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At least 577 records · Page 32

Impact of Clouds and Blowing Snow on Surface and Atmospheric Boundary Layer Properties over Dome C, Antarctica

Clouds and blowing snow (BLSN) occur frequently over Antarctica, where it is critical to understand their feedbacks to surface and atmospheric boundary layer processes. Dome C, an elevated East Antarctic station, dominated by lengthy periods of surface longwave (LW) radiative cooling, is selected to reveal cloud and BLSN impacts within a largely stable environment. The sky condition is classified as clear, cloudy, or BLSN, using 3 years of Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations satellite data. Co-located and contemporaneous in situ observations are used to investigate the relationship of sky condition with surface and atmospheric boundary layer thermal structure, focusing on seasonal variability. Results show that increased downwelling LW radiation from clouds abate surface radiative cooling losses, contributing to warming during all seasons. An increase of 3°C in the mean surface air temperature is observed during spring, whereas, a more dramatic rise (around 10°C), due to accompanying large-scale subsidence, is observed during fall and winter in association with clouds. For all seasons, the wind speed and wind speed shear are strongest during BLSN events, and the surface-based inversion is weakened by cooling which peaks in a shallow above-surface turbulent layer. The stronger background stability during fall and winter seasons, restricts turbulence and BLSN depths generally to the lowest tens of meters. The Earth's cryosphere is among the most rapidly evolving yet least well-observed regions, and knowledge of clouds and BLSN interactions with the typical stable atmospheric boundary layer can help further understand energy and moisture exchanges.

CALIPSO↗

Wake characteristics of an eight-leg tower for a MOD-0 type wind turbine

Low speed wind tunnel tests were conducted to determine the flow characteristics of the wake downwind of a 1/25th scale, all tubular eight leg tower concept suitable for application to the DOE-NASA MOD-0 wind power turbine. Measurements were made of wind speed profiles, and from these were determined the wake local minimum velocity, average velocity, and width for several wind approach angles. These data are presented herein along with tower shadow photographs and comparisons with data from an earlier lattice type, four leg tower model constructed of tubular members. Values of average wake velocity defect ratio and average ratio of wake width to blade radius for the eight leg model were estimated to be around 0.17 and 0.30, respectively, at the plane of the rotor blade. These characteristics suggest that the tower wake of the eight leg concept is slightly less than that of the four leg design.

Savino, J. M.↗

Small Propeller and Rotor Testing Capabilities of the NASA Langley Low Speed Aeroacoustic Wind Tunnel

The Low Speed Aeroacoustic Wind Tunnel (LSAWT) at NASA Langley Research Center has recently undergone a configuration change. This change incorporates an inlet nozzle extension meant to serve the dual purposes of achieving lower free-stream velocities as well as a larger core flow region. The LSAWT, part of the NASA Langley Jet Noise Laboratory, had historically been utilized to simulate realistic forward flight conditions of commercial and military aircraft engines in an anechoic environment. The facility was modified starting in 2016 in order to expand its capabilities for the aerodynamic and acoustic testing of small propeller and unmanned aircraft system (UAS) rotor configurations. This paper describes the modifications made to the facility, its current aerodynamic and acoustic capabilities, the propeller and UAS rotor-vehicle configurations to be tested, and some preliminary predictions and experimental data for isolated propeller and UAS rotor con figurations, respectively. Isolated propeller simulations have been performed spanning a range of advance ratios to identify the theoretical propeller operational limits of the LSAWT. Performance and acoustic measurements of an isolated UAS rotor in hover conditions are found to compare favorably with previously measured data in an anechoic chamber and blade element-based acoustic predictions.

