Exploring the interannual variability of extreme wave climate in the Northeast Atlantic Ocean Articles uri icon

authors

publication date

  • December 2012

start page

  • 31

end page

  • 40

volume

  • 59-60

International Standard Serial Number (ISSN)

  • 1463-5003

Electronic International Standard Serial Number (EISSN)

  • 1463-5011

abstract

  • The extreme wave climate is of paramount importance for: (i) off-shore and coastal engineering design, (ii) ship design and maritime transportation, or (iii) analysis of coastal processes. Identifying the synoptic patterns that produce extreme waves is necessary to understand the wave climate for a specific location. Thus, a characterization of these weather patterns may allow the study of the relationships between the magnitude and occurrence of extreme wave events and the climate system. The aim of this paper is to analyze the interannual variability of extreme wave heights. For this purpose, we present a methodological framework and its application to an area over the North East (NE) Atlantic Ocean. The climatology in the NE Atlantic is analyzed using the self-organizing maps (SOMs). The application of this clustering technique to monthly mean sea level pressure fields provides a continuum of synoptic categorizations compared with discrete realizations produced through most traditional methods. The extreme wave climate has been analyzed by means of monthly maxima of the significant wave height (SWH) in several locations over the NE Atlantic. A statistical approach based on a time-dependent generalized extreme value (GEV) distribution has been applied. The seasonal variation was characterized and, afterwards, the interannual variability was studied throughout regional pressure patterns. The anomalies of the 50-year return level estimates of SWH, due to interannual variability have been projected into the weather types of SOM. It provides a comprehensive visual representation, which relates the weather type with the positive or negative contribution to extreme waves over the selected locations.

subjects

  • Environment
  • Statistics

keywords

  • climate variability; extreme wave climate; generalized extreme value distribution; self organizing maps; synoptic classification; weather types