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NASA NTRS2000

Comparison Between Sea Surface Wind Speed Estimates From Reflected GPS Signals and Buoy Measurements

Reflected signals from the Global Positioning System (GPS) have been collected from an aircraft at approximately 3.7 km altitude on 5 different days. Estimation of surface wind speed by matching the shape of the reflected signal correlation function against analytical models was demonstrated. Wind speed obtained from this method agreed with that recorded from buoys to with a bias of less than 0.1 m/s, and with a standard derivation of 1.3 meters per second.

Garrison, James L.↗

NASA NTRS1978

Correlation of sigma deg (0 deg) inferred wind speed estimates with NOAA hindcast data

Microwave remote sensing is discussed in terms of using GEOS-3 data to infer surface wind speed. Topics covered include: determining surface wind speed from backscattering, estimating surface winds from near normal incidence scattering, and response of the centimeter wavelength components of the ocean surface height spectrum to the wind.

Brown, G. S.↗

NASA NTRS1985

A review of satellite altimeter measurement of sea surface wind speed - With a proposed new algorithm

The scheduled February 1985 launch of a radar altimeter aboard the U.S. Navy satellite Geosat has motivated an in-depth investigation of wind speed retrieval from satellite altimeters. The accuracy of sea surface wind speed estimated by the Seasat altimeter is examined by comparison with wind speed estimated by the Seasat scatterometer. The intercomparison is based on globally distributed spatial and temporal averages of the estimated wind speed. It is shown that there are systematic differences between altimeter and scatterometer wind speed estimates. These differences are traced to errors in the Seasat altimeter geophysical data record wind speed algorithm. A new algorithm is proposed which yields consistent estimates from the two satellite sensors. Using this new algorithm, the rms difference between spatial and temporal averages of the two wind speed estimates is less than 1 m/s, and their correlation is greater than 0.9.

Chelton, D. B.↗

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

Mognard, Nelly M.↗

NASA NTRS1997

Friction Velocity Estimation Using Dual-Frequency Altimeter Data

Global estimation of wind speeds near the sea-surface can be obtained using normalized radar cross sections sigma(o) from satellite-borne single-frequency altimeters. Indeed recent validation studies of Geosat altimeter-derived wind speeds show that several often cited semiempirical algorithms yield linear trends between wind-speeds from altimeter data and wind speeds from (a) ships of opportunity (Etcheto 1992), (b) buoys (Carter 1992), and (c) atmospheric models (Guillaume 1992). Although the linear trends are striking, there is considerable scatter since the range of standard deviations is from 1.5 to 3 m/s. In fact, the scatter of some particular measurements about the regressions is striking because they depart from the 'standard' by as much as +/- 5 m/s, which is large - even for full gale winds of 20 m/s. These anomalies can cause serious problems for gas exchange, heat, and aerosol estimates. They can also induce considerable errors in wind-driven oceanic circulation models and sea-surface wave models. This paper explores the possibility of improving the accuracy of wind speed estimation using dual-frequency altimeters.

Bliven, Larry F.↗

NASA NTRS1993

Determining torques over the ocean and their role in the planetary momentum budget

The transfer of angular momentum between the atmosphere and oceans was examined using a surface wind data set. The data set combines special sensor microwave imager wind speed estimates and operational wind analyses from the European Centre for Medium Range Weather Forecasts for estimation of zonal torques over the global ocean from July 1987 to June 1989. An attempt was made to determine the global space-time structure of ocean torques. The wind data sets are described, the general statistics of local and global torques are presented, and their characteristics were evaluated. Consideration is given to the impact of satellite data on the calculation of local and global torques. The contribution of ocean torques to fluctuations in atmospheric angular momentum was analyzed as a function of time scale and geographical location.

Ponte, Rui M.↗

NASA NTRS1991

An atlas of monthly mean distributions of GEOSAT sea surface height, SSMI surface wind speed, AVHRR/2 sea surface temperature, and ECMWF surface wind components during 1988

Monthly mean global distributions for 1988 are presented with a common color scale and geographical map. Distributions are included for sea surface height variation estimated from GEOSAT; surface wind speed estimated from the Special Sensor Microwave Imager on the Defense Meteorological Satellite Program spacecraft; sea surface temperature estimated from the Advanced Very High Resolution Radiometer on NOAA spacecrafts; and the Cartesian components of the 10m height wind vector computed by the European Center for Medium Range Weather Forecasting. Charts of monthly mean value, sampling distribution, and standard deviation value are displayed. Annual mean distributions are displayed.

Halpern, D.↗

NASA NTRS1983

Errors in scatterometer-radiometer wind measurement due to rain

The behavior of radiometer corrections for the scatterometer is investigated by simulating simple situations using footprint sizes comparable with those used in the SEASAT-1 experiment and also actual footprints and rain rates from a hurricane observed by the SEASAT-1 system. The effects on correction due to attenuation and wind speed gradients are examined independently and jointly. It is shown that the error in the wind-speed estimate can be as large as 200% at higher wind speeds. The worst error occurs when the scatterometer footprint overlaps two or more radiometer footprints and the attenuation in the scatterometer footprint differs greatly from those in parts of the radiometer footprints. This problem could be overcome by using a true radiometer-scatterometer system having identical coincident footprints comparable in size with typical rain cells.

