Environmental contours describing extreme sea states are generated as the input for numerical or physical model simulations as a part of the standard current practice for designing marine structures to survive extreme sea states. Such environmental contours are characterized by combinations of significant wave height (H s ) and energy period (T e ) or peak period (T p ) values calculated for a given recurrence interval using a set of data based on hindcast simulations or buoy observations over a sufficient period of record. The use of the inverse first-order reliability method (I-FORM) is standard design practice for generating environmental contours. This paper develops enhanced methodologies for data analysis prior to the application of the I-FORM, including the use of principal component analysis (PCA) to create an uncorrelated representation of the variables under consideration as well as new distribution and parameter fitting techniques. These modifications better represent the measured data and, therefore, should contribute to the development of more realistic representations of environmental contours of extreme sea states for use in survivability analysis for marine structures.

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A wide range of methods have been proposed for the derivation of environmental contours for marine structures that must meet reliability targets. An environmental contour is a set of joint extremes of environmental conditions associated with a target return period. In general, environmental contour methods help with the prediction of some future critical combinations of environmental conditions (e.g., wind, waves, current) at a location of interest based on a limited dataset, thus allowing designers to ensure a prescribed structural reliability. In fact, some of these contour methods are specifically recommended by technical specifications and standards as part of a design process. This paper outlines the rules and procedures for a collaborative benchmarking exercise — focused on open comparison — in which researchers are invited to develop and present their own contour derivation approaches based on common datasets that will be available to all. Hindcast and observational datasets are considered and two exercises are planned: One focuses on applying environmental contour methods to a wide range of datasets and the other focuses on uncertainty characterization. Besides describing the benchmark’s methodology, this paper presents baseline results of computed contours following current recommendations. The overall goals of this endeavor are: (i) to work towards the development of more robust statistical models and contour construction methods, (ii) to encourage increased discussion in the international research community and among practitioners, and (iii) to support ongoing efforts to improve technical specifications and standards.