Abstract
This report consists of two parts. In the first a spectral tensor model of neutral atmospheric surface layer turbulence is developed. The model is validated trough comparison with second order turbulence statistics from the Great Belt Coherence Experiment, The Lammefjords Experiment and wind tunnel data from Danish Maritime Institute. Based on the spectral tensor an efficient and simple algorithm for simulation of three-dimensional wind fields is generated. The simulation is well suited for load calculation on bridges, wind turbines and other engineering structures. The spectral tensor is also used to estimate errors in momentum flux measurements close to the ground due to displacement of the sensors of vertical and horizontal velocity fluctuations. In the second part mathematical tools are developed to determine how long a time series of turbulent signal must be to estimate covariances and higher order moments with a specified statistical significance. Both systematic and random data from the convective boundary layer over the ocean and over land, that if the time series are assumed to be Gaussian the random errors are underestimated. A skewed model process gives better estimates of the random error. The tools are used in the convective boundary layer to show that the systematic
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Citation Formats
Mann, J.
Models in micrometeorology.
Denmark: N. p.,
1994.
Web.
Mann, J.
Models in micrometeorology.
Denmark.
Mann, J.
1994.
"Models in micrometeorology."
Denmark.
@misc{etde_10149120,
title = {Models in micrometeorology}
author = {Mann, J}
abstractNote = {This report consists of two parts. In the first a spectral tensor model of neutral atmospheric surface layer turbulence is developed. The model is validated trough comparison with second order turbulence statistics from the Great Belt Coherence Experiment, The Lammefjords Experiment and wind tunnel data from Danish Maritime Institute. Based on the spectral tensor an efficient and simple algorithm for simulation of three-dimensional wind fields is generated. The simulation is well suited for load calculation on bridges, wind turbines and other engineering structures. The spectral tensor is also used to estimate errors in momentum flux measurements close to the ground due to displacement of the sensors of vertical and horizontal velocity fluctuations. In the second part mathematical tools are developed to determine how long a time series of turbulent signal must be to estimate covariances and higher order moments with a specified statistical significance. Both systematic and random data from the convective boundary layer over the ocean and over land, that if the time series are assumed to be Gaussian the random errors are underestimated. A skewed model process gives better estimates of the random error. The tools are used in the convective boundary layer to show that the systematic flux and flux gradient errors can be important if fluxes are calculated from a set of several short flight legs or if the vertical velocity and scalar time series are high-pass filtered. (au) (17 tabs., 52 ills., 87 refs.)}
place = {Denmark}
year = {1994}
month = {Mar}
}
title = {Models in micrometeorology}
author = {Mann, J}
abstractNote = {This report consists of two parts. In the first a spectral tensor model of neutral atmospheric surface layer turbulence is developed. The model is validated trough comparison with second order turbulence statistics from the Great Belt Coherence Experiment, The Lammefjords Experiment and wind tunnel data from Danish Maritime Institute. Based on the spectral tensor an efficient and simple algorithm for simulation of three-dimensional wind fields is generated. The simulation is well suited for load calculation on bridges, wind turbines and other engineering structures. The spectral tensor is also used to estimate errors in momentum flux measurements close to the ground due to displacement of the sensors of vertical and horizontal velocity fluctuations. In the second part mathematical tools are developed to determine how long a time series of turbulent signal must be to estimate covariances and higher order moments with a specified statistical significance. Both systematic and random data from the convective boundary layer over the ocean and over land, that if the time series are assumed to be Gaussian the random errors are underestimated. A skewed model process gives better estimates of the random error. The tools are used in the convective boundary layer to show that the systematic flux and flux gradient errors can be important if fluxes are calculated from a set of several short flight legs or if the vertical velocity and scalar time series are high-pass filtered. (au) (17 tabs., 52 ills., 87 refs.)}
place = {Denmark}
year = {1994}
month = {Mar}
}