## A stochastic model of wind gusts |

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### Contents

NATURE OF THE WIND | 6 |

INTRODUCTION TO THE FILTERED POISSON PROCESS | 26 |

STATISTICAL PROCEDURES | 45 |

5 other sections not shown

### Common terms and phrases

air masses anemometer trace anticyclone autocorrelation function average velocity average wind velocity basic beta distribution Chapter characteristic function coefficient of determination computed confidence intervals convectional turbulence correlation coefficient corresponding covariance function cyclone Davenport defined discussed drag coefficient eddy shape eddy velocity exponential distribution exponential random variables extratropical cyclones feet filtered Poisson model filtered Poisson process flow frequency function is given gamma distribution gradient impulse function law with parameter limiting filtered Poisson linear regression magnitudes mathematical mean value function mechanical turbulence model of wind normal process normal random variables observed variables obtained occur physical observations Poisson counting process power law probability density function probability distribution probability law probability theory ratio of gustiness sample function shown in Figure simulated wind spectral density function spectral estimates stationary process stochastic model stochastic process surface roughness terrain thermal Var[X(t velocity fluctuations velocity with height wave number wind gusts wind phenomenon wind records wind storm zero