Oceanographic processes at coastal scales present a number of differences with respect to deep water oceanography, which result in higher prediction errors. In shallow water coastal domains the bottom topography, via the sea-bed boundary condition, exerts a strong control on the resulting wave and current fields. In addition to this, other factors need to be accounted for, such as the relevance of the tidal influence, stratification and mixing effects, land boundary condition (affecting the wind fields), the presence of distributed run off and point-wise river mouths, the effects of densely populated areas with many ongoing economic activities.
Moreover, the coupling between wind, waves, currents and sediments at limited scales, or even the choice of the numerical strategy (including the option between nested meshes, finite-difference or finite-element discretization, variable grid, etc.) may also play a critical role in the quality of the predictions. Coastal observations are therefore necessary to drive numerical models, combining point-wise data from multi variable buoys, high frequency radar images and a number of satellite images, the accuracy of which however tends to degrade as we get closer to the shoreline border.
These issues are even more relevant in a framework of changing climate, since coastal and transitional areas are strongly impacted both by the anthropogenic activities going on along the shores, and the ocean shaping the environment, as stressed by the IPCC last report. Because of the above mentioned reasons, and with the aim to identify also key-parameters that will allow to detect and monitor likely changes, it is timely to discuss recent advances in fields such as: integrated ocean-atmosphere-sediment modeling approaches and the physics of their coupling mechanisms; the hydrological, biogeochemical, geomorphological variability of coastal regions; the availability and use of coastal in-situ observations; and standards procedures and data formats to make data ready for use in an integrated ocean processes monitoring system.