scholarly journals Wind and drifting-snow gust factor in an Alpine context

2011 ◽  
Vol 52 (58) ◽  
pp. 223-230 ◽  
Author(s):  
Florence Naaim-Bouvet ◽  
Mohamed Naaim ◽  
Hervé Bellot ◽  
Kouichi Nishimura
Keyword(s):  
Wind Tunnels ◽  
Wind Gust ◽  
Gust Factor ◽  
Wind Gusts ◽  
Drifting Snow ◽  
Order Of Magnitude ◽  
Snow Particle ◽  
Definition Of ◽  
S Peak ◽  
Gust Factors

AbstarctWind-transported snow is a common phenomenon in cold windy areas, creating snowdrifts and contributing significantly to the loading of avalanche release areas. It is therefore necessary to take into account snowdrift formation both in terms of predicting and controlling drift patterns. Particularly in an Alpine context, drifting snow is a nonstationary phenomenon, which has not been taken into account in physical modeling carried out in wind tunnels or in numerical simulations. Only a few studies have been conducted to address the relation between wind gusts and drifting-snow gusts. Consequently, the present study was conducted at the Lac Blanc pass (2700ma.s.l.) experimental site in the French Alps using a snow particle counter and a cup anemometer in order to investigate drifting-snow gusts. First, it was shown that the behavior of the wind gust factor was coherent with previous studies. Then the definition of wind gust factor was extended to a drifting-snow gust factor. Sporadic drifting-snow events were removed from the analysis to avoid artificially high drifting-snow gust factors. Two trends were identified: (1) A high 1 s peak and a mean 10 min drifting-snow gust factor, greater than expected, were observed for events that exhibited a gamma distribution on the particle width histogram. The values of drifting-snow gust factors decreased with increasing gust duration. (2) Small drifting-snow gusts (i.e. smaller than or of the same order of magnitude as wind gusts) were also observed. However, in this case, they were systematically characterized by a snow particle size distribution that differed from the two-parameter gamma probability density function.

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

2021 ◽  
pp. 1-17
Author(s):  
Jonathan D. W. Kahl ◽  
Brandon R. Selbig ◽  
Austin R. Harris
Keyword(s):  
United States ◽  
Wind Speed ◽  
Power Distribution ◽  
The United States ◽  
Wind Gust ◽  
Average Wind Speed ◽  
Gust Factor ◽  
Wind Gusts ◽  
Wide Range ◽  
Gust Factors

AbstractWind 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.

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.

scholarly journals Reliability and Climatological Impacts of Convective Wind Estimations

2018 ◽  
Vol 57 (8) ◽  
pp. 1825-1845 ◽  
Author(s):  
Roger Edwards ◽  
John T. Allen ◽  
Gregory W. Carbin
Keyword(s):  
United States ◽  
Human Subjects ◽  
Wind Gust ◽  
Wind Tunnel Testing ◽  
Accurate Analysis ◽  
Wind Gusts ◽  
Order Of Magnitude ◽  
Quality And Reliability ◽  
The Difference ◽  
The Impact

AbstractConvective surface winds in the contiguous United States are classified as severe at 50 kt (58 mi h−1, or 26 m s−1), whether measured or estimated. In 2006, NCDC (now NCEI) Storm Data, from which analyzed data are directly derived, began explicit categorization of such reports as measured gusts (MGs) or estimated gusts (EGs). Because of the documented tendency of human observers to overestimate winds, the quality and reliability of EGs (especially in comparison with MGs) has been challenged, mostly for nonconvective winds and controlled-testing situations, but only speculatively for bulk convective data. For the 10-yr period of 2006–15, 150 423 filtered convective-wind gust magnitudes are compared and analyzed, including 15 183 MGs and 135 240 EGs, both nationally and by state. Nonmeteorological artifacts include marked geographic discontinuities and pronounced “spikes” of an order of magnitude in which EG values (in both miles per hour and knots) end in the digits 0 or 5. Sources such as NWS employees, storm chasers, and the general public overestimate EGs, whereas trained spotters are relatively accurate. Analysis of the ratio of EG to MG and their sources also reveals an apparent warning-verification-influence bias in the climatological distribution of wind gusts imparted by EG reliance in the Southeast. Results from prior wind-tunnel testing of human subjects are applied to 1) illustrate the difference between measured and perceived winds for the database and 2) show the impact on the severe-wind dataset if EGs were bias-corrected for the human overestimation factor.

