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Wave extreme events can be understood as the combination of storm-intensity, directionality and intra-time distribution. However, the dependence structure among these factors is still unclear. A methodology has been developed to model wave-storms whose components are linked together. The model is composed by three parts: an intensity module, a wave directionality module, and a intra-time distribution module. In the Storm-intensity sub-model, generalized Pareto distributions and hierarchical Archimedean copulas have been used to characterize the storm energy, unitary energy, peak wave-period and duration. In the Directionality and the Intra-time sub-models, the wave direction (at the peak of the storm) and the storm growth-decay rates are linked to the variables from the intensity model, respectively. The model is applied to the Catalan coast (NW Mediterranean). The outcomes denote spatial patterns that coincide with the state of knowledge. The proposed methodology is able to provide boundary conditions for wave and near-shore studies, saving computational time and establishing the dependence of the proposed variables. Such synthetic storms reproduce the inter-variable co-dependence of the original data.

Storm Gloria (January 19–24, 2020) hit the NW Mediterranean Sea with heavy rainfall, strong easterly winds, and very high waves, causing structural damages and 13 fatalities. The low-lying Ebro Delta (ED) region was severely inundated, ruining rice fields and seaside promenades. A variety of Copernicus Marine Environment Monitoring Service (CMEMS) modeling and observational products were jointly used to examine the fingerprint of Gloria and the response of the upper oceanic layer. According to the results, Gloria can be interpreted as a high-impact once-in-a-decade metocean event where various historical records were beaten. The 99th percentile of several parameters (wind speed, significant wave height, wave period, and surface current velocity), derived from long-term observational time series, was persistently exceeded. The atmospheric surge, albeit not negligible, exerted a secondary role in ED. The ability of a high-frequency radar deployed in this region (HFR-ED) to characterize the striking features of the storm was quantified from both waves and circulation aspects. Consistent radar current observations were subsequently compared against the 5-day-ahead forecast of CMEMS Iberia-Biscay-Ireland (IBI) regional ocean model to determine, from an Eulerian perspective, the strengths and shortcomings in its predictive capabilities. Time-averaged maps of surface circulation, superimposed with fields of Instantaneous Rate of Separation (IROS), were derived to resolve flow features and identify areas of elevated particles dispersion, respectively. The mean and P99 values of IROS almost doubled the historical statistics in the vicinity of the northern Ebro hemidelta. Although IBI predicted moderately well basic features of the storm-induced circulation, results suggests that coastal transport processes, likely modulated by wave-current interactions, were not fully captured. Furthermore, current estimations from other two radar systems, overlooking immediate choke points like the Ibiza Channel and the Strait of Gibraltar, evidenced Gloria’s remote-effect in the anomalous circulation patterns observed, that altered the usual water exchanges between adjacent sub-basins. Finally, three-dimensional outcomes from IBI were used to elucidate the impact of this moving storm at different depth levels. Data analyses illustrated that Gloria caused a large increase in kinetic energy and a significant deepening of the mixed layer depth.

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We identify the mechanisms controlling fine deposits on the inner-shelf in front of the Besos River, in the northwestern Mediterranean Sea. This river is characterized by a flash flood regime discharging large amounts of water (more than 20 times the mean water discharge) and sediment in very short periods lasting from hours to few days. Numerical model output was compared with bottom sediment observations and used to characterize the multiple spatial and temporal scales involved in offshore sediment deposit formation. A high-resolution (50 m grid size) coupled hydrodynamic-wave-sediment transport model was applied to the initial stages of the sediment dispersal after a storm-related flood event. After the flood, sediment accumulation was predominantly confined to an area near the coastline as a result of preferential deposition during the final stage of the storm. Subsequent reworking occurred due to wave-induced bottom shear stress that resuspended fine materials, with seaward flow exporting them toward the midshelf. Wave characteristics, sediment availability, and shelf circulation determined the transport after the reworking and the final sediment deposition location. One year simulations of the regional area revealed a prevalent southwestward average flow with increased intensity downstream. The circulation pattern was consistent with the observed fine deposit depocenter being shifted southward from the river mouth. At the southern edge, bathymetry controlled the fine deposition by inducing near-bottom flow convergence enhancing bottom shear stress. According to the shortterm and long-term analyses, a seasonal pattern in the fine deposit formation is expected.

Extreme events, such as wave-storms, need to be characterized for coastal infrastructure design purposes. Such description should contain information on both the univariate behaviour and the joint-dependence of storm-variables. These two aspects have been here addressed through generalized Pareto distributions and hierarchical Archimedean copulas. A non-stationary model has been used to highlight the relationship between these extreme events and non-stationary climate. It has been applied to a Representative Concentration Pathway 8.5 Climate-Change scenario, for a fetch-limited environment (Catalan Coast). In the non-stationary model, all considered variables decrease in time, except for storm-duration at the northern part of the Catalan Coast. The joint distribution of storm variables presents cyclical fluctuations, with a stronger influence of climate dynamics than of climate itself.Peer ReviewedPostprint (author's final draft