SEARCH · Search NASA
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Satellite wind scatterometers are microwave radar instruments designed specifically to measure near-surface wind speed and direction over the global ocean.
ERS-1 and ERS-2 scatterometer and synthetic aperture radar (SAR) data are used to monitor and track large and small scale sea ice dynamics in the Southern Ocean, and in particular in the Weddell Sea, Antarctica. Sea ice formation in the Weddell Sea regulates vertical and horizontal thermohaline circulation and influences bottom water production rates. Significant seasonal to interannual variability is observed in the sea ice drift dynamics. Coupled model simulations reproduce this variability and indicate that there is significant interannual variability in Weddelll Sea ice formation, drifts and extent on the El Nino southern oscillation (ENSO) timescale, with a period of approximately eight years. Changes in ice dynamics on these timescales regulate the amount of sea ice divergence and polynya formation. Anomalies in the timing and duration of the opening of the Ronne ice shelf polynya system are closely related to the variability in outflow of Weddell Sea bottom water measured at Joinville Island.
SeaSat-A Satellite Scatterometer (SASS) measurements of normalized radar cross section (NRCS) have been merged with high quality surface-wind fields based on in situ, to create a large data base of NRCS-wind signature data. These data are compared to the existing NRCS-wind model used by the SASS to infer winds. Falso-color maps of SASS NRCS and ocean winds from multiple orbits show important synoptic trends.
Radar scattering for geophysical discrimination and identification of terrain surfaces
Radar engineers have used several polarization combinations (HH, HV, VV, and/or VH) in the design of radar imagers and scatterometers for remote sensing research and applications. Scientists have explored their use for vegetation identification, mapping, and canopy condition assessment. In some cases, one polarization combination or another has produced good results; however, the results have not been consistent. In this paper, the use of polarized radar measurements is considered for vegetation studies on a theoretical basis to define ways of isolating parameters related to canopy structure and composition in the presence of backscattering from the underlying surface. It is found that scientists should use all three polarization combinations (VV, HH, and VH or HV) and their ratios.
A scatterometer is a radar that measures the normalized radar cross section sigma(sup 0) of the Earth's surface. Over the ocean this signal is related to the wind via the geophysical model function (GMF). The objective of wind scatterometry is to estimate the wind vector field from sigma(sup 0) measurements; however, there are many subtleties that complicate this problem-making it difficult to obtain a unique wind field estimate. Conventionally, wind estimation is split into two stages: a wind retrieval stage in which several ambiguous solutions are obtained, and an ambiguity removal stage in which ambiguities are chosen to produce an appropriate wind vector field estimate. The most common approach to wind field estimation is to grid the scatterometer swath into wind vector cells and estimate wind vector ambiguities independently for each cell. Then, field wise structure is imposed on the solution by an ambiguity selection routine. Although this approach is simple and practical, it neglects field wise structure in the retrieval step and does not account for the spatial correlation imposed by the sampling. This makes it difficult to develop a theoretically appropriate noise versus resolution trade-off using pointwise retrieval. Fieldwise structure may be imposed in the retrieval step using a model-based approach. However, this approach is generally only practical if a low order wind field model is applied, which may discard more information than is desired. Furthermore, model-based approaches do not account for the structure imposed by the sampling. A more general fieldwise approach is to estimate all the wind vectors for all the WVCs simultaneously from all the measurements. This approach can account for structure of the wind field as well as structure imposed by the sampling in the wind retrieval step. Williams and Long in 2010 developed a fieldwise retrieval method based on maximum a posteriori estimation (MAP). This MAP approach can be extended to perform a noise versus resolution trade-off, and deal with ambiguity selection. This paper extends the fieldwise MAP estimation approach and investigates both the noise versus resolution trade-off as well as ambiguity removal in the fieldwise wind retrieval step. The method is then applied to the Sea Winds scatterometer and the results are analyzed. This paper extends the fieldwise MAP estimation approach and investigates both the noise versus resolution trade-off as well as ambiguity removal in the fieldwise wind retrieval step. The method is then applied to the Sea Winds scatterometer and the results are analyzed.
The design, construction, and data collection procedures of the mobile agricultural radar sensor (MARS) x band scatterometer are described. This system is an inexpensive, highly mobile, truck mounted FM-CW radar operating at a center frequency of 10.2 GHz. The antennas, which allow for VV and VH polarizations, are configured in a side looking mode that allows for drive by data collection. This configuration shortens fieldwork time considerably while increasing statistical confidence in the data. Both internal calibration, via a delay line, and external calibration with a Luneberg lens are used to calibrate the instrument in terms of sigma(o). The radar scattering cross section per unit area, sigma(o), is found using the radar equation.
