No abstract

In January 2020, the storm Gloria hit the Western Mediterranean Sea causing severe coastal damages, destruction of infrastructures, flooding and several casualties. This extreme event was characterized by strong Eastern winds, record-breaking waves heights and periods, and a storm surge that locally beat the record along Valencia’s coastline. This paper analyses the dynamic evolution of sea level during this storm. The study employs both the in situ data and the operational forecasts of the PORTUS early warning system. Tide gauge data are analyzed on the different temporal scales that contribute to total sea level: long-term and seasonal, tides and storm surges, and higher frequency oscillations. It was found that, due to the unusual long wave periods, infragravity waves were generated and dominate the high frequency energy band, contributing significantly to extreme sea level records. This is a relevant finding, since this kind of oscillations are usually associated with larger basins, where swell can develop and propagate. The impact of sea level rise is also analyzed and considered relevant. A multi-model ensemble storm surge forecasting system is employed to study the event. The system was able to correctly forecast the surge, and the measured data were always inside the confidence bands of the system. The differences of the results obtained by the available operational forecasting system integrated into the ensemble, including those from Copernicus Marine Service, are described. All the models provided useful forecasts during the event, but differences with measured data are described and connected with the known limitations in physics (for example, barotropic vs. baroclinic) and set-up of the models (model domain, lack of tides and different inverse barometer implementations at the open boundaries amongst others).

In the last decades, car sharing has been a tool for city planners to reduce private car traffic and pollution in big urban areas. The emergence of the ICTs (Information and Communication Technologies), together with the development of the collaborative economy, has allowed for the birth of the new Free-Floating Carsharing (FFCS): A more flexible type of carsharing, in which electric cars can be used. Little research has been devoted using real FFCS flows data, to the FFCS impacts on user behavior and even on the public transport system thus far. Furthermore, in big metropolitan areas, central rail stations should promote modal interchanges, including new modes of electric FFCS systems. The aim of this paper is to design a web-based platform to collect and analyze FFCS demand on the surrounding areas of rail stations and makes a proposal to provide these systems with electrical recharging energy obtained from the regenerative braking of high-speed trains. This case study includes Atocha and Chamartín Central Stations in Madrid (Spain). Scientific evidence shows a high demand of FFCS cars at central rail stations and a trip profile with a short time duration linked to the closest districts of rail stations.