Spatio-temporal modelling of wind speed variation
Paper in proceeding, 2018
In the present study, these models are used to describe the variability of wind speed in other areas, i.e., the Caribbean sea, the South China Sea and the Arctic area. In most locations, the transformed Gaussian field is a sufficiently accurate model. However, in some regions, e.g. Laptev and the Beaufort Sea at the Arctic, this model severely underestimates the frequencies of extreme winds. In this study, the hybrid model is used to describe the wind variation in these regions. There are also locations, e.g. along the east coast of Greenland, most of the coast areas of the South China Sea, where frequencies of high wind speeds are severely overestimated by the transformed Gaussian model.
In this paper, the models are fitted to ERA-Interim reanalysis wind data and used to find long-term distributions of wind speed, to estimate wind speed return values, e.g. 100-year extreme wind speed, and to compute the expected yearly frequency of events that wind speed exceeds a fixed threshold value.
South China Sea
Spatio-temporal wind statistics
Chalmers, Mechanics and Maritime Sciences (M2), Marine Technology
Chalmers, Computer Science and Engineering (Chalmers), CSE Verksamhetsstöd
Chalmers, Mathematical Sciences, Applied Mathematics and Statistics
Proceedings of the International Offshore and Polar Engineering Conference
10986189 (ISSN) 15551792 (eISSN)Vol. 2018-June 397-402
Modeling environmental loads and structural responses
Swedish Research Council (VR) (2012-6004), 2012-01-01 -- 2015-12-31.
Explore innovative solutions for arctic shipping
The Swedish Foundation for International Cooperation in Research and Higher Education (STINT) (Dnr:CH2016-6673), 2017-05-01 -- 2020-06-30.
Big data based autonomous navigation system for safe and efficient shipping
Chalmers, 2018-01-01 -- 2019-12-31.
Areas of Advance
Information and Communication Technology
Meteorology and Atmospheric Sciences
Probability Theory and Statistics