To main content

Nonstationary fuzzy forecasting of wind and wave climate in very long-term scales

Abstract

Global climate change may have serious impact on human activities in coastal and other areas. Climate change may affect the degree
of storminess and, hence, change the wind-driven ocean wave climate. This may affect the risks associated with maritime activities such
as shipping and offshore oil and gas. So, there is a recognized need to understand better how climate change will affect such processes.
Typically, such understanding comes from future projections of the wind and wave climate from numerical climate models and from the
stochastic modelling of such projections. This work investigates the applicability of a recently proposed nonstationary fuzzy modelling to
wind and wave climatic simulations. According to this, fuzzy inference models (FIS) are coupled with nonstationary time series modelling,
providing us with less biased climatic estimates. Two long-term datasets for an area in the North Atlantic Ocean are used in the present
study, namely NORA10 (57 years) and ExWaCli (30 years in the present and 30 years in the future). Two distinct experiments have been
performed to simulate future values of the time series in a climatic scale. The assessment of the simulations by means of the actual values
kept for comparison purposes gives very good results.
Read publication

Category

Academic article

Client

  • Research Council of Norway (RCN) / 243814

Language

English

Author(s)

Affiliation

  • SINTEF Ocean / Fisheries and New Biomarine Industry
  • DNV

Year

2018

Published in

Journal of Ocean Engineering and Science

ISSN

2468-0133

Publisher

Elsevier

Volume

3

Page(s)

144 - 155

View this publication at Cristin