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DOE OSTI2025

Probabilistic Hazard Assessment for Tornadoes, Straight-Line Wind, and Extreme Precipitation at the Savannah River Site

Recent data sets for three meteorological phenomena with the potential to inflict damage on SRS facilities – tornadoes, straight-line winds, and heavy precipitation – are analyzed using appropriate statistical techniques to estimate the occurrence probabilities for these events in the future. Summaries of the results for DOE-mandated return periods and comparisons to similar calculations performed in 2013 by Werth et al. (W2013) are given. Using tornado statistics for i) the combined states of Georgia and South Carolina, and ii) a 2⁰ square area surrounding SRS, we calculated the probability per year of any location at SRS being struck by a tornado (the ‘strike’ probability) and the probability that any point will experience winds above set thresholds. The strike probability was calculated to be 7.04E-4 (1 chance in 1420) per year and tornadic wind speeds for DOE mandated return periods of 50,000 years (corresponding to wind design category 3 (WDC-3), and 125,000 years (meeting WDC-4) (USDOE, 2016) were estimated to be 132 mph and 147 mph, respectively. By contrast, default tornado wind speeds taken from ANSI/ANS-2.3-2011 are somewhat higher: 161 mph for return periods of 50,000 years and 173 mph every 125,000 years (ANS, 2011). Although the ANS and the SRS evaluation used the same basic model (Ramsdell and Rishel, 2007), the region defined in ANS 2.3 that encompasses the SRS also includes areas of the Great Plains and lower Midwest, regions with much higher occurrence frequencies of strong tornadoes. The SRS straight-line wind values associated with various return periods were calculated by fitting existing wind data to a GEV1 distribution and extrapolating the values for any return period from the tail of that function. For the DOE mandated return periods, we expect straight-line winds of 117 mph every 2500 years (the required WDC-3 standard) and 125 mph every 6250 years (WDC-4) at any point within the SRS. These values are similar to those from the ANS-2.3-2011 report, which has wind speeds of 125mph and 133 mph for return periods of 2500 years and 6250 years, respectively. For extreme precipitation, we compared the fits of two different theoretical extreme-value distributions and applied the one that fit the data best for each of several accumulation periods. The DOE mandated 6-hr accumulated rainfall for return periods of 10,000 years (corresponding to precipitation design category 3 (PDC-3) and 25,000 years (PDC-4) were estimated as 9.1 inches and 10.1 inches, respectively. For the 24-hr rainfall return periods of 10,000 years and 25,000 years, total rainfall estimates were 12.02 inches and 13.17 inches, respectively, higher than comparable values provided in the W2013 report.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Evaluation of coupled wind-wave model simulations of offshore winds in the Mid-Atlantic Bight using lidar-equipped buoys.

From 2014 to 2017, two Department of Energy buoys equipped with Doppler lidar were deployed off the U.S. East Coast to provide long term measurements of hub-height wind speed in the marine environment. In this study, we performed simulations of selected cases from the deployment using a 5-km configuration of the Weather Research and Forecasting (WRF) model, to see if simulated hub height speeds could produce closer agreement with the observations than existing reanalysis products. For each case we performed two additional simulations: one in which marine surface roughness height was one-way coupled to forecast wave parameters from a standalone WaveWatch III (WW3) simulation, and another in which WRF and WW3 were two-way coupled using the Coupled-Ocean-Atmosphere-Wave-Sediment-Transport (COAWST) framework. It was found that all the 5-km WRF simulations improved 90-m wind speed statistics for the tropical cyclone case of 08 May 2015 and the cold frontal case of 25 Mar 2016, but not the nor-easter of 18 Jan 2016. The impact of wave coupling on buoy-level (4 m) wind speed was modest and case dependent, but when present, the impact was typically seen at 90 m as well, being as large as 10% in stable conditions. One-way wave coupling consistently reduced wind speeds, improving biases for 25 Mar 2016 but worsening them for 08 May 2015. Two-way wave coupling mitigated these negative biases, improved wave field representation and statistics, and mostly improved 4-m wind field correlation coefficients, at least at the VA buoy, largely due to greater self-consistency between wind and wave fields.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1980

Use of nose cap and fuselage pressure orifices for determination of air data for space shuttle orbiter below supersonic speeds

