Graduate Thesis Or Dissertation
 

Wave-by-Wave Forecasting via Assimilation of Marine Radar Data

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https://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/4t64gr89b

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  • A wave-by-wave forecasting system is desired for optimization of wave energy conversion devices and for improving safety of vessel-based marine operations. This study outlines the first validation attempts of a recently developed forecasting system called Wavecast. The forecasting approach uses X-Band marine radar images for data assimilation, then reconstructs and propagates the ocean wave field in both space and time using the Mild Slope Equation wave model. For data assimilation, the radial component of the sea surface slope is computed from the radar imagery using the recently-derived Radar Model (Lyzenga & Walker, 2015). The Radar Model is a direct relationship between radar backscatter intensity and radial slope, without the need for external calibration. Validation attempts of the forecasting system are carried out in two phases. First, synthetic data is used. Two trials are presented: a simple monochromatic dataset, and a nonlinear simulation of a realistic sea. Results of monochromatic testing show strong spectral correlation, and time series correlation of up to 0.9 throughout the full domain. Results of nonlinear testing show up to 83% spectral correlation of significant wave height, time series correlation up to 0.9 among reconstructed waves, but some decay in correlation among predicted waves. Next a field dataset is presented, which was collected by a ship-mounted radar offshore Newport, OR with spatial and temporal overlap to a TRIAXYS wave profiling buoy. The field dataset provides several challenges. Noise in the electronic compass readings prevented rectification of the ship’s motion; however, this was overcome using a novel post-processing technique on the radar images to georeference each scan without the need for electronic compass readings. Additionally, uncertainty exists in the location of the TRIAXYS buoy; thus, a cross-correlation analysis was performed on a small region surrounding the buoy’s anticipated location to determine the location of maximum correlation between actual and model time series. Despite complexities in the field dataset, assimilation of the field data in Wavecast shows good spectral reconstruction, with issues remaining in time series correlation. The presented validation attempts provide improved understanding of the accuracy and potential of Wavecast, and give support for the validity of the Radar Model.
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