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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Measurement of oceanic wind vector using satellite microwave radiometers

A feasibility study of deriving both a wind speed and direction from microwave radiometer measurements of the ocean is presented. The study was based on the Special Sensor Microwave/Imager (SSM/I) measurements in conjunction with buoy reports from the National Data Buoy Center. It was found that the SSM/I minus the buoy wind speed difference is correlated with wind direction due to a wind direction signal in the brightness temperatures. When this wind direction signal is removed the rms difference between the SSM/I and buoy winds reduces to 1.3 m/s. The wind direction signal was used to make global, low-resolution maps of the monthly mean oceanic wind vector.

Wentz, Frank J.↗
NASA NTRS1978

Central swath mapping by a future satellite-borne fan-beam microwave scatterometer for inferring global ocean wind fields

The Seasat-A satellite scatterometer is a microwave sensor designed to provide a capability for mapping the global ocean surface wind speed and direction. Four fan beams whose major axes are oriented at + or - 45 deg and + or - 135 deg to the flight vector cover a swath width of 1900 km, but a central region remains that is inadequately mapped. In this paper, two additional fan beams for a future scatterometer are suggested which provide more complete coverage of the central region.

Tomiyasu, K.↗
NASA NTRS1984

Ocean wind field measurement performance of the ERS-1 scatterometer

The Active Microwave Instrumentation (AMI), which will be implemented on the ERS-1, is a 5.3 GHz multipurpose radar for land surface imaging, ocean wave spectrum measurement and wind observations over oceans. The imaging and wave measurements apply Synthetic Aperture Radar (SAR) techniques, while wind field detection is performed by the Scatterometer as part of the AMI. The Scatterometer system design was developed and optimized with the aid of a performance simulator. This paper, aimed at giving an overview, is presented about the: (1) ERS-1 Scatterometer system design; (2) Error budget; and the (3) Overall calibration concept.

Hans, P.↗
NASA NTRS2006

Polarimetric Microwave Remote Sensing of Hurricane Ocean Winds

We presented the analysis of Windsat data for hurricanes Isabel and Fabian in 2003. The polarimetric third and fourth Stokes parameter observations from the Windsat 10, 18 and 37 GHz channels were collocated with the ocean surface winds from the Holland wind model, the QuikSCAT wind vectors and the Global Data Assimilation System (GDAS) operated by the National Center for Environmental Prediction (NCEP). The collocated data were binned as a function of wind speed and wind direction, and were expanded by sinusoidal series of the relative azimuth angles between wind and observation directions. The coefficients of the sinusoidal series, corrected for atmospheric attenuation, have been used to develop an empirical geophysical model function (GMF). The Windsat GMF for extreme high wind compares very well with the aircraft radiometer and radar measurements.

widebands↗
NASA NTRS1984

NROSS scatterometer - An instrument for global oceanic wind observations

One of the instruments - the NROSS scatterometer or SCATT - to be launched on the Navy Remote Ocean Sensing System spacecraft in 1989 is discussed. To determine wind speed and direction that SCATT will measure the ocean normalized radar cross section (NRCS) by illuminating the ocean's surface with microwave pulses and measuring the return signal power. A wind retrieval algorithm is used to compute the wind speed and direction from the measured NRCS. Winds over at least 90 percent of the global, ice-free ocean will be observed at least once every two days. For NASA users, the system will retrieve winds with an accuracy of plus or minus 2 m/s or 10 percent whichever is greater, for wind speeds ranging from 3 to 30 m/s.

Li, F.↗
NASA NTRS1985

Large space antenna technology applied to radar-imaging, rain-rate measurements, and ocean wind sensing

During the last decade, the utility of spaceborne microwave remote sensing systems for ocean windspeed measurement, ocean wave imaging and sea ice studies was demonstrated. Development of large space antennas offers some interesting possibilities for rain rate measurements, ocean and ice studies, and radar imaging. The joint use of active and passive sensors using the 15 m antenna for ocean, ice, and soil moisture studies; rain rate measurements; and radar imaging is considered. Verification of the frequency agile rain radar concept with Shuttle offers the possibility of much needed rain rate statistics over the ocean.

