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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 73 records · Page 4
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NASA NTRS2022

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↗
NASA NTRS1993

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↗
NASA NTRS1992

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.↗
NASA NTRS1977

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.↗
NASA NTRS1995

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.↗
NASA NTRS1988

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.↗
NASA NTRS1978

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.↗
NASA NTRS1993

SSMI wind speed measurements over the Southern Hemisphere oceans

The Special Sensor Microwave Imager (SSMI) carried by the USAF Defense Meteorological Satellite Program spacecraft correlates the intensity of microwave radiation emitted at the ocean surface with the 10-m height wind speed. The 4-year mean global features of the SSMI data were similar to the climatological-mean annual wind speed estimated from ship reports. Time series of area-weighted 60 deg S - zero deg monthly mean wind speeds indicated that the South Indian Ocean had the largest wind speeds throughout the year.

Halpern, David↗
NASA NTRS1988

Scatterometer wind speed bias induced by the large-scale component of the wave field

In order to determine if an environmental bias exists in the winds measured by the Seasat A satellite scatterometer (SASS), the SASS wind speed observations, U(s), colocated with the buoy wind speed data, U(b), were analyzed. There was a trend in the SASS wind speed error, U(b) - U(s), which was found to be related to the degree of the development of wind-generated gravity waves; this trend (estimated to be 0.5 m/sec per 100 km of the generalized wind fetch) is capable of introducing a well-pronounced environmental bias into the scatterometer-produced global distributions of wind.

Glazman, R. E.↗
NASA NTRS2012

Observations of C-Band Brightness Temperature and Ocean Surface Wind Speed and Rain Rate in Hurricanes Earl And Karl (2010)

Ocean surface emission is affected by: a) Sea surface temperature. b) Wind speed (foam fraction). c) Salinity After production of calibrated Tb fields, geophysical fields wind speed and rain rate (or column) are retrieved. HIRAD utilizes NASA Instrument Incubator Technology: a) Provides unique observations of sea surface wind, temp and rain b) Advances understanding & prediction of hurricane intensity c) Expands Stepped Frequency Microwave Radiometer capabilities d) Uses synthetic thinned array and RFI mitigation technology of Lightweight Rain Radiometer (NASA Instrument Incubator) Passive Microwave C-Band Radiometer with Freq: 4, 5, 6 & 6.6 GHz: a) Version 1: H-pol for ocean wind speed, b) Version 2: dual ]pol for ocean wind vectors. Performance Characteristics: a) Earth Incidence angle: 0deg - 60deg, b) Spatial Resolution: 2-5 km, c) Swath: approx.70 km for 20 km altitude. Observational Goals: WS 10 - >85 m/s RR 5 - > 100 mm/hr.

Miller, Timothy↗
NASA NTRS1995

Dependence of velocity fluctuations on solar wind speeds: A simple analysis with IPS method

A number of theoretical works have suggested that MHD plasma fluctuations in solar winds should play an important role particularly in the acceleration of high speed winds inside or near 0.1 AU from the sun. Since velocity fluctuations in solar winds are expected to be caused by the MHD plasma fluctuations, measurements of the velocity fluctuations give clues to reveal the acceleration process of solar winds. We made interplanetary scintillation (IPS) observations at the region out of 0.1 AU to investigate dependence of velocity fluctuations on flow speeds. For evaluating the velocity fluctuation of a flow, we selected the IPS data-set acquired at 2 separate antennas which located in the projected flow direction onto the baseline plane, and tried to compare skewness of the observed cross correlation function(CCF) with skewness of modeled CCFs in which velocity fluctuations were parametrized. The integration effect of IPS along a ray path was also taken into account in the estimation of modeled CCFs. Although this analysis method is significant to derive only parallel fluctuation components to the flow directions, preliminary analyses show following results: (1) High speed winds (Vsw greater than or equal to 500 km/s out of 0.3 AU) indicate enhancement of velocity fluctuations near 0.1 AU; and (2) Low speed winds (Vsw less than or equal to 400 Km/s out of 0.3 AU) indicate small velocity fluctuations at any distances.

