Bayesian Hierarchical Space-Time Models with Application to Significant Wave Height

2013 ◽  
Author(s):  
Erik Vanem
Keyword(s):  
Wave Height ◽  
Significant Wave Height ◽  
Space Time ◽  
Bayesian Hierarchical ◽  
Significant Wave

A Bayesian-Hierarchical Space-Time Model for Significant Wave Height Data

2011 ◽  
Author(s):  
Erik Vanem ◽  
Arne Bang Huseby ◽  
Bent Natvig
Keyword(s):  
Wave Height ◽  
Significant Wave Height ◽  
North Atlantic Ocean ◽  
Space Time ◽  
Maritime Transportation ◽  
Time Model ◽  
Bayesian Hierarchical ◽  
Significant Wave ◽  
The North ◽  
Future Return

Bad weather and rough seas contribute significantly to the risk to maritime transportation. This stresses the importance of taking severe sea state conditions adequately into account, with due treatment of the uncertainties involved, in ship design and operation. Hence, there is a need for appropriate stochastic models describing the variability of sea states. This paper presents a Bayesian hierarchical space-time stochastic model for significant wave height. The model has been fitted by data for an area in the North Atlantic ocean and aims at describing the temporal and spatial variability of significant wave height in this area. It could also serve as foundation for further extensions used for long-term prediction of significant wave height and future return periods of extreme significant wave heights. The model will be outlined in this paper, and the results will be discussed. Furthermore, a discussion of possible model extensions will be presented.

Statistical modeling of the space-time relation between wind and significant wave height

2022 ◽  
Author(s):  
Said Obakrim ◽  
Pierre Ailliot ◽  
Valerie Monbet ◽  
Nicolas Raillard
Keyword(s):  
Statistical Modeling ◽  
Wave Height ◽  
Significant Wave Height ◽  
Space Time ◽  
Significant Wave ◽  
Time Relation

scholarly journals Space-time models for moving fields with an application to significant wave height fields

2010 ◽  
Vol 22 (3) ◽  
pp. 354-369 ◽  
Author(s):  
Pierre Ailliot ◽  
Anastassia Baxevani ◽  
Anne Cuzol ◽  
Valerie Monbet ◽  
Nicolas Raillard
Keyword(s):  
Wave Height ◽  
Significant Wave Height ◽  
Space Time ◽  
Significant Wave ◽  
Height Fields

scholarly journals Statistical modeling of the space-time relation between wind and significant wave height

2022 ◽  
Author(s):  
Said Obakrim ◽  
Pierre Ailliot ◽  
Valerie Monbet ◽  
Nicolas Raillard
Keyword(s):  
Statistical Modeling ◽  
Wave Height ◽  
Significant Wave Height ◽  
Space Time ◽  
Significant Wave ◽  
Time Relation

scholarly journals Bayesian hierarchical modelling of North Atlantic windiness

2013 ◽  
Vol 13 (3) ◽  
pp. 545-557 ◽  
Author(s):  
E. Vanem ◽  
O. N. Breivik
Keyword(s):  
Climate Change ◽  
Wave Height ◽  
North Atlantic ◽  
Environmental Conditions ◽  
Significant Wave Height ◽  
Weather Conditions ◽  
Extreme Weather ◽  
Bayesian Hierarchical ◽  
Significant Wave

Abstract. Extreme weather conditions represent serious natural hazards to ship operations and may be the direct cause or contributing factor to maritime accidents. Such severe environmental conditions can be taken into account in ship design and operational windows can be defined that limits hazardous operations to less extreme conditions. Nevertheless, possible changes in the statistics of extreme weather conditions, possibly due to anthropogenic climate change, represent an additional hazard to ship operations that is less straightforward to account for in a consistent way. Obviously, there are large uncertainties as to how future climate change will affect the extreme weather conditions at sea and there is a need for stochastic models that can describe the variability in both space and time at various scales of the environmental conditions. Previously, Bayesian hierarchical space-time models have been developed to describe the variability and complex dependence structures of significant wave height in space and time. These models were found to perform reasonably well and provided some interesting results, in particular, pertaining to long-term trends in the wave climate. In this paper, a similar framework is applied to oceanic windiness and the spatial and temporal variability of the 10-m wind speed over an area in the North Atlantic ocean is investigated. When the results from the model for North Atlantic windiness is compared to the results for significant wave height over the same area, it is interesting to observe that whereas an increasing trend in significant wave height was identified, no statistically significant long-term trend was estimated in windiness. This may indicate that the increase in significant wave height is not due to an increase in locally generated wind waves, but rather to increased swell. This observation is also consistent with studies that have suggested a poleward shift of the main storm tracks.

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