This book provides an example of a thorough statistical treatment of
ocean wave data in space and time. It demonstrates how the flexible
framework of Bayesian hierarchical space-time models can be applied to
oceanographic processes such as significant wave height in order to
describe dependence structures and uncertainties in the data.
This monograph is a research book and it is partly cross-disciplinary.
The methodology itself is firmly rooted in the statistical research
tradition, based on probability theory and stochastic processes.
However, that methodology has been applied to a problem in the field of
physical oceanography, analyzing data for significant wave height, which
is of crucial importance to ocean engineering disciplines. Indeed, the
statistical properties of significant wave height are important for the
design, construction and operation of ships and other marine and coastal
structures. Furthermore, the book addresses the question of whether
climate change has an effect of the ocean wave climate, and if so what
that effect might be. Thus, this book is an important contribution to
the ongoing debate on climate change, its implications and how to adapt
to a changing climate, with a particular focus on the maritime
industries and the marine environment.
This book should be of value to anyone with an interest in the
statistical modelling of environmental processes, and in particular to
those with an interest in the ocean wave climate. It is written on a
level that should be understandable to everyone with a basic background
in statistics or elementary mathematics, and an introduction to some
basic concepts is provided in the appendices for the uninitiated reader.
The intended readership includes students and professionals involved in
statistics, oceanography, ocean engineering, environmental research,
climate sciences and risk assessment. Moreover, the book's findings are
relevant for various stakeholders in the maritime industries such as
design offices, classification societies, ship owners, yards and
operators, flag states and intergovernmental agencies such as the IMO.
