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Results from the Collaborative Computational Project in Wave Structure Interaction (CCP-WSI) Blind Test Series 3 are presented. Participants, with numerical methods, ranging from low-fidelity linear models to high-fidelity Navier-Stokes (NS) solvers, simulate the interaction between focused waves and floating structures without prior access to the physical data. The waves are crest-focused NewWaves with various crest heights. Two structures are considered: a hemispherical-bottomed buoy and a truncated cylinder with a moon-pool; both are taut-moored with one linear spring mooring. To assess the predictive capability of each method, numerical results for heave, surge, pitch and mooring load are compared against corresponding physical data. In general, the NS solvers appear to predict the behaviour of the structures better than the linearised methods but there is considerable variation in the results (even between similar methods). Recommendations are made for future comparative studies and development of numerical modelling standards.

The seasonal sea level variations observed from tide gauges over 1900–2013 and gridded satellite altimeter product AVISO over 1993–2013 in the northwest Pacific have been explored. The seasonal cycle is able to explain 60–90% of monthly sea level variance in the marginal seas, while it explains less than 20% of variance in the eddy‐rich regions. The maximum annual and semiannual sea level cycles (30 and 6 cm) are observed in the north of the East China Sea and the west of the South China Sea, respectively. AVISO was found to underestimate the annual amplitude by 25% compared to tide gauge estimates along the coasts of China and Russia. The forcing for the seasonal sea level cycle was identified. The atmospheric pressure and the steric height produce 8–12 cm of the annual cycle in the middle continental shelf and in the Kuroshio Current regions separately. The removal of the two attributors from total sea level permits to identify the sea level residuals that still show significant seasonality in the marginal seas. Both nearby wind stress and surface currents can explain well the long‐term variability of the seasonal sea level cycle in the marginal seas and the tropics because of their influence on the sea level residuals. Interestingly, the surface currents are a better descriptor in the areas where the ocean currents are known to be strong. Here, they explain 50–90% of interannual variability due to the strong links between the steric height and the large‐scale ocean currents.

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