Moore, R. K.↗
NASA NTRS2010

Ocean Winds and Turbulent Air-Sea Fluxes Inferred From Remote Sensing

Air-sea turbulent fluxes determine the exchange of momentum, heat, freshwater, and gas between the atmosphere and ocean. These exchange processes are critical to a broad range of research questions spanning length scales from meters to thousands of kilometers and time scales from hours to decades. Examples are discussed (section 2). The estimation of surface turbulent fluxes from satellite is challenging and fraught with considerable errors (section 3); however, recent developments in retrievals (section 3) will greatly reduce these errors. Goals for the future observing system are summarized in section 4. Surface fluxes are defined as the rate per unit area at which something (e.g., momentum, energy, moisture, or CO Z ) is transferred across the air/sea interface. Wind- and buoyancy-driven surface fluxes are called surface turbulent fluxes because the mixing and transport are due to turbulence. Examples of nonturbulent processes are radiative fluxes (e.g., solar radiation) and precipitation (Schmitt et al., 2010). Turbulent fluxes are strongly dependent on wind speed; therefore, observations of wind speed are critical for the calculation of all turbulent surface fluxes. Wind stress, the vertical transport of horizontal momentum, also depends on wind direction. Stress is very important for many ocean processes, including upper ocean currents (Dohan and Maximenko, 2010) and deep ocean currents (Lee et al., 2010). On short time scales, this horizontal transport is usually small compared to surface fluxes. For long-term processes, transport can be very important but again is usually small compared to surface fluxes.

Bourassa, Mark A.↗
NASA NTRS2000

Microwave Sensing of Ocean Winds Including the Use of SAR Imagery

This paper presents aircraft measurements of near-surface atmospheric boundary layer wind roll signatures and radar-derived sea surface roughness. These data are completely coincident in space and time and this unique feature supports attempts to definitively link SAR backscatter signatures to boundary layer roll impacts. The open-ocean data were collected at an altitude of 20 m from NOAA's Long-EZ aircraft using its turbulence probe and down-looking Ka-band radar scatterometer. Several flight legs of 20-30 km were flown with a heading across the wind direction, which is also roughly perpendicular to the roll vortices. We find remarkable correlation between measured modulations in the along-wind component of wind speed and radar backscatter for the spatial scale of 1 to 1.5 km. Close agreement between normalized modulation amplitudes suggests the radar-inferred surface slope variance is changing linearly with wind speed. These data were collected within 30 minutes of a RADARSAT SAR overpass where apparent boundary layer impacts of the same orientation and spatial dimension are prevalent in the SAR backscatter image. Quantitative comparison between modulations in the aircraft and satellite radar data will be discussed.

Vandemark, Douglas↗
NASA NTRS1993

ERS-1 and Seasat scatterometer measurements of ocean winds: Model functions and the directional distribution of short waves

Calculation of accurate vector winds from scatterometers requires knowledge of the relationship between backscatter cross-section and the geophysical variable of interest. As the detailed dynamics of wind generation of centimetric waves and radar-sea surface scattering at moderate incidence angles are not well known, empirical scatterometer model functions relating backscatter to winds must be developed. Less well appreciated is the fact that, given an accurate model function and some knowledge of the dominant scattering mechanisms, significant information on the amplitudes and directional distributions of centimetric roughness elements on the sea surface can be inferred. accurate scatterometer model functions can thus be used to investigate wind generation of short waves under realistic conditions. The present investigation involves developing an empirical model function for the C-band (5.3 GHz) ERS-1 scatterometer and comparing Ku-band model functions with the C-band model to infer information on the two-dimensional spectrum of centimetric roughness elements in the ocean. The C-band model function development is based on collocations of global backscatter measurements with operational surface analyses produced by meteorological agencies. Strengths and limitations of the method are discussed, and the resulting model function is validated in part through comparison with the actual distributions of backscatter cross-section triplets. Details of the directional modulation as well as the wind speed sensitivity at C-band are investigated. Analysis of persistent outliers in the data is used to infer the magnitudes of non-wind effects (such as atmospheric stratification, swell, etc.). The ERS-1 C-band instrument and the Seasat Ku-band (14.6 GHz) scatterometer both imaged waves of approximately 3.4 cm wavelength assuming that Bragg scattering is the dominant mechanism. Comparisons of the C-band and Ku-band model functions are used both to test the validity of the postulated Bragg mechanism and to investigate the directional distribution of the imaged waves under a variety of conditions where Bragg scatter is dominant.

