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West, Richard D.

Publications and source records attributed to West, Richard D..

Cassini RADAR Observations of Enceladus, Tethys, Dione, Rhea, Iapetus, Hyperion, and Phoebe

The Cassini mission includes 34 investigations of Saturn's icy satellites by the 2.2-cm-wavelength (13.8-GHz) RADAR instrument, operating both as a scatterometric radar and a passive radiometer. These measurements are sensitive to near-surface electrical properties and structure at scales about six times smaller than the only groundbased radar wavelength available to study the satellites (13 cm) and 22 times longer than the millimeter wavelengths at the limit of Cassini's Composite Infrared Spectrometer (CIRS). Here we present Cassini's first radar results for seven of the satellites.

Saturn↗

Ground processing of Cassini RADAR imagery of Titan

This paper describes the ground processing of Cassini SAR data. We focus upon the unusual features of the data and how these features impact the processing. We exhibit a data dependent mechanism we have implemented for eliminating artifacts due to attitude and ephemeris knowledge error. Finally we describe how we trade-off SAR performance vs. area of coverage when we design our spacecraft pointing profiles.

remote sensing↗

Potential Applications of Satellite Based Low Frequency Microwave Measurements of Snow and Ice

In this presentation we will examine some potential applications of low frequency microwave radar and radiometer data to remote sensing of snow and ice conditions over land. We focus on the following low frequency bands; L-band (1.28 GHz), S-band (2.69 GHz), and C-band (5.0 GHz). To predict the effect of snow cover on microwave emission, we need to characterize the dielectric properties of the snow in terms of important physical parameters such as snow density, temperature, and wetness. For the case of dry snow, we use an empirical mixing formula which gives the effective complex permittivity of snow as a function of density, temperature, and frequency. For wet snow, we use another mixing formula which gives the effective complex permittivity as a function of snow wetness. With dry snow, the loss at low microwave frequencies is very small so the corresponding penetration depths are very large (eg., 100 m). Clearly seasonal snow covers are far too thin to have a direct scattering or emission effect on these low frequency bands. There are, however, indirect effects introduced because of altered reflection at the snow/soil boundary, and an extra reflecting interface at the snow/air boundary. For C-band, layers of snow with different densities can have an impact if the number of layers grows sufficiently large. (eg., many meters of snow pack with cm-scale density layering.) Wet snow poses a more difficult problem. Liquid water is much more effective than ice at scattering and absorbing L-band radiation, so even a small amount of wetness will greatly reduce penetration. For example, with a snow wetness of 1 percent (volume fraction), and a density of 300 kg/cu. m, the penetration depths for L-band, S-band, and C-band are about 1.6 m, 0.3 m, and 0.15 m respectively. Very wet snow has more than 10 percent liquid water, and the corresponding L-band penetration is less than 0.2 m. Because the penetration distance is a strong function of frequency, it may be possible to identify a particular class of snow where the wetness is a few percent, and the depth is around one meter by looking at the frequency gradient.

West, Richard D.↗

Advanced Techniques for Improving Wind Direction Ambiguity Removal in Scatterometry

The ambiguity removal algorithm currently planned for NSCAT utilizes a simple median filter?? will discuss techniques of ambiguity removal and outline two new algorithms which can be used to improve ambiguity removal performance without the inclusion of additional wind field information. The techniques are applied to simulated NSCAT data but can be generalized to other scatterometer instruments such as the ERS-1 and ERS-2 scatterometers, and Sea Winds to be launched aboard ADEOS-II in 1999.

ambiguity↗