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Wind shear

About: Wind shear is a research topic. Over the lifetime, 8023 publications have been published within this topic receiving 185373 citations.


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Journal ArticleDOI
TL;DR: In this article, a method for determining horizontal wind speeds in hurricanes using ground-based radars is presented and evaluated, which makes use of the tracking reflectivity echos by correlation (TREC) method where individual features in radar reflectivity are tracked, from radar sweeps several minutes apart, by finding the maxima in the cross-correlation function between the two times.
Abstract: A method for determining horizontal wind speeds in hurricanes using ground-based radars is presented and evaluated. The method makes use of the tracking reflectivity echos by correlation (TREC) method where individual features in radar reflectivity are tracked, from radar sweeps several minutes apart, by finding the maxima in the cross-correlation function between the two times. This method has been applied successfully in determining motions within the clear boundary layer where reflectors are insects and refractive index variations, but it generally has failed when applied to determining air motions by tracking precipitation elements in strong environmental shear. It appears to work in the lower few kilometers of the hurricane where the vertical wind shear is relatively weak. Examples are presented where the TREC algorithm is applied to three landfalling hurricanes: Hurricanes Hugo and Erin in the United States and Typhoon Herb in Taiwan. The results from Hugo, where the radar data were provided by a WS...

64 citations

Journal ArticleDOI
TL;DR: In this paper, the power production of an onshore wind farm is investigated through supervisory control and data acquisition data, while the wind field is monitored through scanning light detection and ranging measurements and meteorological data acquired from a met-tower located in proximity to the turbine array.
Abstract: Power production of an onshore wind farm is investigated through supervisory control and data acquisition data, while the wind field is monitored through scanning light detection and ranging measurements and meteorological data acquired from a met-tower located in proximity to the turbine array. The power production of each turbine is analysed as functions of the operating region of the power curve, wind direction and atmospheric stability. Five different methods are used to estimate the potential wind power as a function of time, enabling an estimation of power losses connected with wake interactions. The most robust method from a statistical standpoint is that based on the evaluation of a reference wind velocity at hub height and experimental mean power curves calculated for each turbine and different atmospheric stability regimes. The synergistic analysis of these various datasets shows that power losses are significant for wind velocities higher than cut-in wind speed and lower than rated wind speed of the turbines. Furthermore, power losses are larger under stable atmospheric conditions than for convective regimes, which is a consequence of the stability-driven variability in wake evolution. Light detection and ranging measurements confirm that wind turbine wakes recover faster under convective regimes, thus alleviating detrimental effects due to wake interactions. For the wind farm under examination, power loss due to wake shadowing effects is estimated to be about 4% and 2% of the total power production when operating under stable and convective conditions, respectively. However, cases with power losses about 60-80% of the potential power are systematically observed for specific wind turbines and wind directions. Copyright © 2017 John Wiley & Sons, Ltd.

64 citations

Journal ArticleDOI
TL;DR: In this article, the performance of QuikSCAT-derived wind vectors is evaluated using in-situ data from moored buoys over the Indian Ocean, and the results show that the mean differences for wind speed and wind direction are 0.37 millimms-1 and 5.8 millimm-1, respectively.
Abstract: The performance of QuikSCAT-derived wind vectors is evaluated using in-situ data from moored buoys over the Indian Ocean. The results show that the mean differences for wind speed and wind direction are 0.37 ms-1 and 5.8°, root mean square deviations are 1.57 ms-1 and 44.1° and corresponding coefficients of correlation are 0.87 and 0.75, respectively. The matching between in-situ and satellite estimates seems to be better in the North Indian Ocean than in the Equatorial Indian Ocean. The effects of sea surface temperature and air-sea temperature difference on wind residuals were also investigated. In general, QuikSCAT is found to overestimate the winds. It is speculated that low wind speed during rain-free conditions and high wind speed, normally associated with rain, may be the reason for the less accurate estimation of the wind vector from QuikSCAT over the Indian Ocean.

64 citations

Journal ArticleDOI
TL;DR: The Crop Wind-Energy Experiment (CWEX) provides a platform to investigate the effect of wind turbines and large wind farms on surface fluxes of momentum, heat, moisture, and carbon dioxide (CO2) as mentioned in this paper.

64 citations

Journal ArticleDOI
TL;DR: In this paper, a large eddy simulation (LES) of the National Renewable Energy Laboratory (NREL) Phase VI wind turbine inside a virtual wind tunnel, with the same test section as that of NASA Ames 24, was carried out in order to analyze and better understand the wake instability and its breakdown behind the wind turbine.

64 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023155
2022347
2021165
2020157
2019187
2018165