Bayesian Hierarchical Modeling of the Ocean Windiness

Abstract

AbstractPreviously, 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 chapter, a similar framework is applied to oceanic windiness and the spatial and temporal variability of the 10-m wind speed over essentially the same area in the North Atlantic Ocean is investigated. When the results from the model for North Atlantic windiness are 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.KeywordsWind SpeedSignificant Wave HeightWave ClimateWind Speed DataSpatial FieldThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.