The Project

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Earth Observation Advanced science Tools for Sea level Extreme Events (EOatSEE) is a project funded by ESA and proposed by a consortium of institutions and companies that are internationally recognized for their work in the Marine, Coastal and Earth Observation topics.  It aims to provide an advanced reconstruction of the relevant processes included in extreme sea level (ESL) events and its related coastal hazards, by taking advantage of the novel capabilities and synergies offered by the latest advances in EO technology.

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The solid scientific knowledge arising from EOatSEE therefore shall enhance the fundamental scientific understanding and predictive capacity of such events, as well as our potential to better assess the related risk and the vulnerability of coastal zones. Therefore, following an initial phase for scientific requirements consolidation, EOatSEE will address the following three main science cases domains, which represent the main drivers for the proposed work:

  • Science case 1Predictability: drivers of extreme sea level flooding hazards
  • Science case 2Process understanding: the cascade effect of extreme sea level events on long-term coastal evolution considering the dynamic morphological response
  • Science case 3Assessment and risk and vulnerability: the tipping points of coastal systems

To accomplish such scientific and technical objectives, EOatSEE methodological approach is divided in two main domains:

  • Short-term – where Science case 1 will be addressed using three distinct approaches: a high resolution downscaling process-based modelling approach (HRDW), together with the new EO-products implemented in the model chain; a linear summation empirical modelling downscaling method (LSDW), considering coastal morphology as passive (no changes along time); a reduced complexity forecasting coastal evolution model (ForCE), which adds the capacity to simulate active morphology (morphological response along the time, due to changes in water levels and waves).
  • Long-term – where Science cases 1 and 2 will be addressed using the LSDW and ForCE approaches, considering the extremely high computational cost of performing long-term high-resolution numerical modelling as in HRDW; a combination of both short-term and long-term approaches shall also be employed to address Science case 3.