OS2.2 | Oceanography at coastal scales. Modelling, coupling, observations and applications
EDI
Oceanography at coastal scales. Modelling, coupling, observations and applications
Convener: Agustín Sánchez-Arcilla | Co-conveners: Joanna Staneva, Sandro Carniel, Davide Bonaldo, Manel Grifoll

Coastal oceanographic processes present important differences with deep water oceanography, resulting in higher prediction errors, where topo-bathymetry in shallow areas exerts a strong control on hydrodynamic fields, further modified by stratification, land boundaries and coastal infrastructure. Predictability is limited by strong non-linear interactions (e.g. breaking waves, nearshore circulation and sediment fluxes), choice of numerical strategies (e.g. nested meshes, finite-elements or smooth-particle simulations) or modulations typical of restricted domains (e.g. seiching or vegetation filtering). Coastal observations (in-situ and remote) are therefore necessary to enhance numerical models, where the advent of new satellite capabilities (e.g. Sentinel resolution and sensors) and modelling advances (e.g. coupling or unstructured grids), together with enhanced coastal observatories, are leading to qualitative advances for coastal oceanography applications. Coastal analyses under future scenarios become even more challenging, since transitional areas are more strongly impacted by changing climates (e.g. changing domains due to sea-level rise). For these reasons, it is timely to discuss recent advances in: a) coastal coupled hydro-morpho-ecological modelling at different scales; b) coastal aggregation of in-situ/satellite/numerical data from different sources; c) knowledge-based coastal applications, including the assessment of nature-based interventions; d) use of novel approaches, such as data assimilation or machine learning; and e) uncertainties in coastal decision-making. Building on these challenges, we invite presentations on coastal modelling, data assimilation, boundary effects or operational coastal predictions with/without interactions with Nature-based or traditional interventions. Contributions tackling open questions on non-linear response functions, artificial intelligence or big data for coastal applications are welcome. These coastal topics should conform a fruitful session for discussing coastal oceanography applications, including conventional and nature-based interventions under climate change. We offer the possibility, for interested authors, to submit evolved versions of their presentations to the currently open special issue in Ocean Sciences (see https://www.ocean-science.net/articles_and_preprints/scheduled_sis.html).

Coastal oceanographic processes present important differences with deep water oceanography, resulting in higher prediction errors, where topo-bathymetry in shallow areas exerts a strong control on hydrodynamic fields, further modified by stratification, land boundaries and coastal infrastructure. Predictability is limited by strong non-linear interactions (e.g. breaking waves, nearshore circulation and sediment fluxes), choice of numerical strategies (e.g. nested meshes, finite-elements or smooth-particle simulations) or modulations typical of restricted domains (e.g. seiching or vegetation filtering). Coastal observations (in-situ and remote) are therefore necessary to enhance numerical models, where the advent of new satellite capabilities (e.g. Sentinel resolution and sensors) and modelling advances (e.g. coupling or unstructured grids), together with enhanced coastal observatories, are leading to qualitative advances for coastal oceanography applications. Coastal analyses under future scenarios become even more challenging, since transitional areas are more strongly impacted by changing climates (e.g. changing domains due to sea-level rise). For these reasons, it is timely to discuss recent advances in: a) coastal coupled hydro-morpho-ecological modelling at different scales; b) coastal aggregation of in-situ/satellite/numerical data from different sources; c) knowledge-based coastal applications, including the assessment of nature-based interventions; d) use of novel approaches, such as data assimilation or machine learning; and e) uncertainties in coastal decision-making. Building on these challenges, we invite presentations on coastal modelling, data assimilation, boundary effects or operational coastal predictions with/without interactions with Nature-based or traditional interventions. Contributions tackling open questions on non-linear response functions, artificial intelligence or big data for coastal applications are welcome. These coastal topics should conform a fruitful session for discussing coastal oceanography applications, including conventional and nature-based interventions under climate change. We offer the possibility, for interested authors, to submit evolved versions of their presentations to the currently open special issue in Ocean Sciences (see https://www.ocean-science.net/articles_and_preprints/scheduled_sis.html).