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At least 91 records · Page 5

A Comparison of GPS and Scatterometer Sensing of Ocean Wind Speed and Direction

Initial estimates of ocean surface wind speed and direction based on observations of reflected Global Positioning System (GPS) signals are presented and compared to QuikSCAT wind fields. The two wind speed estimates are generally in agreement to within 2-3 m/s, and under favorable conditions of well developed seas and stable winds, direction estimates agree to within 10 deg. An overview of the GPS technique is presented as well as a presentation and discussion of these first results.

Armatys, Michael↗

Characterization of wind speed and directional shear at the AWAKEN field campaign site

The American wake experiment (AWAKEN) is taking place in northern Oklahoma, USA, close to the Atmospheric Radiation Measurement Southern Great Plains (ARM SGP) atmospheric observatory. The planning for the deployment of the instruments in this observational field campaign required an assessment of the wind characteristics of the site. This paper analyzes long-term data collected by instruments at the ARM SGP observatory to characterize the winds near the AWAKEN site. The analysis shows that this site experiences high wind shear and veer events with a large number of nocturnal low-level jets. A total of 7086 low-level jet wind profiles over 6 years are examined and found to be dominant from the south and southeast. Significant nocturnal wind veer is observed, which causes southerly wind near the surface to become westerly wind aloft. By identifying a strong relationship between atmospheric stability and wind shear, the wind shear at the site is predicted using the Monin–Obukhov similarity theory (MOST) and validated with the observational data collected by a scanning Doppler lidar. The results show that wind speed at a height of 91 m, a proxy hub height for wind turbines in this area, can be predicted from data collected at a height of 10 m with a bias of −0.35 and 0.65 m s−1 in unstable and stable atmospheric boundary layers, respectively. The bias of the predicted wind speed is mostly in the region of low wind speed, and wind speed above 5 m s−1 at a height of 91 m can be predicted with a bias of less than 0.2 m s−1, and the limitations of the MOST in predicting winds during the stably stratified boundary layer is well-observed.

17 WIND ENERGY↗

Maxometers (peak wind speed anemometers)

An instrument for measuring peak wind speeds under severe environmental conditions is described, comprising an elongated cylinder housed in an outer casing. The cylinder contains a piston attached to a longitudinally movable guided rod having a pressure disk mounted on one projecting end. Wind pressure against the pressure disk depresses the movable rod. When the wind reaches its maximum speed, the rod is locked by a ball clutch mechanism in the position of maximum inward movement. Thereafter maximum wind speed or pressure readings may be taken from calibrated indexing means.

Kaufman, J. W.↗

An analysis of maximum horizontal wind speeds recorded since 1961 at Kennedy Space Center, Florida

Tabulations of maximum horizontal wind speed values are reported that were recorded at the Kennedy Space Center. Maximum wind speeds were recorded during the eight hurricanes which have affected the area--Cleo in August 1964 through Agnes in June 1972. Detailed tabulations and frequency distributions of daily maximum horizontal wind speeds recorded at NASA's 150 m ground tower facility at nine levels from December 1965 through March 1970 are also included.

Alexander, M. B.↗

Characterization of HRRR-simulated rotor layer wind speeds and clouds along the coast of California

Stratocumulus clouds, with their low cloud base and top, affect the atmospheric boundary layer wind and turbulence profile, thereby modulating wind energy resources. GOES satellite data reveal an abundance of stratocumulus clouds in the late spring and summer months off the coast of northern and central California, where there are active plans to deploy floating offshore wind farms at two lease areas (near Morro Bay and Humboldt). Since the fall of 2020, two buoys equipped with multiple instruments, including Doppler lidar, have been deployed for about 1 year in these wind farm lease areas to assess the rotor layer wind conditions in these locations. The objective of this study is to evaluate how well the High-Resolution Rapid Refresh (HRRR) model represents stratocumulus cloud characteristics and turbine-relevant rotor layer winds (surface to 300 m) by comparing HRRR simulations with buoy and satellite observations. We first find that the HRRR model reproduces the seasonal cycle of cloud top height reasonably well in these regions. However, during the warm season – especially at Morro Bay – the HRRR-simulated stratocumulus clouds tend to have lower tops by about 150 m and exhibit weaker diurnal cycles than satellite observations. Our analysis also shows that rotor layer wind speeds and vertical shear are stronger at Humboldt than at Morro Bay, and both are generally stronger under clear-sky conditions. Finally, the HRRR model bias in rotor layer wind speed is small under cloudy conditions but larger and dependent on observed wind speed under clear skies. Specifically, HRRR underestimates wind speeds at Morro Bay and overestimates them at Humboldt under clear-sky conditions.

