Academic literature on the topic 'Wind speed measurement'

Abstract. The fusion of drone and wind lidar technology introduces the exciting possibility of performing high-quality wind measurements virtually anywhere. We present a proof-of-concept (POC) drone–lidar system and report results from several test campaigns that demonstrate its ability to measure accurate wind speeds. The POC system is based on a dual-telescope continuous-wave (CW) lidar, with drone-borne telescopes and ground-based optoelectronics. Commercially available drone and gimbal units are employed. The demonstration campaigns started with a series of comparisons of the wind speed measurements acquired by the POC system to simultaneous measurements performed by nearby mast-based sensors. On average, an agreement down to about 0.1 m s−1 between mast- and drone-based measurements of the horizontal wind speed is found. Subsequently, the extent of the flow disturbance caused by the drone downwash was investigated. These tests vindicated the somewhat conservative choice of lidar measurement ranges made for the initial wind speed comparisons. Overall, the excellent results obtained without any drone motion correction and with fairly primitive drone position control indicate the potential of drone–lidar systems in terms of accuracy and applications. The next steps in the development are outlined and several potential applications are discussed.

A system designed for making field measurements of wind action on engineering structures is described. The system is composed of sonic anemometers, differential pressure sensors, a barometer, and a thermohygrometer. The focus of this study is to determine the indications of sonic anemometers; to accomplish this goal, wind tunnel tests were performed. The tests did not involve checking the accuracy of the devices themselves, but determining their indications under field measurement conditions where certain unavoidable errors resulting from their installation can appear. The anemometer measurement uncertainty with respect to wind speed and angle was determined. The devices were rotated in a horizontal plane and inclined against and with the mean wind speed direction in a wind tunnel. Different tunnel wind speeds were tested. The results indicate stable device readings at different horizontal plane positions at different wind speeds and a low sensitivity to changes in inclination against the inflow.

Windbreaks form efficient soil protection against wind erosion particularly at the time when soil cover is not protected by the cultivated plant vegetation cover. The objective of this research was to evaluate windbreaks efficiency in terms of wind speed reduction. Wind speed along the windbreaks was measured in the cadastral areas of Dobrovíz and Středokluky (Czech Republic, Central Europe). The measurement was carried out by 4 stations placed at windward side (1 station at the distance of 3 times the height of the windbreak) and at leeward side of the windbreak (3 stations at the distance of 3, 6, and 9 times the height of the windbreak). Each station contained 2 anemometers situated 0.5 and 1 m above surface. The character of windbreak was described by terrestrial photogrammetry method as the value of optical porosity from the photo documentation of the windbreak at the time of field measurement. A significant dependence between the value of optical porosity and efficiency of windbreak emerged from the results. The correlation coefficient between optical porosity and wind speed reduction was in the range of 0.842 to 0.936 (statistical significance more than 95%). A significant effect of windbreak on airflow reduction was proven on the leeward side of windbreak in a belt corresponding to approximately six times the height of the windbreaks depending on the optical porosity and it was expressed by a polynomial equation.

A wind measurement campaign using a single scanning light detection and ranging (LiDAR) device was conducted at the Hazaki Oceanographical Research Station (HORS) on the Hazaki coast of Japan to evaluate the performance of the device for coastal wind measurements. The scanning LiDAR was deployed on the landward end of the HORS pier. We compared the wind speed and direction data recorded by the scanning LiDAR to the observations obtained from a vertical profiling LiDAR installed at the opposite end of the pier, 400 m from the scanning LiDAR. The best practice for offshore wind measurements using a single scanning LiDAR was evaluated by comparing results from a total of nine experiments using several different scanning settings. A two-parameter velocity volume processing (VVP) method was employed to retrieve the horizontal wind speed and direction from the radial wind speed. Our experiment showed that, at the current offshore site with a negligibly small vertical wind speed component, the accuracy of the scanning LiDAR wind speeds and directions was sensitive to the azimuth angle setting, but not to the elevation angle setting. In addition to the validations for the 10-minute mean wind speeds and directions, the application of LiDARs for the measurement of the turbulence intensity (TI) was also discussed by comparing the results with observations obtained from a sonic anemometer, mounted at the seaward end of the HORS pier, 400 m from the scanning LiDAR. The standard deviation obtained from the scanning LiDAR measurement showed a greater fluctuation than that obtained from the sonic anemometer measurement. However, the difference between the scanning LiDAR and sonic measurements appeared to be within an acceptable range for the wind turbine design. We discuss the variations in data availability and accuracy based on an analysis of the carrier-to-noise ratio (CNR) distribution and the goodness of fit for curve fitting via the VVP method.

Abstract For the first time, the NOAA/Aircraft Operations Center (AOC) flew stepped frequency microwave radiometers (SFMRs) on both WP-3D research aircraft for operational hurricane surface wind speed measurement in 2005. An unprecedented number of major hurricanes provided ample data to evaluate both instrument performance and surface wind speed retrieval quality up to 70 m s−1 (Saffir–Simpson category 5). To this end, a new microwave emissivity–wind speed model function based on estimates of near-surface winds in hurricanes by global positioning system (GPS) dropwindsondes is proposed. For practical purposes, utilizing this function removes a previously documented high bias in moderate SFMR-measured wind speeds (10–50 m s−1), and additionally corrects an extreme wind speed (>60 m s−1) underestimate. The AOC operational SFMRs yield retrievals that are precise to within ∼2% at 30 m s−1, which is a factor of 2 improvement over the NOAA Hurricane Research Division’s SFMR, and comparable to the precision found here for GPS dropwindsonde near-surface wind speeds. A small (1.6 m s−1), but statistically significant, overall high bias was found for independent SFMR measurements utilizing emissivity data not used for model function development. Across the range of measured wind speeds (10–70 m s−1), SFMR 10-s averaged wind speeds are within 4 m s−1 (rms) of the dropwindsonde near-surface estimate, or 5%–25% depending on speed. However, an analysis of eyewall peak wind speeds indicates an overall 2.6 m s−1 GPS low bias relative to the peak SFMR estimate on the same flight leg, suggesting a real increase in the maximum wind speed estimate due to SFMR’s high-density sampling. Through a series of statistical tests, the SFMR is shown to reduce the overall bias in the peak surface wind speed estimate by ∼50% over the current flight-level wind reduction method and is comparable at extreme wind speeds. The updated model function is demonstrated to behave differently below and above the hurricane wind speed threshold (∼32 m s−1), which may have implications for air–sea momentum and kinetic energy exchange. The change in behavior is at least qualitatively consistent with recent laboratory and field results concerning the drag coefficient in high wind speed conditions, which show a fairly clear “leveling off” of the drag coefficient with increased wind speed above ∼30 m s−1. Finally, a composite analysis of historical data indicates that the earth-relative SFMR peak wind speed is typically located in the hurricane’s right-front quadrant, which is consistent with previous observational and theoretical studies of surface wind structure.

Zonal (latitudinal) winds dominate the bulk flow of planetary atmospheres. For gas giant planets such as Jupiter, the motion of clouds can be compared with radio emissions from the magnetosphere, which is connected to the planet’s interior, to determine the wind speed. In principle, this technique can be applied to brown dwarfs and/or directly imaged exoplanets if periods can be determined for both the infrared and radio emissions. We apply this method to measure the wind speeds on the brown dwarf 2MASS J10475385+2124234. The difference between the radio period of 1.751 to 1.765 hours and infrared period of 1.741 ± 0.007 hours implies a strong wind (+650 ± 310 meters per second) proceeding eastward. This could be due to atmospheric jet streams and/or low frictional drag at the bottom of the atmosphere.