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

2020 ◽  
Vol 35 (3) ◽  
pp. 1129-1143
Author(s):  
Jonathan D. W. Kahl
Keyword(s):  
Wind Speed ◽  
Weather Forecasting ◽  
Factor Model ◽  
Model Performance ◽  
The United States ◽  
Gust Factor ◽  
Wind Gusts ◽  
Skill Improvement ◽  
Model Output Statistics ◽  
Gust Factors

Abstract 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.

scholarly journals An Examination of Tropical and Extratropical Gust Factors and the Associated Wind Speed Histograms

2005 ◽  
Vol 44 (2) ◽  
pp. 270-280 ◽  
Author(s):  
B. M. Paulsen ◽  
J. L. Schroeder
Keyword(s):  
Wind Speed ◽  
Tropical Cyclones ◽  
Deep Convection ◽  
Transitional Flow ◽  
Wind Gust ◽  
Measuring Device ◽  
Gust Factor ◽  
Mean Wind Speed ◽  
Landfalling Tropical Cyclones ◽  
Gust Factors

Abstract A gust factor, defined as the ratio between a peak wind gust and mean wind speed over a period of time, can be used along with other statistics to examine the structure of the wind. Gust factors are heavily dependent on upstream terrain conditions (roughness), but are also affected by transitional flow regimes (specifically, changes in terrain and the distance from the upstream terrain change to the measuring device), anemometer height, stability of the boundary layer, and, potentially, the presence of deep convection. Previous studies have yielded conflicting results regarding differences in gust factors that might exist between winds generated by tropical cyclones and those generated by extratropical systems. Using high-resolution wind speed data collected from both landfalling tropical cyclones and extratropical systems, two databases of wind characteristics were developed. Gust factors from tropical cyclone and extratropical winds were examined, summarized, and compared. Further analysis was conducted to examine and compare the characteristics of the associated tropical and extratropical wind speed histograms. As expected, the mean gust factor was found to increase with increasing upstream surface roughness. Some differences were observed between data from the tropical environment and the extratropical environment. Mean gust factors from the tropical regime were found to be higher than mean gust factors from the extratropical environment within each roughness regime and the wind speed histograms generated from data from the two environments indicated some differences.

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

2017 ◽  
Vol 56 (12) ◽  
pp. 3151-3166 ◽  
Author(s):  
Austin R. Harris ◽  
Jonathan D. W. Kahl
Keyword(s):  
Wind Speed ◽  
Meteorological Factors ◽  
Factor Models ◽  
Wind Gust ◽  
Gust Factor ◽  
Wind Measurements ◽  
The Mean ◽  
Substantial Bias ◽  
Wind Speed Forecast ◽  
Gust Factors

AbstractGust 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.

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

2018 ◽  
Vol 57 (7) ◽  
pp. 1459-1476 ◽  
Author(s):  
W. Hu ◽  
F. Letson ◽  
R. J. Barthelmie ◽  
S. C. Pryor
Keyword(s):  
Complex Terrain ◽  
Power Spectra ◽  
Wind Component ◽  
Length Scale ◽  
Wind Gust ◽  
Atmospheric Conditions ◽  
Length Scales ◽  
Wind Gusts ◽  
Sonic Anemometers ◽  
Gust Factors

AbstractImproved 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.

