Meteorologically Stratified Gust Factors for Forecasting Peak Wind Gusts Across the United States

Wind gusts are common to everyday life and affect a wide range of interests including wind energy, structural design, forestry, and fire danger. Strong gusts are a common environmental hazard that can damage buildings, bridges, aircraft, and trains, and interrupt electric power distribution, air traffic, waterways transport, and port operations. Despite representing the component of wind most likely to be associated with serious and costly hazards, reliable forecasts of peak wind gusts have remained elusive. A project at the University of Wisconsin-Milwaukee is addressing the need for improved peak gust forecasts with the development of the meteorologically stratified gust factor (MSGF) model. The MSGF model combines gust factors (the ratio of peak wind gust to average wind speed) with wind speed and direction forecasts to predict hourly peak wind gusts. The MSGF method thus represents a simple, viable option for the operational prediction of peak wind gusts. Here we describe the results of a project designed to provide the site-specific gust factors necessary for operational use of the MSGF model at a large number of locations across the United States. Gust web diagrams depicting the wind speed- and wind direction-stratified gust factors, as well as peak gust climatologies, are presented for all sites analyzed.

Forecasting Peak Wind Gusts Using Meteorologically Stratified Gust Factors and MOS Guidance

Gust prediction is an important element of weather forecasting services, yet reliable methods remain elusive. Peak wind gusts estimated by the meteorologically stratified gust factor (MSGF) model were evaluated at 15 locations across the United States during 2010–17. This model couples gust factors, site-specific climatological measures of “gustiness,” with wind speed and direction forecast guidance. The model was assessed using two forms of model output statistics (MOS) guidance at forecast projections ranging from 1 to 72 h. At 11 of 15 sites the MSGF model showed skill (improvement over climatology) in predicting peak gusts out to projections of 72 h. This has important implications for operational wind forecasting because the method can be utilized at any location for which the meteorologically stratified gust factors have been determined. During particularly windy conditions the MSGF model exhibited skill in predicting peak gusts at forecast projections ranging from 6 to 72 h at roughly half of the sites analyzed. Site characteristics and local wind climatologies were shown to exert impacts on gust factor model performance. The MSGF method represents a viable option for the operational prediction of peak wind gusts, although model performance will be sensitive to the quality of the necessary wind speed and direction forecasts.

Wind Characteristics Investigation on The Roofs of Three Adjacent High-Rise Buildings in a Coastal Area during Typhoon Meranti

This paper presents the study of the pulsating characteristics of three adjacent high-rise buildings A, B, and C under typhoon ‘Moranti’ (2016) based on the measurement of the actual top wind speed. The studied pulsating characteristics included mean wind speed and direction, turbulence intensity, gust factor, turbulence integral scale, wind speed spectrum and correlation. The relationships between each pulsating parameter and the relationship between the pulsating parameter and gust duration have been investigated. Results show that the mean wind speed and wind direction of three buildings are close. When U ≥ 10 m/s in three different sites at the same time, the turbulence intensity variation of three buildings is consistent and decreases when mean wind speed increases. Once only two locations are acquired simultaneously and the wind angle between 35° and 45°, the mean values of the along-wind and cross-wind turbulence of building A and building C are close. The along-wind turbulence of the three buildings is greater than the predicted Chinese codes for various terrains. The turbulence intensity and gust factors obtained through the analysis of the samples with the mean wind speed U ≥ 10 m/s are reasonable. The turbulence integral scales of buildings A and C are equal to the predicted values of ASCE-7 and AIJ-2004, whereas the turbulent integral scale of building B is evidently small. The gust factors of three buildings increase when the turbulence intensity increases; these two characteristics have a linear relationship. At the same time interval, building B has the maximum along-wind turbulence intensity and gust factors during the low wind speed period and building C achieves the minimum values. Building A acquires the maximum and building C obtains the minimum values in the high wind speed period. The turbulence intensity and gust factors of building B show a certain pulsation. Results show that turbulence intensity and gust factors are mainly affected by the short-term fluctuation of wind. The longitudinal wind speed spectrum of three buildings conforms well to the von Karman model. The correlation of along-wind speed depends on the wind speed, whereas the correlation of cross-wind direction is independent of wind speeds. The measured data and statistical parameters provide useful information for the wind resistance design of high-rise buildings in typhoon-prone areas.

Wind Gust Characterization at Wind Turbine Relevant Heights in Moderately Complex Terrain

Improved understanding of wind gusts in complex terrain is critically important to wind engineering and specifically the wind energy industry. Observational data from 3D sonic anemometers deployed at 3 and 65 m at a site in moderately complex terrain within the northeastern United States are used to calculate 10 descriptors of wind gusts and to determine the parent distributions that best describe these parameters. It is shown that the parent distributions exhibit consistency across different descriptors of the gust climate. Specifically, the parameters that describe the gust intensity (gust amplitude, rise magnitude, and lapse magnitude; i.e., properties that have units of length per time) fit the two-parameter Weibull distribution, those that are unitless ratios (gust factor and peak factor) are described by log-logistic distributions, and all other properties (peak gust, rise and lapse times, gust asymmetric factor, and gust length scale) are lognormally distributed. It is also shown that gust factors scale with turbulence intensity, but gusts are distinguishable in power spectra of the longitudinal wind component (i.e., they have demonstrably different length scales than the average eddy length scale). Gust periods at the lower measurement height (3 m) are consistent with shear production, whereas at 65 m they are not. At this site, there is only a weak directional dependence of gust properties on site terrain and land cover variability along sectorial transects, but large gust length scales and gust factors are more likely to be observed in unstable atmospheric conditions.

