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Modeling non-stationarity in significant wave height over the Northern Indian Ocean.
- Source :
-
Stochastic Environmental Research & Risk Assessment . Oct2024, Vol. 38 Issue 10, p3823-3836. 14p. - Publication Year :
- 2024
-
Abstract
- Statistical descriptions of extreme met-ocean conditions are essential for the safe and reliable design and operation of structures in marine environments. The significant wave height ( H S ) is one of the most essential wave parameters for coastal and offshore structural design. Recent studies have reported that a time-varying component exists globally in the H S . Therefore, the non-stationary behavior of an annual maximum series of H S is important for various ocean engineering applications. This study aims to analyze the frequency of H S over the northern Indian Ocean by modeling the non-stationarity in the H S series using a non-stationary Generalized Extreme Value (GEV) distribution. The hourly maximum H S data (with a spatial resolution of 0.5° longitude × 0.5° latitude) collected from the global atmospheric reanalysis dataset of the European Centre for Medium-Range Weather Forecasts (ECMWF) is used for the study. To model the annual maximum series of H S using a non-stationary GEV distribution, two physical covariates (El-Ni n ~ o Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD)) and time covariates are introduced into the location and scale parameters of the GEV distribution. The return levels of various frequencies of H S are estimated under non-stationary conditions. From the results, average increases of 13.46%, 13.66%, 13.85%, and 14.02% are observed over the study area for the 25-year, 50-year, 100-year, and 200-year return periods, respectively. A maximum percentage decrease of 33.3% and a percentage increase of 167% are observed in the return levels of various return periods. The changes in the non-stationary return levels over time highlight the importance of modeling the non-stationarity in H S . [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 14363240
- Volume :
- 38
- Issue :
- 10
- Database :
- Academic Search Index
- Journal :
- Stochastic Environmental Research & Risk Assessment
- Publication Type :
- Academic Journal
- Accession number :
- 179970860
- Full Text :
- https://doi.org/10.1007/s00477-024-02775-3