Wind tunnel pressure measurements were acquired from orifices on a 0.1 scale forebody model of the space shuttle orbiter that were arranged in a preliminary configuration of the shuttle entry air data system (SEADS). Pressures from those and auxiliary orifices were evaluated for their ability to provide air data at subsonic and transonic speeds. The orifices were on the vehicle's nose cap and on the sides of the forebody forward of the cabin. The investigation covered a Mach number range of 0.25 to 1.40 and an angle of attack range from 4 deg. to 18 deg. An air data system consisting of nose cap and forebody fuselage orifices constitutes a complete and accurate air data system at subsonic and transonic speeds. For Mach numbers less than 0.80 orifices confined to the nose cap can be used as a complete and accurate air data system. Air data systems that use only flush pressure orifices can be used to determine basic air data on other aircraft at subsonic and transonic speeds.

Larson, T. J.↗

DOE OSTI2022

UAE6 - Wind Tunnel Tests Data - UAE6 - Sequence 5 - Raw Data

Sequence 5: Sweep Wind Speed (F,P) This test sequence used an upwind, rigid turbine with a 0° cone angle. The wind speed was ramped from 5 m/s to 25 m/s by the wind tunnel operator. This was repeated with a decreasing ramp. The yaw angle was maintained at 0°. The blade tip pitch was 3° or 6°. The rotor rotated at 72 RPM. Blade pressure and probe measurements were collected for both pitch angles. The five-hole probes were removed and the plugs were installed for another 3° pitch case. Plastic tape 0.03 mm thick was used to smooth the interface between the plugs and the blade. The teeter dampers were replaced with rigid links, and these two channels were flagged as not applicable by setting the measured values in the data file to –99999.99 Nm. The teeter link load cell was pre-tensioned to 40,000 N. During post-processing, the probe channels were set to read -99999.99. The 6- minute campaigns were named using the sequence designation 5, followed by DN or UP, which indicates the wind speed ramp direction. The next four digits are 0000, and the sequence digit is at the end.

17 WIND ENERGY↗

DOE OSTI2022

UAE6 - Wind Tunnel Tests Data - UAE6 - Sequence B - Raw Data

Sequences B, C, and D: Downwind Baseline (F), Downwind Low Pitch (F), Downwind High Pitch (F) This test sequence used a downwind, teetered turbine with a 3.4° cone angle. The wind speed ranged from 5 m/s to 25 m/s. Yaw angles of ±180° were achieved at low wind speeds, and yaw angles of -20° to 10° were achieved for high wind speeds. The blade tip pitch was 3° for sequence B, 0° for sequence C, and 6° for sequence D. These three sequences were interleaved during testing because the pitch angle change was easily made by the turbine operator. The rotor rotated at 72 RPM. Blade and probe pressure measurements were collected.

17 WIND ENERGY↗

DOE OSTI2022

UAE6 - Wind Tunnel Tests Data - UAE6 - Sequence C - Raw Data

17 WIND ENERGY↗

DOE OSTI2022

UAE6 - Wind Tunnel Tests Data - UAE6 - Sequence D - Raw Data

17 WIND ENERGY↗

NASA NTRS1992

Low-level nocturnal wind maximum over the Central Amazon Basin

A low-level nocturnal wind maximum is shown to exist over extensive and nearly undisturbed rainforest near the central Amazon city of Manaus. Meteorological data indicate the presence of this nocturnal wind maximum during both the wet and dry seasons of the Central Amazon Basin. Daytime wind speeds which are characteristically 3-7 m/s between 300 and 1000 m increase to 10-15 m/s shortly after sunset. The wind-speed maximum is reached in the early evening, with wind speeds remaining high until several hours after sunrise. The nocturnal wind maximum is closely linked to a strong low-level inversion formed by radiational cooling of the rainforest canopy. Surface and low-level pressure gradients between the undisturbed forest and the large Amazon river system and the city of Manaus are shown to be responsible for much of the nocturnal wind increase. The pressure gradients are interpreted as a function of the thermal differences between undisturbed forest and the river/city. The importance of both the frictional decoupling and the horizontal pressure gradient suggest that the nocturnal wind maximum does not occur uniformly over all Amazonia. Low-level winds are thought to be pervasive under clear skies and strong surface cooling and that, in many places (i.e., near rivers), local pressure gradients enhance the low-level nocturnal winds.