scholarly journals Snow particle speeds in drifting snow

2014 ◽  
Vol 119 (16) ◽  
pp. 9901-9913 ◽  
Author(s):  
Kouichi Nishimura ◽  
Chika Yokoyama ◽  
Yoichi Ito ◽  
Masaki Nemoto ◽  
Florence Naaim-Bouvet ◽  
...  
Keyword(s):  
Drifting Snow ◽  
Snow Particle

scholarly journals Ultrafast epithelial contractions provide insights into contraction speed limits and tissue integrity

2018 ◽  
Vol 115 (44) ◽  
pp. E10333-E10341 ◽  
Author(s):  
Shahaf Armon ◽  
Matthew Storm Bull ◽  
Andres Aranda-Diaz ◽  
Manu Prakash
Keyword(s):  
Apical Cell ◽  
Physiological Role ◽  
Marine Animal ◽  
Trichoplax Adhaerens ◽  
Contraction Speed ◽  
Order Of Magnitude ◽  
Tissue Rupture ◽  
Epithelial Layers ◽  
Definition Of ◽  
External Forces

By definition of multicellularity, all animals need to keep their cells attached and intact, despite internal and external forces. Cohesion between epithelial cells provides this key feature. To better understand fundamental limits of this cohesion, we study the epithelium mechanics of an ultrathin (∼25 μm) primitive marine animal Trichoplax adhaerens, composed essentially of two flat epithelial layers. With no known extracellular matrix and no nerves or muscles, T. adhaerens has been claimed to be the “simplest known living animal,” yet is still capable of coordinated locomotion and behavior. Here we report the discovery of the fastest epithelial cellular contractions known in any metazoan, to be found in T. adhaerens dorsal epithelium (50% shrinkage of apical cell area within one second, at least an order of magnitude faster than other known examples). Live imaging reveals emergent contractile patterns that are mostly sporadic single-cell events, but also include propagating contraction waves across the tissue. We show that cell contraction speed can be explained by current models of nonmuscle actin–myosin bundles without load, while the tissue architecture and unique mechanical properties are softening the tissue, minimizing the load on a contracting cell. We propose a hypothesis, in which the physiological role of the contraction dynamics is to resist external stresses while avoiding tissue rupture (“active cohesion”), a concept that can be further applied to engineering of active materials.

scholarly journals Wind Gust Measuring at Low Altitude Using An Unmanned Aerial System

2021 ◽  
Author(s):  
Alton Yeung
Keyword(s):  
Turbulence Models ◽  
Satellite System ◽  
Data System ◽  
Measurement Unit ◽  
Wind Gust ◽  
Wind Gusts ◽  
Low Altitude ◽  
And Performance ◽  
Global Navigation Satellite ◽  
Aerial Platform

A small unmanned aerial vehicle (UAV) was developed with the specific objective to explore atmospheric wind gusts at low altitudes within the atmospheric boundary layer (ABL). These gusts have major impacts on the flight characteristics and performance of modern small unmanned aerial vehicles. Hence, this project was set to investigate the power spectral density of gusts observed at low altitudes by measuring the gusts with an aerial platform. The small UAV carried an air-data system including a fivehole probe that was adapted for this specific application. The air-data system measured the local wind gusts with an accuracy of 0.5 m/s by combining inputs from a five-hole probe, an inertial measurement unit, and Global Navigation Satellite System (GNSS) receivers. Over 20 flights were performed during the development of the aerial platform. Airborne experiments were performed to collect gust data at low altitudes between 50 m and 100 m. The result was processed into turbulence spectrum and the measurements were compared with the MIL-HDBK-1797 von K´arm´an turbulence model and the results have shown the model underpredicted the gust intensities experienced by the flight vehicle. The anisotropic properties of low-altitude turbulence were also observed when analyzing the measured gusts spectra. The wind and gust data collected are useful for verifying the existing turbulence models for low-altitude flights and benefit the future development of small UAVs in windy environment.

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