A quality assurance algorithm for NASA Scatterometer ambiguity removal

Abstract

The recently launched NASA Scatterometer (NSCAT) estimates the wind speed and direction of near-surface ocean wind. This is done by directing microwaves toward the Earth's surface and measuring the backscattered radiation. From this, several possible wind vectors are identified for each point over the swath. The correct wind must be distinguished from these in a step called ambiguity removal. Unfortunately, ambiguity removal algorithms are subject to error. Because the true wind is not known, where these errors occur is difficult to determine, and there is little information in the measurements alone to detect the errors in this removal step. The authors have developed a method to assess the accuracy of the ambiguity removal algorithm by comparing the point-wise retrieved wind to winds inferred with a wind field model. The performance of the algorithm achieves its goal to identify at least 95% of regions containing ambiguity removal-errors. The algorithm provides a very simple tool to indicate regions of possible ambiguity removal errors in the point-wise retrieved winds for NSCAT data. This paper describes this algorithm and its performance for real NSCAT data.