2022 CSDMS meeting-095

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Developments towards global coupled ocean modelling of waves and storm surges.

Guillermo García-Sánchez, CSIC Madrid , Spain. guillermo.garcia@icmat.es
Lorenzo Mentaschi, University of Bologna Bologna , Italy. lorenzo.mentaschi@unibo.it
Michalis Vousdoukas, Joint Research Centre (JRC) Ispra , Italy. vousdoukas@gmail.com
Tomas Fernandez Montblanc, Universidad de Cadiz Cadiz , Spain. tomas.fernandez@uca.es
Aaron Roland, GMX , Germany. aaronroland@gmx.de
Luc Feyen, Joint Research Centre Ispra , Italy. Luc.FEYEN@ec.europa.eu

[[CSDMS meeting abstract::Global warming is expected to drive increasing extreme sea levels (ESLs) and flood risk along the world’s coastlines [1]. Thus, reliable models are needed to better understand extreme coastal events. In this work, we analyse the performance of a coupled ocean model for simulating waves and storm surges, on a global mesh with a resolution varying from about 50 km offshore, to about 2 km nearshore. The model system consists of the Semi-implicit Cross-scale Hydroscience Integrated System Model (SCHISM) [2,3] two-way coupled with the 3rd-generation spectral wave model (WWM-V) [4]. The hydrodynamic component provides the wave model with current velocities and sea levels, while the sea surface roughness is estimated by WWM-V are passed back to SCHISM. The wave model was updated with developments to improve its numerical scalability and to take into account the energy dampening of unresolved islands and ice, using the Unresolved Obstacles Source Term (UOST) methodology [5]. The modelling system was forced with hourly data from ERA5, more specifically wind at 10 m above the sea surface, sea-level pressure, and sea ice concentration, with the aim of developing a hindcast from 2000 to present. Here we present an evaluation of the model skill versus satellite altimeters, buoys and tidal gauges, finding for the waves an overall Normalized Bias (NBI) of -2% and Normalized Root Mean Squared Error (NRMSE) of 17%, while for sea levels the Root Mean Squared Error (RMSE) is 0.099 m and BIAS 0.007 m.

  1. Vousdoukas, M. I., et al (2018). Global probabilistic projections of extreme sea levels show intensification of coastal flood hazard. Nature communications, 9(1), 1-12.
  2. Zhang, Y. and Baptista, A.M. (2008) SELFE: A semi-implicit Eulerian-Lagrangian finite-element model for cross-scale ocean circulation", Ocean Modelling, 21(3-4), 71-96.
  3. Zhang, Y., et al (2016) Seamless cross-scale modeling with SCHISM, Ocean Modelling, 102, 64-81.
  4. Roland, A. (2008). Development of WWM II: Spectral wave modelling on unstructured meshes (Doctoral dissertation, Ph. D. thesis, Technische Universität Darmstadt, Institute of Hydraulic and Water Resources Engineering).
  5. Mentaschi, L., et al. (2020). Assessment of global wave models on regular and unstructured grids using the Unresolved Obstacles Source Term. Ocean Dynamics, 70(11), 1475-1483.]]