Wind measurement accuracy for the NASA scatterometer

David G. Long; Travis Oliphant

doi:10.1117/12.278915

18 September 1997 Wind measurement accuracy for the NASA scatterometer

David G. Long, Travis Oliphant

Proceedings Volume 3117, Earth Observing Systems II; (1997) https://doi.org/10.1117/12.278915
Event: Optical Science, Engineering and Instrumentation '97, 1997, San Diego, CA, United States

Abstract

The NASA Scatterometer (NSCAT) is designed to make measurements of the normalized radar backscatter coefficient ((sigma) ^o) of the ocean's surface. The measured (sigma) ^o is a function of the viewing geometry and the surface roughness due to wind-generated waves. By making multiple measurements of the same location from different azimuth angles it is possible to retrieve the near-surface wind speed and direction with the aid of a Geophysical Model Function (GMF) which relates wind and (sigma) ^o. The wind is estimated from the noisy (sigma) ^o measurements using maximum likelihood techniques. The probability density of the measured (sigma) ^o is assumed to be Gaussian with a variance that depends on the true (sigma) ^o and therefore the wind through the GMF and the measurements from different azimuth angles are assumed independent in estimating the wind. In order to estimate the accuracy of the retrieved wind, we derive the Cramer-Reo (CR) bound for wind estimation from scatterometer measurements. We show that the CR bound can be used as an error bar on the estimated wind. The role of geophysical modeling error in the GMF is considered and shown to play a significant role in the wind accuracy. Estimates of the accuracy of NSCAT measurements are given along with other scatterometer geometries and types.

Citation Download Citation

David G. Long and Travis Oliphant "Wind measurement accuracy for the NASA scatterometer", Proc. SPIE 3117, Earth Observing Systems II, (18 September 1997); https://doi.org/10.1117/12.278915

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KEYWORDS

Wind measurement

Radar

Statistical analysis

Scatter measurement

Error analysis

Monte Carlo methods

Chromium

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