediction models typically derive estimates for wind gusts at the standard measurement height of 10 m above the land surface only. Here, we present a statistical post-processing to derive a conditional distribution for hourly peak wind speed as a function of height. The conditioning variables are taken from the regional reanalysis COSMO-REA6. The post-processing is trained using peak wind speed observations at five vertical levels between 10 m and 250 m of the Hamburg Weather Mast. The statistical post-processing is based on a censored generalized extreme value (cGEV) distribution with non-stationary parameters. We use a least absolute shrinkage and selection operator to select the most informative variables. Vertical variations of the cGEV parameters are approximated using Legendre polynomials, such that predictions may be derived at any desired vertical height. Further, the Pickands dependence function is used to assess dependencies between gusts at different heights. The most important predictors are the 10 m gust diagnostic, the barotropic and the baroclinic mode of absolute horizontal wind speed, the mean absolute horizontal wind in 700 hPa, the surface pressure tendency, and the lifted index. Proper scores show improvements with respect to climatology of up to 60 % especially at higher vertical levels. The post-processing model with a Legendre approximation is able to provide reliable predictions of gusts statistics at non-observed intermediate levels. The strength of dependency between gusts at different levels is non-stationary and strongly modulated by the vertical stability of the atmosphere.

scholarly journals Vertical profiles of wind gust statistics from a regional reanalysis using multivariate extreme value theory

2020 ◽  
Vol 27 (2) ◽  
pp. 239-252
Author(s):  
Julian Steinheuer ◽  
Petra Friederichs
Keyword(s):  
Wind Speed ◽  
Prediction Models ◽  
Weather Prediction ◽  
Value Theory ◽  
Extreme Value ◽  
Processing Method ◽  
Horizontal Wind ◽  
Wind Gust ◽  
Post Processing ◽  
Regional Reanalysis

Abstract. Many applications require wind gust estimates at very different atmospheric height levels. For example, the renewable energy sector is interested in wind and gust predictions at the hub height of a wind power plant. However, numerical weather prediction models typically only derive estimates for wind gusts at the standard measurement height of 10 m above the land surface. Here, we present a statistical post-processing method to derive a conditional distribution for hourly peak wind speed as a function of height. The conditioning variables are taken from the COSMO-REA6 regional reanalysis. The post-processing method was trained using peak wind speed observations at five vertical levels between 10 and 250 m from the Hamburg Weather Mast. The statistical post-processing method is based on a censored generalized extreme value (cGEV) distribution with non-homogeneous parameters. We use a least absolute shrinkage and selection operator to select the most informative variables. Vertical variations of the cGEV parameters are approximated using Legendre polynomials, such that predictions may be derived at any desired vertical height. Further, the Pickands dependence function is used to assess dependencies between gusts at different heights. The most important predictors are the 10 m gust diagnostic, the barotropic and the baroclinic mode of absolute horizontal wind speed, the mean absolute horizontal wind at 700 hPa, the surface pressure tendency, and the lifted index. Proper scores show improvements of up to 60 % with respect to climatology, especially at higher vertical levels. The post-processing model with a Legendre approximation is able to provide reliable predictions of gusts' statistics at non-observed intermediate levels. The strength of dependency between gusts at different levels is non-homogeneous and strongly modulated by the vertical stability of the atmosphere.

The Application of Wind Speed Numerical Simulation in Wind Power Generation

2013 ◽  
Vol 380-384 ◽  
pp. 3370-3373 ◽  
Author(s):  
Li Yang Liu ◽  
Jun Ji Wu ◽  
Shao Liang Meng
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Wind Power ◽  
Wind Farm ◽  
Power Grid ◽  
Wind Farms ◽  
Stable Operation ◽  
Wind Gust ◽  
Gradual Change ◽  
Wake Effect

With the massive development and application of wind energy, wind power is having an increasing proportion in power grid. The changes of the wind speed in a wind farm will lead to fluctuations in the power output which would affect the stable operation of the power grid. Therefore the research of the characteristics of wind speed has become a hot topic in the field of wind energy. In the paper, the wind speed at the wind farm was simulated in a combination of wind speeds by which wind speed was decomposed of four components including basic wind, gust wind, stochastic wind and gradient wind which denote the regularity, the mutability, the gradual change and the randomness of a natural wind respectively. The model is able to reflect the characteristics of a real wind, easy for engineering simulation and can also estimate the wind energy of a wind farm through the wind speed and wake effect model. This paper has directive significance in the estimation of wind resource and the layout of wind turbines in wind farms.

scholarly journals Influence of climate factors on pediatric alopecia areata flares in Philadelphia, Pennsylvania

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Elisabeth A. George ◽  
Leslie Castelo-Soccio ◽  
Elana Putterman ◽  
Helena Kuhn ◽  
Carlos Wambier ◽  
...  
Keyword(s):  
Wind Speed ◽  
Alopecia Areata ◽  
Seasonal Pattern ◽  
Rank Correlation ◽  
Air Pressure ◽  
Wind Gust ◽  
Climate Factors ◽  
Uv Index ◽  
History Of ◽  
Flare Frequency