Zawodny, Nikolas S.↗

WRF Modelling of Deep Convection and Hail for Wind Power Applications

Deep convection and the related occurrence of hail, intense precipitation and wind gusts represent a hazard to a range of energy infrastructure including wind turbine blades. Wind turbine blade leading edge erosion (LEE) is caused by the impact of falling hydrometeors onto rotating wind turbine blades. It is a major source of wind turbine maintenance costs and energy losses from wind farms. In the United States Southern Great Plains (SGP), where there is widespread wind energy development, deep convection and hail events are common, increasing the potential for precipitation-driven LEE. A 25-day Weather Research and Forecasting (WRF) model simulation conducted at convection-permitting resolution and using a detailed microphysics scheme is carried out for the SGP to evaluate the effectiveness in modelling the wind and precipitation conditions relevant to LEE potential. WRF output for these properties is evaluated using radar observations of precipitation (including hail) and reflectivity, in situ wind speed measurements and wind power generation. This research demonstrates some skill for the primary drivers of LEE. Wind speeds, rainfall rates and precipitation totals show good agreement with observations. Here, the occurrence of precipitation during power producing wind speeds is also shown to exhibit fidelity. Hail events frequently occur during periods when wind turbines are rotating and are especially important to LEE in the SGP. The presence of hail is modelled with a mean proportion correct of 0.77 and an odds ratio 4.55. Further research is needed to demonstrate sufficient model performance to be actionable for the wind energy industry and there is evidence for positive model bias in cloud reflectivity.

17 WIND ENERGY↗

A Comparison of Pre‐Construction and Operational Wake Loss Estimates for Land‐Based Wind Plants

The overall bias between pre‐construction energy yield assessment (EYA) estimates of wind plant energy production and the achieved operational production is improving in the wind industry, but uncertainty remains high for individual wind plants. Wake effects within wind plants are one of the largest sources of energy loss considered in the EYA process, and previous work shows wake loss estimates to be a major source of disagreement among wind energy consultants who perform EYAs. To better understand the accuracy of wake loss predictions, we compare overall operational wake loss estimates based on supervisory control and data acquisition data to pre‐construction estimates provided by six wind energy consultants for five land‐based wind plants in North America. By augmenting existing approaches for quantifying operational wake losses, we estimate wake losses during the period of record for which operational data are available as well as the expected long‐term wake losses, based on historical reanalysis weather data, to which the EYA estimates are compared. To account for power variations at different turbine locations caused by terrain‐induced wind resource heterogeneity, we correct the operational wake loss estimates using predicted freestream wind speed variations from the Wind Systems Engineering Reynolds‐averaged Navier–Stokes (RANS) tool. We identify long‐term corrected operational wake losses between 1.9% and 6.4% for the five plants, with a mean loss of 4%. For the project deemed most acceptable for operational wake loss assessment, which is located in the simplest terrain and isolated from neighboring plants, the mean EYA wake loss estimate is within 0.7 percentage points of the operational value of 6.4%. For most of the remaining plants, results suggest that wake losses are generally overpredicted by 2.6–6.3 percentage points. However, operational wake losses may be underestimated for many of these projects because of spatial wind resource variations not captured by the RANS model, external wake effects that are unaccounted for in the estimation process, and wind plant blockage effects. To better understand factors that contribute to the observed wake losses, we investigate operational wake losses as a function of wind direction and wind speed. As expected, wake losses are generally concentrated near wind directions that are aligned with rows of closely spaced turbines and at below‐rated wind speeds; however, for some projects, the energy produced by the wind plant exceeds the estimated potential energy of the plant without wake interactions for certain wind directions and wind speeds, suggesting inaccurate assumptions in the wake loss estimation method for those plants. Lastly, we compare predicted and operational wake losses for individual wind turbines, finding that even when overall wake losses are predicted accurately, large uncertainty exists at the turbine level.

17 WIND ENERGY↗

Active and passive microwave measurements in Hurricane Allen

The NASA Langley Research Center analysis of the airborne microwave remote sensing measurements of Hurricane Allen obtained on August 5 and 8, 1980 is summarized. The instruments were the C-band stepped frequency microwave radiometer and the Ku-band airborne microwave scatterometer. They were carried aboard a NOAA aircraft making storm penetrations at an altitude of 3000 m and are sensitive to rain rate, surface wind speed, and surface wind vector. The wind speed is calculated from the increase in antenna brightness temperature above the estimated calm sea value. The rain rate is obtained from the difference between antenna temperature increases measured at two frequencies, and wind vector is determined from the sea surface normalized radar cross section measured at several azimuths. Comparison wind data were provided from the inertial navigation systems aboard both the C-130 aircraft at 3000 m and a second NOAA aircraft (a P-3) operating between 500 and 1500 m. Comparison rain rate data were obtained with a rain radar aboard the P-3. Evaluation of the surface winds obtained with the two microwave instruments was limited to comparisons with each other and with the flight level winds. Two important conclusions are drawn from these comparisons: (1) the radiometer is accurate when predicting flight level wind speeds and rain; and (2) the scatterometer produces well behaved and consistent wind vectors for the rain free periods.

