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Generation of Large Directional Wind Speed Datasets from Smaller Synoptic Storm or Thunderstorm Data Samples

Published

Author(s)

Donghun Yeo

Abstract

For structures sensitive to wind directionality, methods for the estimation of wind effects require the use of time series of directional wind speeds covering time periods exceeding the length of the Mean Recurrence Interval of interest in design. This study proposes a procedure for generating such time series from relatively short wind data sets. The focus in this paper is on the estimation of the parameters of a probabilistic model of the wind speeds. The wind speed data being generated can be used within the framework of the Database-Assisted Design approach to determine wind effects on buildings by accounting for wind directionality.
Citation
Technical Note (NIST TN) - 1756
Report Number
1756

Keywords

Directional wind speeds, Mean recurrence intervals, Extreme value statistics, Synthetic wind speed data, Monte Carlo simulation, Generalized Pareto distribution.

Citation

Yeo, D. (2013), Generation of Large Directional Wind Speed Datasets from Smaller Synoptic Storm or Thunderstorm Data Samples, Technical Note (NIST TN), National Institute of Standards and Technology, Gaithersburg, MD, [online], https://doi.org/10.6028/NIST.TN.1756 (Accessed July 13, 2024)

Issues

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Created August 15, 2013, Updated January 27, 2020