Moore, R. K.↗

NASA NTRS1995

An atlas of monthly mean distributions of SSMI surface wind speed, AVHRR/2 sea surface temperature, AMI surface wind velocity, TOPEX/POSEIDON sea surface height, and ECMWF surface wind velocity during 1993

The following monthly mean global distributions for 1993 are presented with a common color scale and geographical map: 10-m height wind speed estimated from the Special Sensor Microwave Imager (SSMI) on a United States (U.S.) Air Force Defense Meteorological Satellite Program (DMSP) spacecraft; sea surface temperature estimated from the Advanced Very High Resolution Radiometer (AVHRR/2) on a U.S. National Oceanic and Atmospheric Administration (NOAA) satellite; 10-m height wind speed and direction estimated from the Active Microwave Instrument (AMI) on the European Space Agency (ESA) European Remote Sensing (ERS-1) satellite; sea surface height estimated from the joint U.S.-France Topography Experiment (TOPEX)/POSEIDON spacecraft; and 10-m height wind speed and direction produced by the European Center for Medium-Range Weather Forecasting (ECMWF). Charts of annual mean, monthly mean, and sampling distributions are displayed.

Halpern, D.↗

NASA NTRS1986

Time dependent wind fields

Two tasks were performed: (1) determination of the accuracy of Seasat scatterometer, altimeter, and scanning multichannel microwave radiometer measurements of wind speed; and (2) application of Seasat altimeter measurements of sea level to study the spatial and temporal variability of geostrophic flow in the Antarctic Circumpolar Current. The results of the first task have identified systematic errors in wind speeds estimated by all three satellite sensors. However, in all cases the errors are correctable and corrected wind speeds agree between the three sensors to better than 1 ms sup -1 in 96-day 2 deg. latitude by 6 deg. longitude averages. The second task has resulted in development of a new technique for using altimeter sea level measurements to study the temporal variability of large scale sea level variations. Application of the technique to the Antarctic Circumpolar Current yielded new information about the ocean circulation in this region of the ocean that is poorly sampled by conventional ship-based measurements.

Chelton, D. B.↗

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 NTRS2000

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↗

NASA NTRS1989

Probabilities and statistics for backscatter estimates obtained by a scatterometer

Methods for the recovery of winds near the surface of the ocean from measurements of the normalized radar backscattering cross section must recognize and make use of the statistics (i.e., the sampling variability) of the backscatter measurements. Radar backscatter values from a scatterometer are random variables with expected values given by a model. A model relates backscatter to properties of the waves on the ocean, which are in turn generated by the winds in the atmospheric marine boundary layer. The effective wind speed and direction at a known height for a neutrally stratified atmosphere are the values to be recovered from the model. The probability density function for the backscatter values is a normal probability distribution with the notable feature that the variance is a known function of the expected value. The sources of signal variability, the effects of this variability on the wind speed estimation, and criteria for the acceptance or rejection of models are discussed. A modified maximum likelihood method for estimating wind vectors is described. Ways to make corrections for the kinds of errors found for the Seasat SASS model function are described, and applications to a new scatterometer are given.

Pierson, Willard J., Jr.↗

NASA NTRS1980

Catalog of sea state and wind speed in the South Atlantic Bight

The GEOS 3 significant waveheight and ground wind speed estimation algorithms are derived and then applied to all GEOS 3 data in the South Atlantic Bight. The investigation area is divided into five geographical sectors and significant waveheight and wind speed histograms are presented in each sector by month and by season. In the discussion of the histograms, definite seasonal trends are identified and examined.

Mcmillan, J. D.↗

NASA NTRS1972

Wind speeds in lower atmosphere of Venus: Status report on possible measurement via differential VLBI tracking of entry probes

The potential of very-long-baseline interferometry (VLBI) is examined for use in the determination of wind speeds in Venus' lower atmosphere via the differential tracking of entry probes. A simplified mathematical model is presented in detail. An incomplete error analysis based on this model permits an educated guess to be made: an uncertainty in wind speed determination of no more than about 100/t m/sec, where t l is the corresponding time resolution in seconds, is an achievable goal, without the use of transponders on the miniprobes. If transponders are available on all probes, there should be little difficulty in estimating wind speeds with useful precision.

Shapiro, I. I.↗

NASA NTRS1976

Estimates of the wind speeds required for particle motion on Mars

Threshold wind speeds for setting particles into motion on Mars are estimated by evaluating experimentally observed threshold friction velocities and determining the ratio of this velocity to the threshold wind speed at the top of earth's atmospheric boundary layer (ABL). Turning angles between the direction of the wind at the top of the ABL and the wind stress at the surface are also estimated. Detailed consideration is given to the dependence of the threshold wind speed at the top of the ABL on particle diameter, surface pressure, air temperature, atmospheric stability and composition, surface roughness, and interparticle cohesion. The results are applied to interpret a number of phenomena that have been observed on Mars and are attributable to aeolian processes. It is shown that: (1) minimum threshold wind speeds of about 50 to 100 m/sec are required to cause particle motion on Mars under 'favorable' conditions; (2) particle motion should be infrequent and strongly correlated with proximity to small topographical features; (3) in general, particle motion occurs more readily at night than during the day, in winter polar areas than equatorial areas around noon, and for H2O or CO2 ice particles than for silicate particles; and (4) the boundary between saltating and suspendible particles is located at a particle diameter of about 100 microns.

Pollack, J. B.↗

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↗