Skylab II S193 scatterometer data for the passes of June 5, 1973, over the Gulf of Mexico and June 6, 1973, over Pacific Hurricane AVA were analyzed. These two passes were chosen since it was possible to correlate the scattering data with simultaneous measurements of the local ocean wind conditions. The S193 scatterometer measured the radar cross section of the ocean at 13.9 GHz (Ku-band) as a function of incidence angle. The S193 data of June 5, 1973, when a practically uniform wind field was present, show reasonable agreement with the Naval Research Laboratory (NRL) empirical and theoretical models. The data of June 6, 1973, are more complex, due to rapid variations in wind speeds and directions around Hurricane AVA. The NRL empirical model was interpolated to account for variation in wind heading relative to the S193 antenna pointing direction; a reasonable comparison could then be made with the corresponding S193 data of June 6, 1973.
The paper describes how user requirements were integrated into the development of the Seasat-A program and shows how user requirements influenced sensor selection, mission planning, satellite systems design, and the end-to-end data system. User requirements included the measurement of ocean topography, surface winds, gravity waves, surface temperature, sea ice, salinity, and surface pressure. Particular attention is paid to the selection of sensors: compressed pulse radar altimeter, synthetic aperture imaging radar, microwave wind scatterometer, visible/infrared radiometer, and multispectral microwave radiometer.
Mission details, onboard equipment, and measurements to be taken are described for the Seasat-A global ocean monitoring satellite. The satellite is designed for mapping the global ocean geoid, charting ice fields and leads, precision measurement of sea surface topography, global monitoring of wave height and wave directional spectra, surface winds and wind direction, current patterns, and ocean temperature. Data handling subsystems, a compressed pulse radar altimeter, coherent synthetic aperture imaging radar, microwave wind scatterometer, scanning visible/IR radiometer, scanning multispectral (5 freq) microwave radiometer mounted on the satellite are described briefly.
A microwave remote sensing program of sea ice in the Beaufort Sea was conducted during the Arctic Ice Dynamics Joint Experiment (AIDJEX). Several types of both passive and active sensors were used to perform surface and aircraft measurements during all seasons of the year. In situ observations were made of physical properties (salinity, temperature, density, surface roughness), dielectric properties, and passive microwave measurements were made of first-year, multiyear, and first-year/multiyear mixtures. Airborne passive microwave measurements were performed with the electronically scanning microwave radiometer while airborne active microwave measurements were performed by synthetic aperture radar, X- and L-band radar, and a scatterometer.
The experimental Seasat-A satellite, scheduled for launch in 1978, is designed to provide measurements of sea-surface temperature, surface wind speed and direction, sea state and directional wave spectra. The instrument package of the satellite includes a highly precise radar altimeter, a wind-field scatterometer, a synthetic-aperture imaging radar, a scanning multifrequency microwave radiometer and a radiometer operating in the visual and infrared. Tides, currents and storm surges on the marine geoid may be monitored through analysis of range information from the radar altimeter and a satellite ephemeris; sea-ice reconnaissance is also planned.
It is pointed out that oceanographers have benefited from the space program mainly through the increased efficiency it has brought to ship operations. For example, the Transit navigation system has enabled oceanographers to compile detailed maps of sea-floor properties and to more accurately locate moored subsurface instrumentation. General descriptions are given of instruments used in satellite observations (altimeter, color scanner, infrared radiometer, microwave radiometer, scatterometer, synthetic aperture radar). It is pointed out that because of the large volume of data that satellite instruments generate, the development of algorithms for converting the data into a form expressed in geophysical units has become especially important.
The background and development of the Seasat commercial demonstration program are reviewed and the Seasat spacecraft and its sensors (altimeter, wind field scatterometer, synthetic aperture radar, and scanning multichannel microwave radiometer) are described. The satellite data distribution system allows for selected sets of data, reformatted or tailored to specific needs and geographical regions, to be available to commercial users. Products include sea level and upper atmospheric pressure, sea surface temperature, marine winds, significant wave heights, primary wave direction and period, and spectral wave data. The results of a set of retrospective case studies performed for the commercial demonstration program are described. These are in areas of application such as marine weather and ocean condition forecasting, offshore resource exploration and development, commercial fishing, and marine transportation.
Nonlinearities within a synthetic aperture radar (SAR) present significant obstacles to the calibration of the output imagery. The problem of calibrating a SAR is considerably more involved than that of calibrating a real aperture radar (RAR) or scatterometer, since the SAR relies heavily on the principle of superposition, which fails in nonlinear systems. It is shown in this paper that non-linearities can distort SAR imagery to such an extent that two areas of equal backscatter on the ground can be imaged to have significantly different intensities in the image.
