Time series modeling of significant wave height in multiple scales, combining various sources of data

In the present paper, a composite stochastic model is formulated and validated, resolving the state‐by‐state, seasonal and interannual variabilities of HS. The model is a combination of two cyclostationary random processes modeling the variability of mean monthly values and mean monthly standard deviations, respectively, and of a stationary random process modeling the residual, state‐by‐state, variability. In this way, the time series of significant wave height is given the structure of a multiple‐scale composite stochastic process. The present model is a generalization of the nonstationary stochastic modeling introduced by the authors in previous works.