17 WIND ENERGY↗

An empirical model for ocean radar backscatter and its application in inversion routine to eliminate wind speed and direction effects

Several regression models were tested to explain the wind direction dependence of the 1975 JONSWAP (Joint North Sea Wave Project) scatterometer data. The models consider the radar backscatter as a harmonic function of wind direction. The constant term accounts for the major effect of wind speed and the sinusoidal terms for the effects of direction. The fundamental accounts for the difference in upwind and downwind returns, while the second harmonic explains the upwind-crosswind difference. It is shown that a second harmonic model appears to adequately explain the angular variation. A simple inversion technique, which uses two orthogonal scattering measurements, is also described which eliminates the effect of wind speed and direction. Vertical polarization was shown to be more effective in determining both wind speed and direction than horizontal polarization.

Dome, G. J.↗

Large-scale Advanced Prop-fan (LAP) high speed wind tunnel test report

High Speed Wind Tunnel testing of the SR-7L Large Scale Advanced Prop-Fan (LAP) is reported. The LAP is a 2.74 meter (9.0 ft) diameter, 8-bladed tractor type rated for 4475 KW (6000 SHP) at 1698 rpm. It was designated and built by Hamilton Standard under contract to the NASA Lewis Research Center. The LAP employs thin swept blades to provide efficient propulsion at flight speeds up to Mach .85. Testing was conducted in the ONERA S1-MA Atmospheric Wind Tunnel in Modane, France. The test objectives were to confirm that the LAP is free from high speed classical flutter, determine the structural and aerodynamic response to angular inflow, measure blade surface pressures (static and dynamic) and evaluate the aerodynamic performance at various blade angles, rotational speeds and Mach numbers. The measured structural and aerodynamic performance of the LAP correlated well with analytical predictions thereby providing confidence in the computer prediction codes used for the design. There were no signs of classical flutter throughout all phases of the test up to and including the 0.84 maximum Mach number achieved. Steady and unsteady blade surface pressures were successfully measured for a wide range of Mach numbers, inflow angles, rotational speeds and blade angles. No barriers were discovered that would prevent proceeding with the PTA (Prop-Fan Test Assessment) Flight Test Program scheduled for early 1987.

Campbell, William A.↗

The wind-speed measurement capability of spaceborne radar altimeters

This study represents an attempt to quantitatively assess the capability of a spaceborne radar altimeter to infer ocean surface wind speeds from a measurement of the backscattered power at vertical incidence. The study uses data acquired during 184 near overflights of NOAA data buoys with the GEOS-3 satellite radar altimeter and encompasses a wind-speed range from less than 1 to 18 m/s. An algorithm is derived from the data comparison for converting measurements of the normalized scattering cross section of the ocean surface at 13.9 GHz into estimates of the surface wind speed at the standard anemometer height of 10 m. The algorithm is straightforward and potentially useful for on-board processing of raw altimeter data for the purpose of providing real-time estimates of surface wind speed. For winds in the range of 1 to 18 m/s, the mean difference between the altimeter-inferred winds and the buoy measurements is negligible while the standard deviation of the difference is 1.74 m/s.

Brown, G. S.↗

Improving Multiday Solar Wind Speed Forecasts

We analyze the residual errors for the Wang-Sheeley-Arge (WSA) solar wind speed forecasts as a function of the photospheric magnetic field expansion factor (fp) and the minimum separation angle (d) in the photosphere between the footpoints of open field lines and the nearest coronal hole boundary. We find the map of residual speed errors are systematic when examined as a function of fp and d. We use these residual error maps to apply corrections to the model speeds. We test this correction approach using 3-day lead time speed forecasts for an entire year of observations and model results. Our methods can readily be applied to develop corrections for the remaining WSA forecast lead times which range from 1 to 7 days in 1-day increments. Since the solar wind density, temperature, and the interplanetary magnetic field strength all correlate well with the solar wind speed, the improved accuracy of solar wind speed forecasts enables the production of multiday forecasts of the solar wind density, temperature, pressure, and interplanetary field strength, and geophysical indices. These additional parameters would expand the usefulness of Air Force Data Assimilative Photospheric Flux Transport-WSA forecasts for space weather clients.

