Temporal Filtering Enhances the Skewness of Sea Surface Winds

• Published in: Journal of climate 2018-07, Vol.31 (14), p.5695-5706
• Main Author: Monahan, Adam H.
• Format: Article
• Language: English
• Subjects: Additives; Air temperature; Bandpass filters; Dynamical systems; Dynamics; Low pass filters; Noise; Nonlinear dynamics; Nonlinear systems; Oceans; Parameter estimation; Probability distribution; Radiosondes; Sea surface; Skewness; Stochastic models; Storm tracks; Storms; Surface wind; Temperature (air-sea); Time; Time series; Wind; Wind direction; Winds
• ISSN: 0894-8755; 1520-0442
• DOI: 10.1175/JCLI-D-17-0814.1

The component of the sea surface wind in the along-mean wind direction is known to display pronounced skewness at many locations over the ocean. A recent study by Proistosescu et al. found that the skewness of daily 850-hPa air temperature measured by radiosondes is typically reduced by bandpass filtering. This behavior was also shown to be characteristic of correlated additive–multiplicative (CAM) noise, which has been proposed as a generic model for non-Gaussian variability in the atmosphere and ocean. The present study shows that if the cutoff frequency is not too low, the skewness of the along-mean wind component is enhanced by low-pass filtering, particularly in the equatorial band and in the midlatitude storm tracks. The filter time scale beyond which skewness is systematically reduced by filtering is of the daily to synoptic scale, except in a narrow equatorial band where it is of subseasonal to seasonal time scales. This behavior is reproduced in an idealized stochastic model of the near-surface winds, in which key parameters are the characteristic time scales of the nonlinear dynamics and of the noise. These results point toward more general approaches for assessing the relative importance of multiplicative noise or dynamical nonlinearities in producing non-Gaussian structure in atmospheric and oceanic fields.