Misawa, H.↗
NASA NTRS1978

Wind speed and aerosol optical thickness estimates from aircraft observations of sea glitter

A method is proposed whereby the optical characteristics of the bright glitter pattern of the sunlight reflected from water are used to determine wind speed and aerosol optical thickness in the troposphere. Radiances observed from an aircraft are used to derive the aerosol optical thickness and the surface wind speed. A scanning radiometer is used to measure the radiances in several spectral channels within 45 deg of the nadir and in a plane transverse to the aircraft motion. The observations are taken under nearly cloudless sky conditions over the Pacific Ocean (long. 130.4 deg, lat. 42.3 deg), and the aircraft height is 150 m above water with a 292-deg heading. It is shown that the derived wind speed depends strongly on the width of the glitter pattern, and that the width of the computed radiance pattern at the 150-m aircraft height diverges from the measured value, indicating overestimated wind speed.

Ahmad, Z.↗
NASA NTRS1978

On the relationship of radar backscatter to wind speed and fetch

The physics of the interaction of electromagnetic waves with the ocean surface has been an active area of research for a number of years. This paper contains the results of satellite and aircraft experiments to investigate the ability of active microwave radars to infer surface wind speeds remotely. Data obtained from the recent National Aeronautics and Space Administration (NASA) Skylab experiment are compared with surface wind speeds measured by low-flying aircraft and ships-of-opportunity and found to give useful estimates of the ocean wind field. Also investigated was the influence of varying wave height on radar measurements of wind speed by measuring the backscattering cross-section for constant wind speed but variable wave conditions. It is found that this effect is of little importance.

Ross, D.↗
NASA NTRS1992

Comparison of wind speed measurements over the oceans with the Special Sensor Microwave/Imager and the Geosat altimeter

In order to compare wind speed estimates from the Geosat altimeter and the Special Sensor Microwave/Imager (SSM/I), 25 colocated passes, within 2 hours of each other, were selected and the SSM/I estimates of wind speed and atmospheric parameters extracted along the Geosat track. Both instruments and their algorithms are described. A statistical comparison of wind speed estimates is presented and the effects of the atmospheric parameters from Geosat are analyzed. Quasi-simultaneous measurements by Geosat and SSM/I, along a Geosat track in the North-East Pacific, are also presented.

Mognard, Nelly M.↗
NASA NTRS1992

Comparison of wind speed measurements over the oceans with the Special Sensor Microwave/Imager and the Geosat altimeter

In order to compare wind speed estimates from the Geosat altimeter and the Special Sensor Microwave/Imager (SSM/I), 25 colocated passes, within 2 hours of each other, were selected and the SSM/I estimates of wind speed and atmospheric parameters extracted along the Geosat track. Both instruments and their algorithms are described. A statistical comparison of wind speed estimates is presented and the effects of the atmospheric parameters from Geosat are analyzed. Quasi-simultaneous measurements by Geosat and SSM/I, along a Geosat track in the North-East Pacific, are also presented.

Mognard, Nelly M.↗
NASA NTRS2000

GPS Signal Scattering from Sea Surface: Wind Speed Retrieval Using Experimental Data and Theoretical Model

Global Positioning System (GPS) signals reflected from the ocean surface have potential use for various remote sensing purposes. Some possibilities arc measurements of surface roughness characteristics from which ware height, wind speed, and direction could be determined. For this paper, GPS-reflected signal measurements collected at aircraft altitudes of 2 km to 5 km with a delay-Doppler mapping GPS receiver arc used to explore the possibility of determining wind speed. To interpret the GPS data, a theoretical model has been developed that describes the power of the reflected GPS signals for different time delays and Doppler frequencies as a function of geometrical and environmental parameters. The results indicate a good agreement between the measured and the modeled normalized signal power waveforms during changing surface wind conditions. The estimated wind speed using surface- reflected GPS data, obtained by comparing actual and modeled waveforms, shows good agreement (within 2 m/s) with data obtained from a nearby buoy and independent wind speed measurements derived from the TOPEX/Poseidon altimetric satellite.

Komjathy, Attila↗