Abstract

Originally designed for wind velocity estimation over the ocean, scatterometers have since been applied to climate studies of the Earth's cryosphere and bioshere. As an integral part of climatological studies of the planet, the NASA Scatterometer Climate Record Pathfinder (SCP) supplies scatterometer-based products designed to aid researchers in climatological studies of the planet. In this thesis, necessary steps are taken to facilitate data from the Oceansat-2 Ku-band scatterometer (OSCAT) to be used in extending the Ku-band SCP dataset of conically scanning pencil-beam scatterometers begun by the Seawinds scatterometer flown on the QuikSCAT mission 1999-2009. As a standard SCP product, a temporal resolution enhancement technique for the scatterometer image reconstruction (SIR) algorithm is applied to OSCAT data. A relative cross-calibration method is developed to ensure consistency amongst datasets of conically scanning pencil-beam scatterometers in the SCP data time series. By application of the method, both raw data and SIR image data of OSCAT is cross-calibrated with QuikSCAT. To enable creation of SCP products requiring knowledge of the spatial response function (SRF) with OSCAT data, a method of estimating the SRF of pencil-beam scatterometers is developed. The estimation method employs rank-reduced least-squares to invert the radar equation using measurements over islands. A simulation is performed to validate the efficacy of the method and provide optimum choice of island size and number of singular values used in rank-reduced least-squares. The utility of the SRF estimates is demonstrated by applying an estimate of the OSCAT SRF to SIR image construction with OSCAT data.

Degree

MS

College and Department

Ira A. Fulton College of Engineering and Technology; Electrical and Computer Engineering

Rights

http://lib.byu.edu/about/copyright/

Date Submitted

2012-04-14

Document Type

Thesis

Handle

http://hdl.lib.byu.edu/1877/etd5176

Keywords

OSCAT, QuikSCAT, SIR algorithm, scatterometer calibration, local time of day processing, spatial response function

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