Estimating return period wave heights and wind speeds using a seasonal point process model

I D Morton, J. Bowers, G. Mould

    Research output: Contribution to journalArticlepeer-review

    63 Citations (Scopus)


    A method of extreme value analysis is described which incorporates a model reflecting the seasonality of the environment. A point process model is employed with the arrival of storms described as a Poisson process and a generalised Pareto distribution to model the magnitude of the storm. Separate point process models are constructed for each season and then aggregated to provide a basis for estimating the return values. The construction of separate models, including the use of seasonal thresholds, ensures that more appropriate models are fitted to each season's data. The method also reflects the completeness of the environmental record, avoiding the bias that can result from missing data. The potential benefits of the approach include greater accuracy, robustness to missing data and the provision of seasonal return values for mobile systems deployed on a temporary basis. The method is demonstrated in estimating the N year significant wave heights and wind speeds in the northern North Sea. © 1997 Elsevier Science B.V.

    Original languageEnglish
    Pages (from-to)305-326
    Number of pages22
    JournalCoastal Engineering
    Issue number1-4
    Publication statusPublished - Jul 1997


    • Extreme values
    • Point process
    • Seasonality
    • Wave heights
    • Wind speeds


    Dive into the research topics of 'Estimating return period wave heights and wind speeds using a seasonal point process model'. Together they form a unique fingerprint.

    Cite this