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On the Expected Structure of Extreme Waves in a Gaussian Sea. Part II: SWADE Scanning Radar Altimeter Measurements

O. M. PhillipsEarth and Planetary Sciences, The Johns Hopkins University, Baltimore, Maryland

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Daifang GuEarth and Planetary Sciences, The Johns Hopkins University, Baltimore, Maryland

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Edward J. WalshNASA Goddard Space Flight Center, Greenbelt, Maryland

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Abstract

In a previous paper (Phillips et al.) an approximate theory was developed that predicted that the expected configuration of extreme waves in a random sea (or the average configuration of an ensemble of extreme waves) is proportional to the space-time autocorrelation function of the surface displacement of the wave field as a whole. This result is tested by examination of scanning radar altimeter measurements made during SWADE in four different sea states, including a unimodal mature wave field, a short fetch, a wind-generated sea crossing swell, a very broad directional spectrum, and a fetch-limited wind sea with opposing swell. In each of these, the spatial autocorrelation function was found directly from the SRA data. The highest waves in each dataset were selected and their configurations averaged with respect to the crest. These averaged configurations were in each case found to be consistent with the autocorrelation function.

Abstract

In a previous paper (Phillips et al.) an approximate theory was developed that predicted that the expected configuration of extreme waves in a random sea (or the average configuration of an ensemble of extreme waves) is proportional to the space-time autocorrelation function of the surface displacement of the wave field as a whole. This result is tested by examination of scanning radar altimeter measurements made during SWADE in four different sea states, including a unimodal mature wave field, a short fetch, a wind-generated sea crossing swell, a very broad directional spectrum, and a fetch-limited wind sea with opposing swell. In each of these, the spatial autocorrelation function was found directly from the SRA data. The highest waves in each dataset were selected and their configurations averaged with respect to the crest. These averaged configurations were in each case found to be consistent with the autocorrelation function.

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