Remote sensing is becoming an increasingly important tool for ocean wave measurement, and over the past decade much progress has been made in the development of the wave measuring capabilities of HF (High Frequency) radar. This system is able to make detailed and near continuous observations of the sea surface over a wide area. However, because the mathematics of the data extraction process is rather difficult, the statistical properties of the observed data have to date been poorly understood. In this study, the approximate sampling distributions of a variety of measurements from HF radar (including significant waveheight, mean wave period, wind direction, and various spectral parameters) are derived in terms of quantities that are either known or estimable. The resulting confidence intervals are, in the case of significant waveheight and mean wave period, of comparable width to those obtained from the corresponding NURWEC2 (Netherlands UK Radar Wave buoy Experimental Comparison) wave buoy measurements, and in the case of spectral power, they are narrower. Furthermore, methods are derived by which such radar measurements may be compared with their corresponding wave buoy measurements in a statistically valid manner, and their relative biases estimated. These methods are then applied to data taken during the NURWEC2 field trial, which suggest that the radars and the wave buoy show good correspondence for measurements of significant waveheight and of spectral power (over 85 - 125mHz - the frequencies with most wave power, and hence those of most importance). There is also a fair correspondence for mean period measurements in the range 6.8 - 11.0secs. Spectral mean direction shows good correspondence over 85 - 155mHz over the somewhat limited directional range (i. e. as observed during the NURWEC2 storm) of the data.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:319442 |
| Date | January 1995 |
| Creators | Sova, Markus Gintas |
| Publisher | University of Sheffield |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://etheses.whiterose.ac.uk/12786/ |
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