The sea state plays an important role in oshore- and marine operations.It affects both direct costs as well as risks for human and/or materialloss. A better understanding of the present-, near-future-, and far-futuresea states will increase efficiency and safety in shipping since it allowa ship to reroute to a safer and/or more cost effective route. In the off-shore industry it allows for minimizing downtime and aids in planningthe construction of new offshore sites.Due to the complex nature of the sea state, its spatial distribution overa large region of ocean should be modeled using a probabilistic model.In this way, uncertainties due to lack of information and/or computingpower can be quantified and decisions can be taken based on both whatis known and what is not known.We analyze such a spatial probabilistic model in order to assess its abilityto predict the significant wave height in the whole north Atlantic basedonly on measurements on a small line path, i.e., conditional prediction.This work is relevant for several applications, for instance data assimilation,oceanographic forecasting, and routing of ships.
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