Location
University of Utah
Start Date
6-19-1998 12:00 AM
Description
A wind field model can be used to evaluate the accuracy of pointwise ambiguity removal for NASA Scatterometer (NSCAT) data. Errors in pointwise ambiguity removal result in large model-fit errors when the pointwise wind estimates are assimilated into the model. By thresholding the error, regions containing ambiguity removal error can be identified. For these regions, the ambiguity selection can be improved using the model-fit field. I have developed a new automated algorithm for evaluating the quality of the pointwise ambiguity selection and for correcting the ambiguity selection. This paper presents this correction algorithm, which is generally applicable to other scatterometers, and the results for NSCAT data.
An Algorithm to Assess the Accuracy of NSCAT Ambiguity Removal
University of Utah
A wind field model can be used to evaluate the accuracy of pointwise ambiguity removal for NASA Scatterometer (NSCAT) data. Errors in pointwise ambiguity removal result in large model-fit errors when the pointwise wind estimates are assimilated into the model. By thresholding the error, regions containing ambiguity removal error can be identified. For these regions, the ambiguity selection can be improved using the model-fit field. I have developed a new automated algorithm for evaluating the quality of the pointwise ambiguity selection and for correcting the ambiguity selection. This paper presents this correction algorithm, which is generally applicable to other scatterometers, and the results for NSCAT data.