Delnore, V. E.↗

Wind Shear and Wind Veer Effects on Wind Turbines

This chapter highlights key contributions to the scientific literature on the sources of wind shear and wind veer in the atmospheric boundary layer, observations of shear and veer, and the effects of shear and veer on wind turbine power production, wind turbine wake evolution, and wind turbine loads. As wind turbines have grown larger, they encounter deeper and more complicated regions of the atmosphere. Over this height, profiles of wind speed shear and wind direction veer play a quantifiable role. Changes in the wind speed and wind direction across the vertical extent of a wind turbine rotor disk modify the inflow vector on the blades of the turbine, thereby affecting the magnitude and orientation of the lift and drag forces of the blade's airfoil. These changes can affect the power production and loads on large modern turbines, as well as the evolution of the wake that could affect a downwind turbine.

atmospheric stability↗

Latitudinal variation of speed and mass flux in the acceleration region of the solar wind inferred from spectral broadening measurements

Spectral broadening measurements conducted at S-band (13-cm wavelength) during solar minimum conditions in the heliocentric distance range of 3-8 R(sub O) by Mariner 4, Pioneer 10, Mariner 10, Helios 1, Helios 2, and Viking have been combined to reveal a factor of 2.6 reduction in bandwidth from equator to pole. Since spectral broadening bandwidth depends on electron density fluctuation and solar wind speed, and latitudinal variation of the former is available from coherence bandwidth measurements, the remote sensing spectral broadening measurements provide the first determination of the latitudinal variation of solar wind speed in the acceleration region. When combined with electron density measurements deduced from white-light coronagraphs, this result also leads to the first determination of the latitudinal variation of mass flux in the acceleration region. From equator to pole, solar wind speed increases by a factor of 2.2, while mass flux decreases by a factor of 2.3. These results are consistent with measurements of solar wind speed by multi-station intensity scintillation measurements, as well as measurements of mass flux inferred from Lyman alpha observations, both of which pertain to the solar wind beyond 0.5 AU. The spectral broadening observations, therefore, strengthen earlier conclusions about the latitudinal variation of solar wind speed and mass flux, and reinforce current solar coronal models and their implications for solar wind acceleration and solar wind modeling.

Woo, Richard↗

Wind tunnel wall interference effects on a supercritical airfoil at transonic speeds

Wind tunnel tests of a 10% supercritical airfoil have been conducted in the Lockheed Compressible Flow Facility at transonic speeds to determine the effects of varying wind tunnel wall porosity on airfoil performance. Wall configurations ranging in porosity from 1.3% to 10% were investigated at Reynolds numbers of 7 to 30 million. Experimental data presented to show the effect of varying wall porosity include airfoil surface pressures, airfoil forces, and wind tunnel wall pressures. Utilizing the experimental results, an assessment of the applicability of current subcritical theoretical methods to predict wall interference corrections in subsonic and transonic flows is made.

Blackwell, J. A., Jr.↗

Gaussian and Lognormal Models of Hurricane Gust Factors

A document describes a tool that predicts the likelihood of land-falling tropical storms and hurricanes exceeding specified peak speeds, given the mean wind speed at various heights of up to 500 feet (150 meters) above ground level. Empirical models to calculate mean and standard deviation of the gust factor as a function of height and mean wind speed were developed in Excel based on data from previous hurricanes. Separate models were developed for Gaussian and offset lognormal distributions for the gust factor. Rather than forecasting a single, specific peak wind speed, this tool provides a probability of exceeding a specified value. This probability is provided as a function of height, allowing it to be applied at a height appropriate for tall structures. The user inputs the mean wind speed, height, and operational threshold. The tool produces the probability from each model that the given threshold will be exceeded. This application does have its limits. They were tested only in tropical storm conditions associated with the periphery of hurricanes. Winds of similar speed produced by non-tropical system may have different turbulence dynamics and stability, which may change those winds statistical characteristics. These models were developed along the Central Florida seacoast, and their results may not accurately extrapolate to inland areas, or even to coastal sites that are different from those used to build the models. Although this tool cannot be generalized for use in different environments, its methodology could be applied to those locations to develop a similar tool tuned to local conditions.

