Open AccessPrediction of the extreme wind speed in the mixed climate region by using Monte Carlo simulation and measure‐correlate‐predict method
Author(s) -
Ishihara Takeshi,
Yamaguchi Atsushi
Publication year - 2015
Publication title -
wind energy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.743
H-Index - 92
eISSN - 1099-1824
pISSN - 1095-4244
DOI - 10.1002/we.1693
Subject(s) - gumbel distribution , wind speed , monte carlo method , meteorology , extreme value theory , environmental science , probability distribution , extratropical cyclone , statistics , climatology , mathematics , physics , geology
The extreme wind speed at an offshore location was predicted using Monte Carlo simulation (MCS) and measure‐correlate‐predict (MCP) method. The Gumbel distribution could successfully express the annual maximum wind speed of extratropical cyclone. On the other hand, the estimated extreme wind speed of tropical cyclones by analytical probability distribution shows larger uncertainty. In the mixed climate like Japan, the extreme wind speed estimated from the combined probability distribution obtained by MCP and MCS methods agrees well with the observed data as compared with the combined probability distribution obtained by the MCP method only. The uncertainty of extreme wind speed due to limited observation period of wind speed and pressure was also evaluated by the Gumbel theory and Monte Carlo simulation. As a result, it was found that the uncertainty of 50 year recurrence wind speed obtained by MCS method is considerably smaller than that obtained by MCP method in the mixed climate. Copyright © 2014 John Wiley & Sons, Ltd.