Freilich, Michael H.↗
NASA NTRS1981

The study of mesoscale ocean winds

SAR data gathered over the U.S. East Coast are used to infer near-surface wind speed, using a simplified model to relate the strength of the 30 to 40 cm SAR backscatter to surface wind speed. It is found that the SAR backscatter is nearly isotropic with a wind speed exponent of 0.4. Using this exponent, the model is tested against an independent data set. Subsequent agreement between wind speeds simultaneously determined by SAR and the Seasat-A Satellite Scatterometer (SASS) is within 0.7 m/s rms. A one-dimensional Fourier transform of the SAR-derived wind field shows an increasing energy content in rough agreement with the Van der Hoven spectrum.

Jones, W. L.↗
NASA NTRS1984

New algorithms for microwave measurements of ocean winds

Improved second generation wind algorithms are used to process the three month SEASAT SMMR and SASS data sets. The new algorithms are derived without using in situ anemometer measurements. All known biases in the sensors prime measurements are removed, and the algorithms prime model functions are internally self-consistent. The computed SMMR and SASS winds are collocated and compared on a 150 km cell-by-cell basis, giving a total of 115444 wind comparisons. The comparisons are done using three different sets of SMMR channels. When the 6.6H SMMR channel is used for wind retrieval, the SMMR and SASS winds agree to within 1.3 m/s over the SASS primary swath. At nadir where the radar cross section is less sensitive to wind, the agreement degrades to 1.9 m/s. The agreement is very good for winds from 0 to 15 m/s. Above 15 m/s, the off-nadir SASS winds are consistently lower than the SMMR winds, while at nadir the high SASS winds are greater than SMMR's. When 10.7H is used for the SMMR wind channel, the SMMR/SASS wind comparisons are not quite as good. When the frequency of the wind channel is increased to 18 GHz, the SMMR/SASS agreement substantially degrades to about 5 m/s.

Wentz, F. J.↗
NASA NTRS1986

New algorithms for microwave measurements of ocean winds Applications to Seasat and the special sensor microwave imager

Improved second generation wind algorithms are used to process the three month Seasat SMMR and SASS data sets. The new algorithms are derived without using in situ anemometer measurements. All known biases in the sensors prime measurements are removed, and the algorithms prime model functions are internally self-consistent. The computed SMMR and SASS winds are collocated and compared on a 10 km cell-by-cell basis, giving a total of 115444 wind comparisons. The comparisons are done using three different sets of SMMR channels. When the 6.6H SMMR channel is used for wind retrieval, the SMMR and SASS winds agree to within 1.3 m/s over the SASS primary swath. At nadir where the radar cross section is less sensitive to wind, the agreement degrades to 1.9 m/s. The agreement is very good for winds from 0 to 15 m/s. Above 15 m/s, the off-nadir SASS winds are consistently lower than the SMMR winds, while at nadir the high SASS winds are greater than SMMR's. When 10.7H is used for the SMMR wind channel, the SMMR/SASS wind comparisons are not quite as good. When the frequency of the wind channel is increased to 18 GHz, the SMMR/SASS agreement substantially degrades to about 5 m/S.

Wentz, F. J.↗