A novel method for long-term time series analysis of significant wave height

Abstract

In order to structure the complex nature of the significant wave height time series, Autoregressive Integrated Moving Average model of order (p,1,0) was applied. Each step which is essential for precise modeling is covered comprehensively. First, the stationarity of given time series of SWH with its 1st order difference were checked. Akaike's Information Criteria and Bayesian Information Criteria for each model were calculated thereafter, in order to sort tentative models. And then, Ljung-Box tests were carried out on the residuals of each model to verify whether the residuals show autocorrelation. Through these processes, the optimal models for each time spans were measured. Furthermore, forecasted time series of significant wave height from Monte-Carlo simulations of each model have proven the utility of the proposed method as it mostly complies with the observed time series of significant wave height.