Merceret, Frank↗

Long-term uncertainty quantification in WRF-modeled offshore wind resource off the US Atlantic coast

Uncertainty quantification of long-term modeled wind speed is essential to ensure stakeholders can best leverage wind resource numerical data sets. Offshore, this need is even stronger given the limited availability of observations of wind speed at heights relevant for wind energy purposes and the resulting heavier relative weight of numerical data sets for wind energy planning and operational projects. In this analysis, we consider the National Renewable Energy Laboratory's 21-year updated numerical offshore data set for the US East Coast and provide a methodological framework to leverage both floating lidar and near-surface buoy observations in the region to quantify uncertainty in the modeled hub-height wind resource. We first show how using a numerical ensemble to quantify the uncertainty in modeled wind speed is insufficient to fully capture the model deviation from real-world observations. Next, we train and validate a random forest to vertically extrapolate near-surface wind speed to hub height using the available short-term lidar data sets in the region. We then apply this model to vertically extrapolate the long-term near-surface buoy wind speed observations to hub height so that they can be directly compared to the long-term numerical data set. We find that the mean 21-year uncertainty in 140 m hourly average wind speed is slightly lower than 3 m s -1 (roughly 30m% of the mean observed wind speed) across the considered region. Atmospheric stability is strictly connected to the modeled wind speed uncertainty, with stable conditions associated with an uncertainty which is, on average, about 20 % larger than the overall mean uncertainty.

17 WIND ENERGY↗

Applications of SMAP Data to Retrieval of Ocean Surface Wind and Salinity

We have examined the L-band radiometer and radar data from NASA’s Soil Moisture Active Passive (SMAP) mission for ocean research and applications. We find that the SMAP data are in excellent agreement with the geophysical model function (GMF) derived from the Aquarius data up to a wind speed of 20 ms-1. For severe wind conditions, the higher resolution data from SMAP allowed us to assess the sensitivity of L-band radiometer signals to hurricane force winds. We applied the L-band GMF to the retrieval of ocean surface wind and SSS from the SMAP data. Comparison with the European Center for Medium-Range Weather Forecasting, WindSat and RapidSCAT wind speeds suggests that SMAP’s radiometer wind speed reaches an excellent accuracy of about 1.1-1.7 ms-1 below a wind speed of 20 ms-1. We have also found that the maximum wind speed derived from the SMAP radiometer data can reach 140 knots for severe storms and are generally in good agreement with the hurricane track analysis and operational aircraft Stepped Frequency Microwave Radiometer wind speeds. The spatial patterns of the SMAP SSS agree well with climatological distributions, but exhibit several unique spatial and temporal features.

ocean surface wind↗

High Efficiency 2-Bladed Utility Wind Turbine Enhanced by CoFlow Jet Active Flow Control

The aerodynamic performance and power output of a high efficiency Co-Flow Jet (CFJ) 2-bladed Wind Turbine is studied in this paper. CFJ is a Zero-Net-Mass-Flux (ZNMF) active flow control method that dramatically increases airfoil lift coefficient and suppresses flow separation at a low energy expenditure. The 3D Reynolds Averaged Navier-Stokes (RANS) equations with one-equation Spalart-Allmaras (SA) turbulence model are solved to simulate the 3D flows of the wind turbines. The CFJ-Wind Turbine in this paper is modified from the NREL 3-bladed 3.4 MW reference wind turbine with the same RPM, blade length, distribution of chord, twist, and bending. The CFJ 2-bladed wind turbine utilizes the CFJ-NACA 64 series airfoils at most of the blade span from 31.88\% to the tip. The CFJ injection and suction slots are implemented along the full blade span to enhance the effectiveness and power output. The study shows that the 2-bladed CFJ turbine significantly increases power output compared with the 3-bladed baseline turbine at all wind speeds by 15.8\% at the wind speed of 9.8 m/s and by 25.9\% at 4 m/s respectively. The efficiency enhancement is substantially more at the low wind speed than at high wind speed. This would be very beneficial to increase the annual power output or capacity factor as wind turbines work at the speeds lower than the rated speed for most of the time. The results show that the flow field around the blade surface presents a significant enhanced suction peak near the blade leading edge, which results in a very high tangential force and thus increased wind turbine net power coefficient. Consistent with the previous study for the small NREL Phase VI research wind turbine, this paper demonstrates that CFJ 2-bladed wind turbine is an effective technology to extract more power from the wind at all speeds. This study is just an initial effort to demonstrate the advantage of the CFJ blade with no design optimization. It is believed that there is more potential to further enhance the efficiency improvement.