H A Elliot↗

Validation of Special Sensor Microwave Imager monthly-mean wind speed from July 1987 to December 1989

Since July 1987, the Remote Sensing Systems (Santa Rosa, California) routinely computes from first principles the wind speed from Special Sensor Microwave Imager (SSM/I) measurements of the intensity of microwave radiation emitted at the ocean surface. The accuracy of monthly-mean SSM/I wind speeds is determined by comparisons with moored-buoy wind measurements, which were recorded by four different institutions at 44 sites in the Atlantic and Pacific Oceans during July 1987 to December 1989. All results for 1988 were virtually identical with 1989. The range of monthly mean moored-buoy wind speeds was 2-10 m/s. The rms difference of 697 monthly-mean matchups of the composite 1988 and 1989 data set was 1.2 m/s. The rms differences were smaller in the equatorial zone and higher in middle latitudes, in accord with the monthly standard deviation. At middle latitudes, the time series of rms differences displayed an annual cycle. In the equatorial zone, the agreement between SSM/I and in situ data was better in regions with a lesser amount of clouds, and vice versa. For SSM/I monthly standard deviations of 1-2, 2-3, and 3-4 m/s, the average absolute values of the monthly-mean difference between SSM/I and moored-buoy wind speeds were 0.6, 0.9, and 1.4 m/s, respectively.

Halpern, David↗

Validation of Special Sensor Microwave Imager Monthly-Mean Wind Speed From July 1987 to December 1989

Since July 1987 the Remote Sensing Systems, Santa Rosa, California, routinely computes from first principles the wind speed from Special Sensor Microwave Imager (SSM/I) measurements of the intensity of microwave radiation emitted at the ocean surface. The accuracy of monthly-mean SSM/I wind speeds is determined by comparisons with moored-buoy wind measurements, which were recorded by four different institutions at 44 sites in the Atlantic and Pacific Oceans during July 1987 to December 1989. All results for 1988 were virtually identical with 1989. The range of monthly mean moored-buoy wind speeds was 2-10 m s^(-1). During 1987, the equatorial matchups were not equivalent with 1998 and 1989, and the cause remains unknown. The root-mean-square (rms) difference of 697 monthly-mean matchups of the composite 1988 and 1989 data set was 1.2 m s^(-1). The rms differences were smaller in the equatorial zone and higher in middle latitudes, in accord with the monthly standard deviation. At middle latitudes the time series of rms differences displayed an annual cycle. In the equatorial zone the agreement between SSM/I and in situ data was better in regions with a lesser amount of clouds, and vice versa. For SSM/I monthly standard deviations of 1-2, 2-3, and 3-4 m s^(-1), the average absolute values of the monthly-mean difference between SSM/I and moored-buoy wind speeds were 0.6, 0.9, and 1.4 m s^(-1), respectively.

Halpern, D.↗

Effects of slope steepness and cross-slope wind speed on fire spreading behavior for various vegetation

Wildland fire behavior is significantly influenced by environmental factors such as slope steepness, wind speed, and fuel type. Understanding these interactions is critical for improving predictive models and fire management. This study explores how slope steepness and cross-slope wind speed influence fire spread dynamics in various fuel bed types. Simulations are conducted using a physics-based wildland fire model, HIGRAD/FIRETEC, across six slope angles (0–50 %), four cross-slope wind speeds (4–10 m s –1 ), and three fuel bed types (grass, shrubland, and forest). Representative cases are additionally compared with FARSITE fireline evolution. Fire behavior is categorized into distinct propagation types based on spread characteristics and analyzed. The fire propagation angle, which indicates deviation from the wind direction, generally increases with steeper slopes and decreases with stronger cross-slope winds. Secondary upslope propagation is observed in shrubland under moderate slopes, while secondary downwind propagation occurs in all fuel beds at higher wind speeds. These findings highlight fire spread characteristics that differ from predictions by traditional models like Rothermel’s. By capturing complex propagation patterns and dynamics, this study demonstrates the value of a physics-based, atmosphere-fire coupled model for accurate wildland fire prediction. Incorporating secondary propagations and the influence of fuel bed complexities into predictive models can improve the accuracy of fire spread forecasts, enabling more effective fire management and risk mitigation efforts.

