A new method for estimating maximum wind gust speed with a given return period and a high areal resolution

2016 ◽  
Vol 158 ◽  
pp. 51-60 ◽  
Author(s):  
Lukáš Pop ◽  
Zbyněk Sokol ◽  
David Hanslian
Keyword(s):  
Return Period ◽  
New Method ◽  
Wind Gust ◽  
Maximum Wind ◽  
Gust Speed

Probabilistic Wind Gust Forecasting Using Nonhomogeneous Gaussian Regression

2012 ◽  
Vol 140 (3) ◽  
pp. 889-897 ◽  
Author(s):  
Thordis L. Thorarinsdottir ◽  
Matthew S. Johnson
Keyword(s):  
Wind Speed ◽  
Linear Function ◽  
Location Parameter ◽  
Maximum Wind Speed ◽  
Wind Gust ◽  
Probabilistic Forecasting ◽  
Maximum Wind ◽  
Gaussian Regression ◽  
Gust Speed ◽  
Wind Speed Forecast

Abstract A joint probabilistic forecasting framework is proposed for maximum wind speed, the probability of gust, and, conditional on gust being observed, the maximum gust speed in a setting where only the maximum wind speed forecast is available. The framework employs the nonhomogeneous Gaussian regression (NGR) statistical postprocessing method with appropriately truncated Gaussian predictive distributions. For wind speed, the distribution is truncated at zero, the location parameter is a linear function of the wind speed ensemble forecast, and the scale parameter is a linear function of the ensemble variance. The gust forecasts are derived from the wind speed forecast using a gust factor, and the predictive distribution for gust speed is truncated according to its definition. The framework is applied to 48-h-ahead forecasts of wind speed over the North American Pacific Northwest obtained from the University of Washington mesoscale ensemble. The resulting density forecasts for wind speed and gust speed are calibrated and sharp, and offer substantial improvement in predictive performance over the raw ensemble or climatological reference forecasts.

scholarly journals Daily wind gust speed probabilities over Switzerland according to three types of synoptic circulation

2002 ◽  
Vol 22 (4) ◽  
pp. 485-499 ◽  
Author(s):  
Patricia Jungo ◽  
St�phane Goyette ◽  
Martin Beniston
Keyword(s):  
Wind Gust ◽  
Synoptic Circulation ◽  
Gust Speed

scholarly journals Joint Modeling of Severe Dust Storm Events in Arid and Hyper Arid Regions Based on Copula Theory: A Case Study in the Yazd Province, Iran

Climate ◽  
2020 ◽  
Vol 8 (5) ◽  
pp. 64 ◽  
Author(s):  
Tayyebeh Mesbahzadeh ◽  
Maryam Mirakbari ◽  
Mohsen Mohseni Saravi ◽  
Farshad Soleimani Sardoo ◽  
Nir Y. Krakauer
Keyword(s):  
Wind Speed ◽  
Natural Disasters ◽  
Return Period ◽  
Vertical Velocity ◽  
Geopotential Height ◽  
Dust Storms ◽  
Maximum Wind Speed ◽  
Near Surface ◽  
Copula Theory ◽  
Maximum Wind

Natural disasters such as dust storms are random phenomena created by complicated mechanisms involving many parameters. In this study, we used copula theory for bivariate modeling of dust storms. Copula theory is a suitable method for multivariate modeling of natural disasters. We identified 40 severe dust storms, as defined by the World Meteorological Organization, during 1982–2017 in Yazd province, central Iran. We used parameters at two spatial vertical levels (near-surface and upper atmosphere) that included surface maximum wind speed, and geopotential height and vertical velocity at 500, 850, and 1000 hPa. We compared two bivariate models based on the pairs of maximum wind speed–geopotential height and maximum wind speed–vertical velocity. We determined the bivariate return period using Student t and Gaussian copulas, which were considered as the most suitable functions for these variables. The results obtained for maximum wind speed–geopotential height indicated that the maximum return period was consistent with the observed frequency of severe dust storms. The bivariate modeling of dust storms based on maximum wind speed and geopotential height better described the conditions of severe dust storms than modeling based on maximum wind speed and vertical velocity. The finding of this study can be useful to improve risk management and mitigate the impacts of severe dust storms.

