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."
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