Spatio-temporal modelling of wind speed variations and extremes in the Caribbean and the Gulf of Mexico
Journal article, 2019
Gaussian field. However, this type of model does not correctly describe the extreme wind speeds attributed to tropical
storms and hurricanes. In this study, the transformed Gaussian model is further developed to include the occurrence of
severe storms. In this new model, random components are added to the transformed Gaussian field to model rare events with
extreme wind speeds. The resulting random field is locally stationary and homogeneous. The localized dependence structure
is described by time- and space-dependent parameters. The parameters have a natural physical interpretation. To exemplify
its application, the model is fitted to the ECMWF ERA-Interim reanalysis data set. The model is applied to compute longterm
wind speed distributions and return values, e.g., 100- or 1000-year extreme wind speeds, and to simulate random wind
speed time series at a fixed location or spatio-temporal wind fields around that location.
extreme prediction
spatio-temporal model
wind speed
laplace moving average
transformed gaussian model
Author
Igor Rychlik
Chalmers, Mathematical Sciences, Applied Mathematics and Statistics
Wengang Mao
Chalmers, Mechanics and Maritime Sciences (M2), Marine Technology
Theorectical and Applied Climatology
0177-798X (ISSN) 1434-4483 (eISSN)
Vol. 135 3-4 921-944Areas of Advance
Information and Communication Technology
Transport
Energy
Driving Forces
Sustainable development
Subject Categories
Ocean and River Engineering
Marine Engineering
Probability Theory and Statistics
Roots
Basic sciences
DOI
10.1007/s00704-018-2411-y