A probabilistic approach for short-term prediction of wind gust speed using ensemble learning

2020 ◽  
Vol 202 ◽  
pp. 104198 ◽  
Author(s):  
Hao Wang ◽  
Yi-Ming Zhang ◽  
Jian-Xiao Mao ◽  
Hua-Ping Wan
Keyword(s):  
Ensemble Learning ◽  
Probabilistic Approach ◽  
Wind Gust ◽  
Short Term ◽  
Term Prediction ◽  
Short Term Prediction ◽  
Gust Speed

scholarly journals Effects of sensor response and moving average filter duration on maximum wind gust measurements

2020 ◽  
Vol 206 ◽  
pp. 104354 ◽  
Author(s):  
Amir Ali Safaei Pirooz ◽  
Richard G.J. Flay ◽  
Lorenzo Minola ◽  
Cesar Azorin-Molina ◽  
Deliang Chen
Keyword(s):  
Moving Average ◽  
Sensor Response ◽  
Wind Gust ◽  
Moving Average Filter ◽  
Maximum Wind ◽  
Average Filter

scholarly journals The 21st Century Decline in Damaging European Windstorms

2016 ◽  
Author(s):  
Laura C. Dawkins ◽  
David B. Stephenson ◽  
Julia F. Lockwood ◽  
Paul E. Maisey
Keyword(s):  
21St Century ◽  
Wind Gust ◽  
Correlation Pattern ◽  
North West ◽  
Modes Of Variability ◽  
The North ◽  
Strong Positive Relationship ◽  
Resolution Model ◽  
The North Atlantic Oscillation ◽  
Gust Speed

Abstract. A decline in damaging European windstorms has led to a reduction in insured losses in the 21st century. This decline is explored by identifying a damaging windstorm characteristic and investigating how and why this characteristic has changed in recent years. This novel exploration is based on 6103 high resolution model generated historical footprints (1979–2014) representing the whole European domain. The footprint of a windstorm is defined as the maximum wind gust speed to occur at a set of spatial locations over the duration of the storm. The area of the footprint exceeding 20 ms−1 over land, A20, is shown to be a good predictor of windstorm damage. This damaging characteristic has decreased in the 21st century, due to a statistically significant decrease in the relative frequency of windstorms exceeding 20 ms−1 in north-west Europe. This is explained by a decrease in the quantiles of the footprint wind gust speed distribution above approximately 18 ms−1 at locations in this region. Much of the change in A20 is explained by the North Atlantic Oscillation (NAO). The correlation between winter total A20 and winter averaged mean sea-level pressure resembles the NAO pattern, shifted eastwards over Europe, and a strong positive relationship (correlation of 0.715) exists between winter total A20 and winter averaged NAO. The shifted correlation pattern, however, suggests that other modes of variability may also play a role in the variation in windstorm losses.

scholarly journals Extreme Wind and Waves in U.S. East Coast Offshore Wind Energy Lease Areas

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 1053
Author(s):  
Rebecca J. Barthelmie ◽  
Kaitlyn E. Dantuono ◽  
Emma J. Renner ◽  
Frederick L. Letson ◽  
Sara C. Pryor
Keyword(s):  
Return Period ◽  
East Coast ◽  
Offshore Wind ◽  
Time Interval ◽  
Annual Maximum ◽  
Outer Continental Shelf ◽  
Reanalysis Dataset ◽  
Maximum Wind ◽  
Wind Speeds ◽  
Extreme Wind

The Outer Continental Shelf along the U.S. east coast exhibits abundant wind resources and is now a geographic focus for offshore wind deployments. This analysis derives and presents expected extreme wind and wave conditions for the sixteen lease areas that are currently being developed. Using the homogeneous ERA5 reanalysis dataset it is shown that the fifty-year return period wind speed (U50) at 100 m a.s.l. in the lease areas ranges from 29.2 to 39.7 ms−1. After applying corrections to account for spectral smoothing and averaging period, the associated pseudo-point U50 estimates are 34 to 46 ms−1. The derived uncertainty in U50 estimates due to different distributional fitting is smaller than the uncertainty associated with under-sampling of the interannual variability in annual maximum wind speeds. It is shown that, in the northern lease areas, annual maximum wind speeds are generally associated with intense extratropical cyclones rather than cyclones of tropical origin. Extreme wave statistics are also presented and indicate that the 50-year return period maximum wave height may substantially exceed 15 m. From this analysis, there is evidence that annual maximum wind speeds and waves frequently derive from the same cyclone source and often occur within a 6 h time interval.

scholarly journals Hydrological and Meteorological Controls on Large Wildfire Ignition and Burned Area in Northern California during 2017–2020

Fire ◽  
2021 ◽  
Vol 4 (4) ◽  
pp. 90
Author(s):  
Yusuke Hiraga ◽  
M. Levent Kavvas
Keyword(s):  
Vapor Pressure Deficit ◽  
Horizontal Wind ◽  
Burned Area ◽  
Wind Gust ◽  
Northern California ◽  
Horizontal Wind Speed ◽  
Spatial And Temporal Scales ◽  
Moisture Deficit ◽  
In Fire ◽  
Gust Speed

