Verification within Wave Resource Assessments. Part 1: Statistical Analysis

Emma Edwards, Lucy Cradden, David Ingram, Christina Kalogeri

Research output: Contribution to journalArticlepeer-review


Interest in wave energy as a viable renewable energy has increased greatly in the past couple of decades. To determine the potential that a certain location has to harvest wave energy, a resource assessment must be performed for that location. As wave energy converter technologies get closer to market, it is becoming necessary to undertake more detailed resource assessments in order to determine the optimal location for deployment as well as the design and operating sea states. This study shows the level of sophistication that must be included in the verification process within a wave resource assessment. We describe the methodology in two articles. The first part shows how doing a complete statistical analysis of the fit of the model at the location of interest is essential for determining the reliability of the model data. Part 2 of this study will investigate the systematic trends of the fit of spectral values. In Part 1, it is shown that spatial analysis, the examination of distributions to reveal overall trends, and the careful choice of the appropriate statistical model to describe the fit of the wave model to buoy observations are all critical steps that must be added to verification processes. Part 2 demonstrates that looking closely at the fit of spectral values can reveal potentially vital issues for energy extraction. Better statistical validation gives the predictions of a particular resource assessment greater credibility or reveals areas where model accuracy must be improved.
Original languageEnglish
JournalInternational Journal of Marine Energy
Early online date15 Oct 2014
Publication statusPublished - 2014


  • Wave energy
  • Wave power
  • Resource assessment
  • Model validation
  • EMEC Test Site
  • WAM3
  • Numerical Modelling


Dive into the research topics of 'Verification within Wave Resource Assessments. Part 1: Statistical Analysis'. Together they form a unique fingerprint.

Cite this