Greco, Steven↗

NASA NTRS1999

Evaluation of Wind Profiler Data

This report presents the Applied Meteorology Unit's evaluation of a "Hypersodar" wind profiler located on KSC adjacent to tower 412. The sodar data used for this evaluation were collected during two different periods in March 1999 and November 1998. The evaluation is performed by calculating sodar data availability as a function of height, and bias and Root Mean Square (RMS) differences of wind speed and direction between sodar and tower 313 observations at comparable heights. The RMS differences in wind speed and wind direction from sodar wind solution B at KSC range from 0.65 m s (exp. -1) - 2.04 m s (exp. -1) and 4.5 - 32.3 deg., respectively. Note that these RMS differences are not bias-corrected. The vendor claims that the accuracy of the wind measurements from the sodar is better than 0.5 m s (exp -1) in speed and 10 deg. in direction. The results of the evaluation described here suggest that such accuracy may be attainable though the data available for this comparison made it impossible to confirm the vendor's claims. The sodar was not aligned with true north and was separated by a distance of 3.5 km from tower 313 used for comparisons in this study.

Manobianco, John↗

NASA NTRS1976

Vector wind and vector wind shear models 0 to 27 km altitude for Cape Kennedy, Florida, and Vandenberg AFB, California

The techniques are presented to derive several statistical wind models. The techniques are from the properties of the multivariate normal probability function. Assuming that the winds can be considered as bivariate normally distributed, then (1) the wind components and conditional wind components are univariate normally distributed, (2) the wind speed is Rayleigh distributed, (3) the conditional distribution of wind speed given a wind direction is Rayleigh distributed, and (4) the frequency of wind direction can be derived. All of these distributions are derived from the 5-sample parameter of wind for the bivariate normal distribution. By further assuming that the winds at two altitudes are quadravariate normally distributed, then the vector wind shear is bivariate normally distributed and the modulus of the vector wind shear is Rayleigh distributed. The conditional probability of wind component shears given a wind component is normally distributed. Examples of these and other properties of the multivariate normal probability distribution function as applied to Cape Kennedy, Florida, and Vandenberg AFB, California, wind data samples are given. A technique to develop a synthetic vector wind profile model of interest to aerospace vehicle applications is presented.

Smith, O. E.↗

NASA NTRS1979

Preliminary analysis of performance and loads data from the 2-megawatt mod-1 wind turbine generator

Preliminary test data on output power versus wind speed, rotor blade loads, system dynamic behavior, and start-stop characteristics on the Mod-1 wind turbine generator are presented. These data were analyzed statistically and are compared with design predictions of system performance and loads. To date, the Mod-1 wind turbine generator has produced up to 1.5 MW of power, with a measured power versus wind speed curve which agrees closely with design. Blade loads were measured at wind speeds up to 14 m/s and also during rapid shutdowns. Peak transient loads during the most severe shutdowns are less than the design limit loads. On the inboard blade sections, fatigue loads are approximately equal to the design cyclic loads. On the outboard blade sections, however, measured cyclic loads are significantly larger than design values, but they do not appear to exceed fatigue allowable loads as yet.

Spera, D. A.↗

DOE OSTI2024

Quantitative comparison of power production and power quality onshore and offshore: a case study from the eastern United States

Abstract. A major issue in quantifying potential power generation from prospective wind energy sites is the lack of observations from heights relevant to modern wind turbines, particularly for offshore where blade tip heights are projected to increase beyond 250 m. We present analyses of uniquely detailed data sets from lidar (light detection and ranging) deployments in New York State and on two buoys in the adjacent New York Bight to examine the relative power generation potential and power quality at these on- and offshore locations. Time series of 10 min wind power production are computed from these wind speeds using the power curve from the International Energy Agency 15 MW reference wind turbine. Given the relatively close proximity of these lidar deployments, they share a common synoptic-scale meteorology and seasonal variability with lowest wind speeds in July and August. Time series of power production from the on- and offshore location are highly spatially correlated with the Spearman rank correlation coefficient dropping below 0.4 for separation distances of approximately 350 km. Hence careful planning of on- and offshore wind farms (i.e., separation of major plants by > 350 km) can be used reduce the system-wide probability of low wind energy power production. Energy density at 150 m height at the offshore buoys is more than 40 % higher, and the Weibull scale parameter is 2 m s−1 higher than at all but one of the land sites. Analyses of power production time series indicate annual energy production is almost twice as high for the two offshore locations. Further, electrical power production quality is higher from the offshore sites that exhibit a lower amplitude of diurnal variability, plus a lower probability of wind speeds below the cut-in and of ramp events of any magnitude. Despite this and the higher resource, the estimated levelized cost of energy (LCoE) is higher from the offshore sites mainly due to the higher infrastructure costs. Nonetheless, the projected LCoE is highly competitive from all sites considered.

