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1

Tidal Level Predictions in Reference to Their Datum, Based on Particular, Selective Sources

Kabzinski B.

TransNav : International Journal on Marine Navigation and Safety of Sea Transportation

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2008

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Vol. 2, no. 2

149--154

EN

The article presents differences between tidal datum of predictions taken from six official data sources (British, American and Caribbean comprising both paper and electronic form) for three pairs of ports located on the Atlantic coast of North, Central and South America. Two day of predictions represent spring and neap tide. It can be treated as a continuation, a deeper stage of works focused on tidal comparisons. The most essential trial of tidal datum unification for particular ports gives the more adequate base for comparison of Height Deviations from reference values (for particular ports: local or mean) and shows wide variety of the results.

2

The Role of Operational Ocean Forecasting in E-Navigation

Graff J.

TransNav : International Journal on Marine Navigation and Safety of Sea Transportation

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2008

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Vol. 2, no. 3

259--262

EN

Advances in ocean modelling have led to improved performance for operational ocean forecasting and the availability of continuously reliable forecast information for certain ocean regions of the world. Although such forecasts are being increasingly adopted into a wide range of services across the maritime industry they have not yet been considered as candidates to supplement or to substitute conventional tide tables for navigation use. The issue is important in the context of climate change and the added uncertainty now placed on the use of conventional tide table for navigation in complex coastal waters. In the context of e-navigation it is timely to begin to explore the issue and examine how such forecasts might be used and adopted. This requires closer connectivity between ocean forecasting and navigation communities and the involvement of overarching organisations such as IMO and I GOOS. This paper raises the issue and opens the debate.

3

Numerical Simulation of Nonlinear Water Wave Problems

Lo D. C., Hu Jia-Shen, Lin I-Fu

TransNav : International Journal on Marine Navigation and Safety of Sea Transportation

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2008

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Vol. 2, no. 2

137--142

EN

The main purpose of present paper aims at the establishment of a numerical model for solving the nonlinear water wave problems. The model is based on the Navier-Stokes equations with the consideration of a free-surface through the streamfunction-vorticity formulation. The main advantage of the streamfunction-vorticity formulation is that pressure field can be eliminated from the Navier-Stokes equations. To demonstrate the model feasibility, the present studies are first concentrated on problems including the collision of two solitary waves with different amplitudes, and the overtaking collision of two solitary waves. Then, the model is also applied to a solitary wave passes over the submerged obstacle in a viscous fluid. Finally, the application of present study is also to simulate the generation of solitary waves by underwater moving object. All examples give very promising results, those applications reveal that present formulation is a very powerful approach to simulate the fully nonlinear water wave problems.

4

A Required Data Span to Detect Sea Level Rise

Niedzielski T., Kosek W.

TransNav : International Journal on Marine Navigation and Safety of Sea Transportation

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2008

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Vol. 2, no. 2

143--147

EN

Altimetric measurements indicate that the global sea level rises about 3 mm/year, however, in various papers different data spans are adopted to estimate this value. The minimum time span of TOPEX/Poseidon (T/P) and Jason-1 (J-1) global sea level anomalies (SLA) data required to detect a statisti-cally significant trend in sea level change was estimated. Seeking the trend in the global SLA data was per-formed by means of the Cox-Stuart statistical test. This test was supported by the stepwise procedure to make the results independent of the starting data epoch. The probabilities of detecting a statistically significant trend within SLA data were computed in the relation with data spans and significance levels of the above-mentioned test. It is shown that for the standard significance level of 0.05 approximately 5.5 years of the SLA data are required to detect a trend with the probability close to 1. If the seasonal oscillations are removed from the combined T/P and J-1 SLA data, 4.3 years are required to detect a statistically significant trend with a probability close to 1. The estimated minimum time spans required to detect a trend in sea level rise are ad-dressed to the problem of SLA data predictions. In what follows, the above-mentioned estimate is assumed to be minimum data span to compute the representative sample of SLA data predictions. The forecasts of global mean SLA data are shown and their mean prediction errors are discussed.