This study examined the hydrological/meteorological controls on large wildfires > 10,000 acres (40.5 km2) during 2017–2020 in Northern California at spatial and temporal scales of the target wildfires’ occurrence or growth. This study used the following simple indices for analysis: Moisture Deficit Index (MDI) computed by dividing vapor pressure deficit by soil moisture, MDIWIND computed by multiplying MDI by horizontal wind speed, and MDIGUST computed by multiplying MDI by wind gust speed. The ignition location MDIWIND and MDIGUST showed larger values on the ignition date in fire-years compared to non-fire-years for most of the target wildfires (95.8% and 91.7%, respectively). The peak timing of MDIGUST, which is to evaluate the integrated effect of dry atmosphere/soil and windy condition, coincided with the ignition date for August Complex Fire 2020, Ranch Fire 2018, Claremont-Bear Fire 2020, and Camp Fire 2018. We also found that August Complex Fire 2020, Claremont-Bear Fire 2020, and Camp Fire 2018 occurred in the areas where MDIGUST became spatially and temporally high. Further, strong relationships were found between burned area sizes of the target wildfires and MDI (R = 0.62, p = 0.002), MDIWIND (R = 0.72, p < 0.001), and MDIGUST (R = 0.68, p < 0.001). Overall, the findings in this study implied the strong effect of dry atmosphere/soil and windy conditions on recent large wildfire activities in Northern California. The findings could contribute to a more temporally and spatially detailed forecast of wildfire risks or a better understanding of wildfires’ occurrence and growth mechanisms.

scholarly journals Wintersturmschäden im Schweizer Wald von 1865 bis 2014

2015 ◽  
Vol 166 (3) ◽  
pp. 184-190 ◽  
Author(s):  
Tilo Usbeck
Keyword(s):  
Present Article ◽  
Forest Area ◽  
Wind Gust ◽  
Turn Of The Millennium ◽  
Storm Events ◽  
Winter Storm ◽  
Winter Storms ◽  
Growing Stock ◽  
The Past ◽  
Gust Speed

Forest damages from winter storms in Switzerland from 1865 to 2014 Winter storms cause the most catastrophic damages in Swiss forests. The present article analyses how these storm damages correspond with wind gust speed, growing stock and forest area, in regard to the whole country and individual cantons, and from 1865 to 2014. During the study period, 26 storm events each totalling a volume of at least 70,000 m3 damaged wood were registered. Winter storm damages were highly variable regarding absolute numbers (volume) and portions per area (m3 per ha) and per growing stock (%). In the past 150 years, the cantons Nidwalden, Freiburg, Aargau, Zurich and Zug were hit most often by storm events, with damages ranging per event in average from 2.2 m3 per ha (Zurich) to 3.1 m3 per ha (Nidwalden). At the turn of the millennium, not only the greatest damages occurred but also growing stock peaked as well did the wind gust speeds.

scholarly journals The 21st century decline in damaging European windstorms

2016 ◽  
Vol 16 (8) ◽  
pp. 1999-2007 ◽  
Author(s):  
Laura C. Dawkins ◽  
David B. Stephenson ◽  
Julia F. Lockwood ◽  
Paul E. Maisey
Keyword(s):  
21St Century ◽  
Western Europe ◽  
Wind Gust ◽  
Correlation Pattern ◽  
Modes Of Variability ◽  
The North ◽  
Strong Positive Relationship ◽  
Resolution Model ◽  
The North Atlantic Oscillation ◽  
Gust Speed

Abstract. A decline in damaging European windstorms has led to a reduction in insured losses in the 21st century. This decline is explored by identifying a damaging windstorm characteristic and investigating how and why this characteristic has changed in recent years. This novel exploration is based on 6103 high-resolution model-generated historical footprints (1979–2014), representing the whole European domain. The footprint of a windstorm is defined as the maximum wind gust speed to occur at a set of spatial locations over the duration of the storm. The area of the footprint exceeding 20 ms−1 over land, A20, is shown to be a good predictor of windstorm damage. This damaging characteristic has decreased in the 21st century, due to a statistically significant decrease in the relative frequency of windstorms exceeding 20 ms−1 in north-western Europe, although an increase is observed in southern Europe. This is explained by a decrease in the quantiles of the footprint wind gust speed distribution above approximately 18 ms−1 at locations in this region. In addition, an increased variability in the number of windstorm events is observed in the 21st century. Much of the change in A20 is explained by the North Atlantic Oscillation (NAO). The correlation between winter total A20 and winter-averaged mean sea-level pressure resembles the NAO pattern, shifted eastwards over Europe, and a strong positive relationship (correlation of 0.715) exists between winter total A20 and winter-averaged NAO. The shifted correlation pattern, however, suggests that other modes of variability may also play a role in the variation in windstorm losses.

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