Foody, Rebecca↗

NASA NTRS1995

Polarimetric measurements of sea surface brightness temperatures using an aircraft K-band radiometer

This paper presents the first experimental evidence that the polarimetric brightness temperatures of sea surfaces are sensitive to ocean wind direction in the incidence angle range of 30 to 50 degrees. Our experimental data were collected by a K-band (19.35 GHz) polarimetric wind radiometer (WINDRAD) mounted on the NASA DC-8 aircraft. A set of aircraft radiometer flights was successfully completed in November 1993. We performed circle flights over National Data Buoy Center (NDBC) moored buoys deployed off the northern California coast, which provided ocean wind measurements. The first WINDRAD flight was made on November 4, 1993. There was clear weather with a wind speed of 12 m/s at 330 degrees around the Pt. Arena buoy. We circled the buoy at three incidence angles, and all data when plotted as functions of azimuth angles show clear modulations of several Kelvin. At 40 degrees incidence angle, there is a 5 Kelvin peak-to-peak signal in the second Stokes parameter Q and the third Stokes parameter U. The Q data maximum is in the upwind direction and U has a 45 degrees phase shift in azimuth as predicted by theory. There is also an up/downwind asymmetry of 2 Kelvin in the Q data, and 1 Kelvin in the U data. At 50 degrees incidence angle, the collected data show very similar wind direction signatures to the SSM/I model function. Additional flights were made on other days under cloudy conditions. Data taken at a wind speed of 8 m/s show that at 40 degrees incidence Q and U have a smaller azimuthal modulation of 3 Kelvin, probably due to the lower wind speed. Additionally, the simultaneously recorded video images of sea surfaces suggested that Q and U data were less sensitive to unpolarized geophysical variations, such as clouds and whitecaps, while the T(v) and T(h) increased by a few Kelvin when the radiometer beam crossed over clouds, or there was a sudden increase of whitecaps in the radiometer footprint. The results of our aircraft flights indicate that passive polarimetric radiometry has a strong potential for global ocean wind speed and direction measurements from space.

Yueh, Simon H.↗

NASA NTRS2005

NASA Langley Low Speed Aeroacoustic Wind Tunnel: Background Noise and Flow Survey Results Prior to FY05 Construction of Facilities Modifications

The NASA Langley Research Center Low Speed Aeroacoustic Wind Tunnel is a premier facility for model-scale testing of jet noise reduction concepts at realistic flow conditions. However, flow inside the open jet test section is less than optimum. A Construction of Facilities project, scheduled for FY 05, will replace the flow collector with a new design intended to reduce recirculation in the open jet test section. The reduction of recirculation will reduce background noise levels measured by a microphone array impinged by the recirculation flow and will improve flow characteristics in the open jet tunnel flow. In order to assess the degree to which this modification is successful, background noise levels and tunnel flow are documented, in order to establish a baseline, in this report.

Booth, Earl R., Jr.↗

DOE OSTI2024

Automated Generation of Weather and Climate Analysis Products

Wind roses are an important part to site operations as they depict the wind speed and direction percentage over a time period. In this project, I automated the production of wind roses for SRS meteorological towers. I developed a script to sequence through the dataset by period and create a wind rose for each of those period sets. Graphics were generated for every 4-hour period of the day, for each of the 4 heights of the instruments, for every half of each month. A 10-year climatological period consisted of wind speed and directions measurements at 15-minute intervals. We used the years 2014-2024 as the wind instruments on the tower were upgraded to sonic anemometers in early 2014. I then compared these wind roses to those from a previous study done in 2003 to analyze the differences and similarities in the wind patterns. The wind roses are also used to understand environmental transport conditions at SRS. When comparing the different heights of the anemometers to the 2003 report, there is a similarity in the fact that the direction is relatively the same across the levels, with the wind speeds increasing as you get higher in the air. When comparing the season of our graphs against the 2003 report, we noticed that the winter and summer months appear to have very similar wind directions. However, in the spring we noticed that there were more southerly winds compared to the 2003 report which had more westerly winds. Finally, in the fall months, we noticed that there was a higher percentage of northeasterly winds, while the 2003 report showed more southeasterly winds. We can use these summaries to estimate the directional dependence of dose that the surrounding areas receive throughout the year according to time of day.

