In this thesis, three improved analysis techniques for scatterometer wind estimation are presented. These techniques build upon previous methods that help validate scatterometer data. This thesis examines the theory connecting the 1D and 2D kinetic energy spectra and uses QuikSCAT data to measure the 2D kinetic energy spectrum of ocean winds. The measured 2D kinetic energy spectrum is compared to the traditional 1D kinetic energy spectrum. The relationship between the 2D kinetic energy spectra and the 1D kinetic energy spectra confirms findings from previous studies that ocean winds modeled in 2D are isotropic and nondivergent. The 1D and 2D kinetic energy spectra also confirm the known conclusion that the zonal and meridional components of ocean winds are uncorrelated. Through simulation, the wind response function (WRF) is calculated for three different QuikSCAT processing algorithms. The WRF quantifies the contribution that the wind at each point of the surface makes to a given wind estimate. The spatial resolution of the different processing algorithms is estimated by their WRFs. The WRFs imply that the spatial resolution of ultrahigh resolution (UHR) processing is finer than the spatial resolution of conventional drop-in-the-bucket (DIB) processing; the spatial resolution of UHR processing is ~5-10 km while the spatial resolution of DIB slice processing is ~12-15 km and the spatial resolution of coarse resolution DIB egg processing is ~30 km. Simulation is used to analyze the effectiveness of various wind retrieval and ambiguity selection algorithms. To assist in the simulation, synthetic wind fields are created through extrapolating the 2D Fourier transform of a numerical weather prediction wind field. These synthetic wind fields are sufficiently realistic to evaluate ambiguity selection algorithms. The simulation employs the synthetic wind fields to compare wind estimation with and without direction interval retrieval (DIR) applied. Both UHR and DIB wind estimation processes are performed in the simulation and UHR winds are shown to resolve finer resolution wind features than DIB winds at the cost of being slightly noisier. DIR added to standard QuikSCAT UHR wind estimation drops the wind direction root-mean-squared error by ~10° to ~24.74° in the swath sweet spot.
College and Department
Ira A. Fulton College of Engineering and Technology; Electrical and Computer Engineering
BYU ScholarsArchive Citation
Schachterle, Gregory Dallin, "Improved Analysis Techniques for Scatterometer Wind Estimation" (2020). Theses and Dissertations. 9218.
scatterometer, QuikSCAT, ultrahigh resolution, direction interval retrieval, simulation, kinetic energy spectrum, synthetic wind field, wind response function