It has recently been demonstrated that the GPS signal which has reflected from the ocean surface contains useful geophysical data from which the sea surface wind speed and other parameters can be extracted. This can be used for remote sensing, similar to present day use of radar altimeters or scatterometers, but with significantly smaller instrumentation because of the utilization of the existing GPS broadcast signal for illumination. Several campaigns of aircraft experimentation have been completed demonstrating this technique and reflected GPS data has been reliably collected from 25 km altitude on a balloon. However, there has not yet been a demonstration that the reflected GPS signal can be detected from orbit with sufficient signal to noise ratio (SNR) to make useful remote sensing measurements. A technology demonstration experiment is planned for a Space Shuttle flight in the late 2000 using the Spartan 251 recoverable carrier. This experiment will be also be the first flight validation of the PiVoT GPS receiver developed in house at the Goddard Space Flight Center. The open-architecture, design of this receiver allows the software modifications to be made which control code-correlator spacing to map out the shape of the reflected signal waveform, which is the most basic data product generated by this instrumentation. A moderate gain left-hand circularly polarized antenna, constructed from an array of off-the-shelf hemispherical antennas will be used to give approximately 6dB of additional gain. Preliminary SNR predictions have been done indicating that this antenna will offer sufficient gain to record waveform measurements. A system level description of the experiment instrumentation, including the receiver, antenna and data storage and retrieval will be given. The visibility of GPS reflections over the mission duration of several hours will be studied, including the effects of the limited beamwidth of the antenna. Additionally, because of the small size of this instrumentation, several other space flight opportunities are being considered in the near term. If these missions materialize, they will be described in the paper as well.
It has recently been demonstrated that the GPS signal which has reflected from the ocean surface contains useful geophysical data from which the sea surface wind speed and other parameters can be extracted. This can be used for remote sensing, similar to present day use of radar altimeters or scatterometers, but with significantly smaller instrumentation because of the utilization of the existing GPS broadcast signal for illumination. Several campaigns of aircraft experimentation have been completed demonstrating this technique and reflected GPS data has been reliably collected from 25 km altitude on a balloon. However, there has not yet been a demonstration that the reflected GPS signal can be detected from orbit with sufficient signal to noise ratio (SNR) to make useful remote sensing measurements. A technology demonstration experiment was planned for a Space Shuttle flight in the late 2000 using the Spartan 251 recoverable carrier. This experiment would also have been the first flight validation of the PiVoT GPS receiver developed in house at the Goddard Space Flight Center. The "open-architecture" design of this receiver would allow the software modifications to be made which control code-correlator spacing to map out the shape of the reflected signal waveform, which is the most basic data product generated by this instrumentation. A moderate gain left-hand circularly polarized antenna, constructed from an array of off-the-shelf hemispherical antennas was to be used to give approximately 3 to 6 dB of additional gain. Preliminary SNR predictions have been done indicating that this antenna would offer sufficient gain to record waveform measurements. A system level description of the experiment instrumentation, including the receiver, antenna and data storage and retrieval will be given. The visibility of GPS reflections over the mission duration of several hours will be studied, including the effects of the limited beamwidth of the antenna. Spartan 251 has now been postponed with the earliest opportunity in the year 2002. The results of this study however, have been 2 used to further the define the requirements and expected performance of reflected GPS receivers in orbit. Several other space flight opportunities are being considered based upon this new information.
The key observational tools for detecting large scale changes of various parameters in the polar regions have been satellite sensors. The sensors include passive and active satellite systems in the visible, infrared and microwave frequencies. The monitoring started with Tiros and Nimbus research satellites series in the 1970s but during the period, not much data was stored digitally because of limitations and cost of the needed storage systems. Continuous global data came about starting with the launch of ocean color, passive microwave, and thermal infrared sensors on board Nimbus-7 and Synthetic Aperture Radar, Radar Altimeter and Scatterometer on board SeaSat satellite both launched in 1978. The Nimbus-7 lasted longer than expected and provided about 9 years of useful data while SeaSat quit working after 3 months but provided very useful data that became the baseline for follow-up systems with similar capabilities. Over the years, many new sensors were launched, some from Japan Aeronautics and Space Agency (JAXA), some from the European Space Agency (ESA) and more recently, from RuSSia, China, Korea, Canada and India. For polar studies, among the most useful sensors has been the passive microwave sensor which provides day/night and almost all weather observation of the surface. The sensor provide sea surface temperature, precipitation, wind, water vapor and sea ice concentration data that have been very useful in monitoring the climate of the region. More than 30 years of such data are now available, starting with the Scanning Multichannel Microwave Radiometer (SMMR) on board the Nimbus-7, the Special Scanning Microwave/Imager (SSM/I) on board a Defense Meteorological Satellite Program (DMSP) and the Advanced Microwave Scanning Radiometer on board the EOS/ Aqua satellite. The techniques that have been developed to derive geophysical parameters from data provided by these and other sensors and associated instrumental and algorithm errors and validation techniques will be discussed. An important issue is the organization and storage of hundreds of terabytes of data collected by even just a few of these satellite sensors. Advances in mass storage and computer technology have made it possible to overcome many of the collection and archival problems and the availability of comprehensive satellite data sets put together by NASA's Earth Observing System project will be discussed.