Gust Factors: Meteorologically Stratified Climatology, Data Artifacts, and Utility in Forecasting Peak Gusts

Gust factors in Milwaukee, Wisconsin, are investigated using Automated Surface Observing System (ASOS) wind measurements from 2007 to 2014. Wind and gust observations reported in the standard hourly ASOS dataset are shown to contain substantial bias caused by sampling and reporting protocols that restrict the reporting of gusts to arbitrarily defined “gusty” periods occurring during small subsets of each hour. The hourly ASOS gust reports are found to be inadequate for describing the gust characteristics of the site and ill suited for the study of gust factors. A gust-factor climatology was established for Milwaukee using the higher-resolution, 1-min version of the ASOS dataset. The mean gust factor is 1.74. Stratified climatologies demonstrate that Milwaukee gust factors vary substantially with meteorological factors, with wind speed and wind direction exerting the strongest controls. A variety of modified gust-factor models were evaluated in which the peak wind gust is estimated by multiplying a gust factor by the observed, rather than forecast, wind speed. Errors thus obtained are entirely attributable to utility of the gust factor in forecasting peak gusts, having eliminated any error associated with the wind speed forecast. Results show that gust-factor models demonstrate skill in estimating peak gusts and improve with the use of meteorologically stratified gust factors.

Statistical characteristics of convective wind gusts in Germany

Due to the small-scale and non-stationary nature of the convective wind gusts usually associated with thunderstorms, there is a considerable lack of knowledge regarding their characteristics and statistics. In an effort to remedy this situation, we investigated in this study a set of 110 climate stations of the German Weather Service between 1992 and 2014 to analyze the temporal and spatial distribution, intensity, and occurrence probability of convective gusts. Similar to thunderstorm activity, the frequency of convective gusts decreases gradually from southern to northern Germany. No further spatial structures, such as a relation to orography or climate conditions, can be identified regarding their strength or likelihood. Rather, high wind speeds of above 30 m s−1 can be expected everywhere in Germany with almost similar occurrence probabilities. A comparison of the 20-year return values of convective gusts with those of turbulent gusts demonstrates that the latter have higher frequencies, especially in northern Germany. However, for higher return periods, this effect can be reversed at some stations. The values of the convective gust factors are mainly in a range between 1 and 4 but can even reach values up to 10. Besides the dependency from the averaging time period of the mean wind, the values of the gust factors additionally depend on the event duration and the storm type, respectively.

Statistical characteristics of convective wind gusts in Germany

Due to the small-scale and non-stationary nature of the convective wind gusts usually associated with thunderstorms, there is a considerable lack of knowledge regarding their characteristics and statistics. In an effort to remedy this situation, we investigated in this study a set of 110 climate stations of the German Weather Service between 1992 and 2014 to analyze the temporal and spatial distribution, intensity, and occurrence probability of convective gusts. Similar to thunderstorm activity, the frequency of convective gusts decreases gradually from South to North Germany. No further spatial structures, such as a relation to orography or climate conditions, can be identified regarding their strength or likelihood. Rather, high wind speeds of above 30 m s−1 can be expected everywhere in Germany with almost similar occurrence probabilities. A comparison of the 20-year return values of convective gusts with those of turbulent gusts demonstrates that the latter have higher frequencies, especially in northern Germany. However, for higher return periods, this effect can be reversed at some stations. The values of the convective gust factors are mainly in a range between 1 and 4 but can even reach values up to 10. Besides the dependency from the averaging time period of the mean wind, the values of the gust factors additionally depend on the event duration and the storm type, respectively.

Influences on Observed Near-Surface Gust Factors in Landfalling U.S. Gulf Coast Hurricanes: 2004–08

The deployment of ruggedized surface observing platforms by university research programs in the path of landfalling tropical cyclones has yielded a wealth of information regarding the near-surface wind flow characteristics. Data records collected by Texas Tech University’s Wind Engineering Mobile Instrument Tower Experiment and StickNet probes and by the Florida Coastal Monitoring Program along the Gulf Coast of the United States from 2004 to 2008 were compiled to examine influences on near-surface gust factors. Archived composite reflectivity data from coastal WSR-88D instruments were also merged with the tower records to investigate the influence of precipitation structure. Wind records were partitioned into 10-min segments, and the ratio of the peak moving-average 3-s-gust wind speed to the segment mean was used to define a gust factor. Observations were objectively stratified into terrain exposure categories to determine if factors beyond those associated with surface frictional effects can be extracted from the observations. Wind flow characteristics within exposure classes were weakly influenced by storm-relative position and precipitation structure. Eyewall observations showed little difference in mean gust factors when compared with other regions. In convective precipitation, only peak gust factors were slightly larger than those found in stratiform conditions, with little differences in the mean. Gust factors decreased slightly with decreasing radial distance in rougher terrain exposures and did not respond to radar-observed changes in precipitation structure. In two limited comparisons, near-surface gusts did not exceed the magnitude of the wind maximum aloft detected through wind profiles that were derived from WSR-88D velocity–azimuth displays.