active flow control↗

Characterization of terrestrial service environments - The simultaneous occurrence of combined conditions of solar insolation and climatic variables

Computational methods for occurrences of combined environmental and pollution variables are compared. General statistical data and diurnal statistics on 24 environmental variables are treated. Combinations of variables dealt with include: air temperature, relative humidity, wind speed, total insolation; air temperature and weather event (rain, fog); air pollutant and weather event; wind speed, wind direction, and weather event; air temperature, total insolation, and weather event; air temperature, relative humidity, wind speed, computed direct insolation levels; air temperature, relative humidity, air pollution.

Thomas, R. E.↗

Comparison of moored wind measurements from a spar and toroidal buoy in the eastern equatorial Pacific during February-March 1981

Wind measurements at 3.8 m from a surface-following toroid and at 4.0 m from a vertically stable spar were compared to estimate the influence of mooring motion. Buoys were separated by 9 km. Data were obtained at 15-min intervals for 41 days in the equatorial Pacific, where the maximum 15-min averaged wind speed was 9.0 m/s and wind speeds averaged 4.5 m/s. Toroid wind speeds were 3.5 percent greater than the spar data, and the correlation coefficient between 15-min toroid and spar data was 0.92. The frequency of the 50-percent noise level was 0.125 cph, and the correlation coefficient between 8-hour averaged toroid and spar data was 0.98. Toroid 8-hour averaged wind speeds referenced to 10-m height were 2 percent larger thancorresponding spar data.

Halpern, David↗

Occurrence of Low-Level Jets over the Eastern U.S. Coastal Zone at Heights Relevant to Wind Energy

Two years of high-resolution simulations conducted with the Weather Research and Forecasting (WRF) model are used to characterize the frequency, intensity and height of low-level jets (LLJ) over the U.S. Atlantic coastal zone. Meteorological conditions and the occurrence and characteristics of LLJs are described for (i) the centroids of thirteen of the sixteen active offshore wind energy lease areas off the U.S. east coast and (ii) along two transects extending east from the U.S. coastline across the northern lease areas (LA). Flow close to the nominal hub-height of wind turbines is predominantly northwesterly and southwesterly and exhibits pronounced seasonality, with highest wind speeds in November, and lowest wind speeds in June. LLJs diagnosed using vertical profiles of modeled wind speeds from approximately 20 to 530 m above sea level exhibit highest frequency in LA south of Massachusetts, where LLJs are identified in up to 12% of hours in June. LLJs are considerably less frequent further south along the U.S. east coast and outside of the summer season. LLJs frequently occur at heights that intersect the wind turbine rotor plane, and at wind speeds within typical wind turbine operating ranges. LLJs are most frequent, intense and have lowest core heights under strong horizontal temperature gradients and lower planetary boundary layer heights.

17 WIND ENERGY↗

Tower Mesonetwork Climatology and Interactive Display Tool

Forecasters at the 45th Weather Squadron and Spaceflight Meteorology Group use data from the tower network over the Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) to evaluate Launch Commit Criteria, and issue and verify forecasts for ground operations. Systematic biases in these parameters could adversely affect an analysis, forecast, or verification. Also, substantial geographical variations in temperature and wind speed can occur under specific wind directions. To address these concerns, the Applied Meteorology Unit (AMU) developed a climatology of temperatures and winds from the tower network, and identified the geographical variation and significant tower biases. The mesoclimate is largely driven by the complex land-water interfaces across KSC/CCAFS. Towers with close proximity to water typically had much warmer nocturnal temperatures and higher wind speeds throughout the year. The strongest nocturnal wind speeds occurred from October to March whereas the strongest mean daytime wind speeds occurred from February to May. These results of this project can be viewed by forecasters through an interactive graphical user interface developed by the AMU. The web-based interface includes graphical and map displays of mean, standard deviation, bias, and data availability for any combination of towers, variables, months, hours, and wind directions.

Case, Jonathan L.↗