Advanced techniques for improving wind direction ambiguity removal in scatterometry

Abstract

A scatterometer can be used to determine the driving wind speed and direction through the inversion of an empirical model function relating /spl sigma//sup 0/ (normalized radar cross-section) to wind speed and direction. Unfortunately, for a given value of measured /spl sigma//sup 0/, there is not a unique wind vector solution. Multiple /spl sigma//sup 0/ measurements of the same ocean area using different viewing geometries and/or polarizations can be used to reduce the number of possible wind vector solutions. The NASA Scatterometer (NSCAT) was designed and built to be launched on ADEOS. NSCAT will measure /spl sigma//sup 0/ from three different viewing geometries with one of the antennas making dual-polarization measurements. The NSCAT configuration provides additional information to assist in the selection of a wind vector solution. The process of selecting one of the wind vector solutions to represent the true wind vector is referred to as ambiguity removal or dealiasing. The ambiguity removal algorithm currently planned for NSCAT utilizes a simple median filter. From simulations, it has been determined that the median filtering technique will have an average skill of about 87.6%. The errors remaining in the wind field after ambiguity removal tend to be clustered together, span the width of the swath (600 km), and extend in the along track direction for several hundred kilometers. Errors also tend to produce sharp discontinuities in the retrieved wind field where there are no such discontinuities in the true wind field. We 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.