Global extreme wave estimates and their sensitivity to the analysed data period and data sources

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AMAROUCHE K., AKPINAR A., Kamranzad B., Khames G.

Marine Structures, cilt.92, 2023 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 92
  • Basım Tarihi: 2023
  • Doi Numarası: 10.1016/j.marstruc.2023.103494
  • Dergi Adı: Marine Structures
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, PASCAL, Aerospace Database, Aquatic Science & Fisheries Abstracts (ASFA), Communication Abstracts, ICONDA Bibliographic, INSPEC, Metadex, Civil Engineering Abstracts
  • Anahtar Kelimeler: Annual maximum, Extreme value analysis, Generalized extreme value distribution, Generalized pareto distribution, Global extreme waves, Peak-over-threshold
  • Bursa Uludağ Üniversitesi Adresli: Evet

Özet

In the absence of wave measuring buoys operating over extended periods, wave hindcast data or satellite observations are indispensable for estimating global extreme wave heights. However, the results may depend on the analysed wind wave sources and the period's length. The sensitivity of the estimated extreme significant wave heights (SWH) to the analysed data sources and periods is investigated in this study. Global extreme wave heights are estimated using ECMWF Reanalysis v5 data (ERA5), global wave hindcast developed based on Simulating WAves Nearshore forced by the Japanese 55-year Reanalysis (SWAN-JRA55), satellite altimeter observations, and long-term wave buoy measurements. Both Annual Maximum fitting to the Generalized Extreme Value Distribution (AM-GEV) and Peaks Over Threshold fitted to the Generalized Pareto Distribution (POT-GPD) models are used. The results show that the global extreme SWH estimates considerably depend on the analysed data sources. The relative differences observed between the analysed data sources are >20% in large parts of the world. Thus, the relative differences in extreme SWH are mainly lower by increasing the analysed data periods. However, they can reach 30% and are more critical using AM-GEV. Besides, by comparing the extreme values from reanalysis and hindcast wave data to those from long-term wave measurements, underestimations of up to 2 m are observed for a return period of 100 years in the North-West Atlantic and North-East Pacific.