Spatio-temporal modelling of wind speed variations and extremes in the Caribbean and the Gulf of Mexico
Journal article, 2019

The wind speed variability in the North Atlantic has been successfully modelled using a spatio-temporal transformed
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


Igor Rychlik

Chalmers, Mathematical Sciences, Applied Mathematics and Statistics

Wengang Mao

Chalmers, Mechanics and Maritime Sciences, Marine Technology

Theorectical and Applied Climatology

0177-798X (ISSN) 1434-4483 (eISSN)

Vol. 135 3-4 921-944

Areas of Advance

Information and Communication Technology



Driving Forces

Sustainable development

Subject Categories

Ocean and River Engineering

Marine Engineering

Probability Theory and Statistics


Basic sciences



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