Monday, 7 January 2013

Exhibit Hall 3 (Austin Convention Center)

The linear predictability of wind speed using Gaussian predictors, relative to the predictability of the vector wind components, is considered. Analytic expressions for the correlation-based wind speed prediction skill are obtained in terms of the prediction skills of the vector wind components and their statistical moments. This analysis is facilitated by the assumption that the vector winds are Gaussian, and by the fact that fluctuations of the wind speed are highly correlated with those of its square. It is shown that:

1. at least one of the vector wind components is generally better predicted than the wind speed

2. wind speed predictions constructed from the predictions of vector wind components are more skillful than direct wind speed predictions

3. the linear predictability of wind speed (relative to that of the vector wind components) increases as vector wind fluctuations become smaller relative to their mean value

These model results are shown to be broadly consistent with linear predictive skills assessed using sea surface wind observations from the SeaWinds scatterometer. Biases in the model predictions are shown to be related to the degree to which vector wind fluctuations are non-Gaussian.

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