{'fraction_non_alphanumeric': 0.015189873417721518, 'fraction_numerical': 0.0, 'mean_word_length': 5.020304568527918, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
New approach to the generation of realistic sea surfaces using stationary non-Gaussian random fields

The methods currently used for the generation of wind roughened sea surfaces suffer shortcomings. This paper shows that in the one-dimensional case (i.e. looking at the vertical movements of a single point on a sea surface in time) the problem of generating a time series of surface heights having the correct autocorrelation function and the required Cox-Munk distribution of slopes can be solved by generating a Gaussian random sequence with the appropriate autocorrelation function, and passing it through a non-linear pointwise transform to generate a sequence with the required properties. In the two-dimensional case the problem is not yet completely solved, as it is not clear whether an appropriate field of slopes can be integrated to generate a field of wave heights. Nevertheless, the results obtained so far serve as a correction to the algorithm where a pseudo sea surface is generated by convolving a field of independent slope values drawn from a Cox-Munk distribution with a spatial filter derived from the Pierson-Moskowitz power spectral density of surface heights.