47 OTHER INSTRUMENTATION↗

NASA NTRS1993

Geophysics, Oceanography

Development of decade-long time series of global surface wind measurements for studies ofseasonal-to-interannual climate variability presents unique challenges for space- borne instrumentationbecause of the necessity to combine data sets of 3- to 5-year lifetimes. Before the first Special SensorMicrowave Imager (SSMI), which was launched on the Defence Meteorological Satellite Program(DMSP) F8 spacecraft in July 1987, stopped recording wind speed in December 1991, another SSMIwas launched on DMSP F10 in December 1991. Interpretation of the 1987 - 1993 composite timeseries is dependent upon the space and time characteristics of the differences between concurrent F8and F10 SSMI measurements. This paper emphasizes large geographical regions and 1-month timescale. The F8-F10 area-weighted difference between 60 degrees S and 60 degrees S during 305 daysof 1991 (-0.12 m s^(-1)) was comparable to the year-to-year wind speed variations during 1988-1991. The 10 degree-zonal averaged monthly mean F8-F10 difference was negative (positive) forwind speeds less (greater) than 7.9 m s^(-1), reaching - 0.43(0.32) m s^(-1) at 5(10) m s^(-1). The10 degree-zonal averaged monthly mean F8-F10 bias had considerable variations throughout the yearand between 60 degrees S - 60 degrees N, with the largest temporal variation (1.4 m s^(-1)) in the 50degrees - 60 degrees N region from February to April. The 1991 average value of the monthly meanroot-mean-square (rms) difference between F8 and F10 daily wind speeds in 10 degree-longitudinalbands was 2.0 m s^(-1) over 60 degrees S - 60 degrees N, the amplitude of the annual cycle of therms difference was largest in the northern hemisphere middle latitudes, and the rms difference wasrelated to the wind speed (e.g., at 6 and 10 m s^(-1), the rms difference was 1.7 and 2.7 m s^(-1),respectively). The relationship between monthly mean 1/3 degrees x 1/3 degrees F8-F10 SSMI windspeed differences and integrated water vapor and liquid water content in the atmosphere is discussed.

Halpern, D.↗

NASA NTRS1979

Relationship between hurricane surface winds and L-band radar backscatter from the sea surface

High-altitude, airborne, L-band synthetic aperture radar (SAR) data were collected in Hurricane Gloria on 28 and 30 September 1976. The backscattered power levels (proportional to the surface scattering coefficient) averaged over a few square kilometers of surface area were found to vary with surface wind speed and the angle of the wind relative to the radar. Comparisons between the backscatter from the eye and eye-wall regions of the hurricane were made with low-level aircraft wind measurements that were nearly coincident in space and time. The SAR has the potential advantage over other radar types because of its higher spatial resolution. It also appears to have the ability to penetrate rainfall, with a reduction in the echo from the surface. One difference when compared with higher frequency microwave radars is a decrease in the sensitivity of the backscatter to changes in wind speed. This dependence of L-band radar backscatter on surface winds suggests that the winds associated with hurricanes can be measured with airborne or spaceborne radars.

Weissman, D. E.↗

NASA NTRS1976

Low-speed wind-tunnel tests of a large scale blended arrow advanced supersonic transport model having variable cycle engines and vectoring exhaust nozzles

A low-speed wind-tunnel investigation was conducted in a full-scale tunnel to determine the performance and static stability and control characteristics of a large-scale model of a blended-arrow advanced supersonic transport configuration incorporating variable-cycle engines and vectoring exhaust nozzles. Configuration variables tested included: (1) engine mode (cruise or low-speed), (2) engine exit nozzle deflection, (3) leading-edge flap geometry, and (4) trailing-edge flap deflection. Test variables included values of C sub micron from 0 to 0.38, values of angle of attack from -10 degrees to 30 degrees, values of angle of sideslip, from -5 degrees to 5 degrees, and values of Reynolds number, from 3.5 million to 6.8 million.

Parlett, L. P.↗