NASA Logo

NTRS

NTRS - NASA Technical Reports Server

Back to Results
Towards an Optimal Noise Versus Resolution Trade-Off in Wind ScatterometryA scatterometer is a radar that measures the normalized radar cross section sigma(sup 0) of the Earth's surface. Over the ocean this signal is related to the wind via the geophysical model function (GMF). The objective of wind scatterometry is to estimate the wind vector field from sigma(sup 0) measurements; however, there are many subtleties that complicate this problem-making it difficult to obtain a unique wind field estimate. Conventionally, wind estimation is split into two stages: a wind retrieval stage in which several ambiguous solutions are obtained, and an ambiguity removal stage in which ambiguities are chosen to produce an appropriate wind vector field estimate. The most common approach to wind field estimation is to grid the scatterometer swath into wind vector cells and estimate wind vector ambiguities independently for each cell. Then, field wise structure is imposed on the solution by an ambiguity selection routine. Although this approach is simple and practical, it neglects field wise structure in the retrieval step and does not account for the spatial correlation imposed by the sampling. This makes it difficult to develop a theoretically appropriate noise versus resolution trade-off using pointwise retrieval. Fieldwise structure may be imposed in the retrieval step using a model-based approach. However, this approach is generally only practical if a low order wind field model is applied, which may discard more information than is desired. Furthermore, model-based approaches do not account for the structure imposed by the sampling. A more general fieldwise approach is to estimate all the wind vectors for all the WVCs simultaneously from all the measurements. This approach can account for structure of the wind field as well as structure imposed by the sampling in the wind retrieval step. Williams and Long in 2010 developed a fieldwise retrieval method based on maximum a posteriori estimation (MAP). This MAP approach can be extended to perform a noise versus resolution trade-off, and deal with ambiguity selection. This paper extends the fieldwise MAP estimation approach and investigates both the noise versus resolution trade-off as well as ambiguity removal in the fieldwise wind retrieval step. The method is then applied to the Sea Winds scatterometer and the results are analyzed. This paper extends the fieldwise MAP estimation approach and investigates both the noise versus resolution trade-off as well as ambiguity removal in the fieldwise wind retrieval step. The method is then applied to the Sea Winds scatterometer and the results are analyzed.
Document ID
20150005745
Acquisition Source
Jet Propulsion Laboratory
Document Type
Conference Paper
External Source(s)
Authors
Williams, Brent A.
(Jet Propulsion Lab., California Inst. of Tech. Pasadena, CA, United States)
Date Acquired
April 16, 2015
Publication Date
July 26, 2011
Subject Category
Meteorology And Climatology
Meeting Information
Meeting: 2011 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
Location: Vancouver
Country: Canada
Start Date: July 24, 2011
End Date: July 29, 2011
Sponsors: Institute of Electrical and Electronics Engineers
Distribution Limits
Public
Copyright
Other
Keywords
soil moisture
ancillary datasets
maximum a posteriori estimation (MAP)
freeze/thaw

Available Downloads

There are no available downloads for this record.
No Preview Available