AbstractPatients with alopecia areata (AA) may experience episodic disease flares characterized by increasing hair loss that follow a seasonal pattern. However, no studies have examined whether specific climate factors contribute to the seasonal pattern of AA flares. Using Spearman rank correlation analyses, we assessed the association between climate variables and AA flare frequency per month in 336 children with AA in Philadelphia, Pennsylvania. Region-specific monthly values for average ambient temperature, air pressure, cloudiness, hours of sunlight, relative humidity, number of days with sun, number of days with rain, volume of precipitation, wind gust, wind speed, and UV index from January 2015 to December 2017 were obtained from World Weather Online. We found significant (P < 0.05) correlations between AA flare frequency and UV index (R = − 0.66), precipitation (R = − 0.66), number of days with rain (R = − 0.70), number of days with sun (R = 0.62), and air pressure (R = 0.80). Stratified analyses showed even stronger associations with UV index and precipitation in patients with an atopic comorbidity. New significant correlations appeared with temperature, wind speed, and UV index of the prior month. However, in patients who did not have atopic comorbidities, we generally observed weaker and non-significant correlations between climate and AA flare frequency. This study suggests that certain climate factors may mediate the seasonal pattern of AA flares and may contribute to AA pathogenesis. Atopic AA patients may be more susceptible to the influence of climate compared to those with no history of atopy.

scholarly journals Effects of Sensor Response and Gust Duration on Maximum Wind Gust Measurements and Data Homogenisation

2020 ◽  
Author(s):  
Amir Ali Safaei Pirooz ◽  
Richard G.J. Flay ◽  
Lorenzo Minola ◽  
Cesar Azorin-Molina ◽  
Deliang Chen
Keyword(s):  
Wind Speed ◽  
Wind Tunnel ◽  
Turbulence Intensity ◽  
Moving Average ◽  
Wind Gust ◽  
Gust Factor ◽  
Wind Speeds ◽  
Research Areas ◽  
Factor Ratios ◽  
Cup Anemometer

&lt;p&gt;Wind speed data recorded using different signal-processing procedures can introduce errors in the wind speed measurements. This study aims to assess the effects of a set of various moving average filter durations and turbulence intensities on the recorded maximum gust wind speeds. For this purpose, a series of wind-tunnel experiments was carried out at the University of Auckland, New Zealand, on the widely-used Vaisala WAA151 cup anemometer. The variations of gust and peak factors, and turbulence intensities measured by the cup anemometer as a function of the averaging duration and turbulence intensity are presented. The wind-tunnel results are compared with values computed from a theoretical approach, namely random process and linear system theory, and the results were also validated against values reported in the literature where possible.&lt;/p&gt;&lt;p&gt;To summarise, the major findings of this experimental study are:&lt;/p&gt;&lt;ol&gt;&lt;li&gt;The results show that increasing the effective gust duration reduces both the gust and peak factors, resulting in an underestimation of maximum gust wind speeds and an overestimation of minimum gust wind speeds.&lt;/li&gt; &lt;li&gt;The maximum difference between gust factors obtained for high (e.g. 3-s to 5-s) and low (raw, unfiltered measurements) gust durations reached values of 25% &amp;#8211; 30% for the high turbulence conditions, and up to 5% &amp;#8211; 10% for low turbulence intensities.&lt;/li&gt; &lt;li&gt;Gust factor ratios, an important parameter that allow the measurements from a specific gust duration to be converted to other gust durations of interest, are reported for various gust durations as a function of turbulence intensity.&lt;/li&gt; &lt;li&gt;The differences and gust factor ratios computed in this study can be applied directly to full-scale measurements, and can be used in several research areas, including analysing and homogenisation of historical wind speed time series, comparing gust climatologies of countries where different gust durations have been adopted, and so on. These factors clearly play an essential role in meteorological, climatological and wind engineering studies.&lt;/li&gt; &lt;/ol&gt;

Recent reversal of mean wind speed and gusts across the Iberian Peninsula and its relationship with modes of climate variability, 1961-2019

2021 ◽  
Author(s):  
Eduardo Utrabo-Carazo ◽  
Cesar Azorin-Molina ◽  
Encarna Serrano ◽  
Enric Aguilar ◽  
Manola Brunet
Keyword(s):  
Wind Speed ◽  
Iberian Peninsula ◽  
Atmospheric Circulation ◽  
Weather Forecasting ◽  
Surface Wind ◽  
Wind Gust ◽  
Near Surface ◽  
Modes Of Variability ◽  
Mean Wind Speed ◽  
Mediterranean Oscillation

&lt;p&gt;In a context of climate change, near-surface wind speed (SWS) has received less attention than other variables such as air temperature or precipitation, despite its undeniable environmental and socio-economic impacts. Studies suggest a generalized decrease of SWS in continental surfaces located in the middle latitudes from 1979 to 2010, the so-called stilling phenomenon, and an increase in it thereafter, which has been termed reversal or recovery phenomenon. Recent studies indicate that multidecade oscillations produced by the internal variability of the climate system are responsible for both phenomena. The aim of this work is to advance in the evaluation of the multidecadal variability and causes of the stilling and reversal in the observed SWS, covering the complete 2010s decade and focusing on the Iberian Peninsula region (IP). More specifically, the particular objectives of this study are: (i) to determine for the first time the occurrence of the reversal phenomenon in the IP over the last decade(s), identifying its onset year and its magnitude; (ii) to deepen into the relation between atmospheric teleconnection indices and observed trends in SWS; and (iii) to link atmospheric circulation changes to observed SWS variability. For that purpose, homogenized series of mean wind speed and gusts will be used, as well as data from the ERA5 reanalysis (European Centre for Medium-Range Weather Forecasting). Three SWS parameters will be analysed: monthly mean SWS anomaly; monthly mean daily peak wind gust (DPWG) anomaly; and number of days in which the value of DPWG exceeds the 90th percentile of the series considered. Trends of these parameters will be calculated, as well as the correlation between them and the modes of variability that govern in the region: North Atlantic Oscillation (NAO), Mediterranean Oscillation (MO) and Western Mediterranean Oscillation. Finally, trends of these modes of variability and of other parameters dependent on atmospheric circulation (e.g., geostrophic wind) will be calculated to try to clarify the drivers of the observed changes in the SWS.&lt;/p&gt;

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