Modeling non-stationarity in significant wave height over the Northern Indian Ocean

• Published in: Stochastic environmental research and risk assessment 2024-10, Vol.38 (10), p.3823-3836
• Main Authors: Dhanyamol, P., Agilan, V., KV, Anand
• Format: Article
• Language: English
• Subjects: Aquatic Pollution; Chemistry and Earth Sciences; Coastal engineering; Coastal structures; Computational Intelligence; Computer Science; Cyclones; Dipoles; Earth and Environmental Science; Earth Sciences; El Nino; Environment; Environmental research; Extreme values; Global warming; Marine environment; Math. Appl. in Environmental Science; Ocean engineering; Ocean models; Oceans; Offshore structures; Original Paper; Parameter estimation; Physics; Probability Theory and Stochastic Processes; Risk assessment; Southern Oscillation; Spatial discrimination; Spatial resolution; Statistical analysis; Statistical models; Statistics for Engineering; Structural design; Structural engineering; Waste Water Technology; Water Management; Water Pollution Control; Wave height; Weather forecasting
• ISSN: 1436-3240; 1436-3259
• DOI: 10.1007/s00477-024-02775-3

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 .