54 ENVIRONMENTAL SCIENCES↗

On the high correlation between long-term averages of solar wind speed and geomagnetic activity

Six-month and yearly averages of solar-wind speed from 1962 to 1975 are shown to be highly correlated with geomagnetic activity as measured by averages of the Ap index. On the same time scale the correlation between the southward component of the interplanetary magnetic field and geomagnetic activity is poor. Previous studies with hourly averages gave opposite results. The better correlation with the southward component on an hourly time scale is explained by its large variation compared with the relatively constant solar-wind speed. However, on a yearly time scale the magnitude of the variations in both parameters are about the same. This problem can be solved by invoking an energy transfer mechanism which is proportional to the first power of the southward component and a higher power of the solar-wind speed.

Crooker, N. U.↗

Comparing Ulysses wind speed with coronal flux-tube expansion factor

We have been comparing measurements of solar wind speed at the Ulysses spacecraft with coronal flux-tube expansion rates, derived from photospheric field measurements using a current-free coronal model. The large-scale patterns of derived speed have continued to reproduce the observed patterns from launch through south polar passage to the present 40S latitude of the spacecraft. The fastest non-transient wind speeds of approx. 860 km/s were encountered at midlatitudes en route to the south pole, rather than during polar passage when the peak speeds were approx. 820 km/s. Although this result is in qualitative agreement with the idea that the wind speed is controlled by the coronal flux-tube expansion rate, the 40 km/s difference is significantly smaller than the 100-150 km/s difference based on our in-ecliptic calibration. This paper will summarize our attempts to resolve this discrepancy and will show the observational status of our coronal/interplanetary comparison at the time of the meeting.

Sheeley, N. R., Jr.↗

Assimilation of satellite surface wind speed data using the GLA analysis/forecast system

Research at the Goddard Laboratory for Atmospheres to evaluate methods to assign directions to both real and simulated surface wind speed data is discussed. Surface wind speed measurements are obtained from satellites, including Seasat, Nimbus-7, and Geosat. The methods include the interpolation of modeled forecast winds to the wind speed datum location, the use of surface pressures with a balance relation, and a variational analysis method. It is found that the best estimates may be obtained using a multipass approach to perform a surface analysis incorporating all conventional surface data.

Bloom, S. C.↗

Estimates of oceanic surface wind speed and direction using orthogonal beam scatterometer measurements and comparison of recent sea scattering theories

The wind direction properties of radar backscatter from the sea were empirically modelled using a cosine Fourier series through the 4th harmonic in wind direction (referenced to upwind). A comparison with 1975 JONSWAP (Joint North Sea Wave Project) scatterometer data, at incidence angles of 40 and 65, indicates that effects to third and fourth harmonics are negligible. Another important result is that the Fourier coefficients through the second harmonic are related to wind speed by a power law expression. A technique is also proposed to estimate the wind speed and direction over the ocean from two orthogonal scattering measurements. A comparison between two different types of sea scatter theories, one type presented by the work of Wright and the other by that of Chan and Fung, was made with recent scatterometer measurements. It demonstrates that a complete scattering model must include some provisions for the anisotropic characteristics of the sea scatter, and use a sea spectrum which depends upon wind speed.

Moore, R. K.↗

Laboratory Heat Flux Estimates of Seawater Foam for Low Wind Speeds

Laboratory experiments were conducted to measure the heat flux from seafoam continuously generated in natural seawater. Using a control volume technique, heat flux was calculated from foam and foam-free surfaces as a function of ambient humidity (ranged from 40% to 78%), air–water temperature difference (ranged from -9 °C to 0 °C), and wind speed (variable up to 3 m s-1). Water-surface skin temperature was imaged with a calibrated thermal infrared camera, and near-surface temperature profiles in the air, water, and foam were recorded. Net heat flux from foam surfaces increased with increasing wind speed and was shown to be up to four times greater than a foam-free surface. The fraction of the total heat flux due to the latent heat flux was observed for foam to be 0.75, with this value being relatively constant with wind speed. In contrast, for a foam-free surface the fraction of the total heat flux due to the latent heat flux decreased at higher wind speeds. Temperature profiles through foam are linear and have larger gradients, which increased with wind speed, while foam free surfaces show the expected logarithmic profile and show no variation with temperature. The radiometric surface temperatures show that foam is cooler and more variable than a foam-free surface, and bubble-resolving thermal images show that radiometrically transparent bubble caps and burst bubbles reveal warm foam below the cool surface layer, contributing to the enhanced variability.

54 ENVIRONMENTAL SCIENCES↗