The Probability Distribution of Sea Surface Wind Speeds. Part I: Theory and SeaWinds Observations
The probability distribution of sea surface wind speeds,w, is considered. Daily SeaWinds scatterometer observations are used for the characterization of the moments of sea surface winds on a global scale. These observations confirm the results of earlier studies, which found that the two-parameter W...
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Veröffentlicht in: | Journal of climate 2006-02, Vol.19 (4), p.497-520 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | The probability distribution of sea surface wind speeds,w, is considered. Daily SeaWinds scatterometer observations are used for the characterization of the moments of sea surface winds on a global scale. These observations confirm the results of earlier studies, which found that the two-parameter Weibull distribution provides a good (but not perfect) approximation to the probability density function ofw. In particular, the observed and Weibull probability distributions share the feature that the skewness ofwis a concave upward function of the ratio of the mean ofwto its standard deviation. The skewness ofwis positive where the ratio is relatively small (such as over the extratropical Northern Hemisphere), the skewness is close to zero where the ratio is intermediate (such as the Southern Ocean), and the skewness is negative where the ratio is relatively large (such as the equatorward flank of the subtropical highs). An analytic expression for the probability density function ofw, derived from a simple stochastic model of the atmospheric boundary layer, is shown to be in good qualitative agreement with the observed relationships between the moments ofw. Empirical expressions for the probability distribution ofwin terms of the mean and standard deviation of the vector wind are derived using Gram–Charlier expansions of the joint distribution of the sea surface wind vector components. The significance of these distributions for improvements to calculations of averaged air–sea fluxes in diagnostic and modeling studies is discussed. |
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ISSN: | 0894-8755 1520-0442 |
DOI: | 10.1175/jcli3640.1 |