Suchergebnisse

Abstract. This study examines the wind-wave characteristics along the Emilia-Romagna coasts (northern Adriatic Sea, Italy) with a 10-year wave simulation for the period 2010–2019 performed with the high-resolution unstructured-grid WAVEWATCH III (WW3) coastal wave model. The wave parameters (significant wave height, mean and peak wave period, and wave direction) were validated with the in situ measurements at a coastal station, Cesenatico. In the coastal belt, the annual mean wave heights varied from 0.2–0.4 m, and the seasonal mean was highest for the winter period (>0.4 m). The Emilia-Romagna coastal belt was characterized by wave and spectra seasonal signals with two dominant frequencies of the order of 10 and 5–6 s for autumn and winter and 7–9 and 4 s for spring and summer. The wavelet power spectra of significant wave height for 10 years show considerable variability, having monthly and seasonal periods. This validated and calibrated data set enabled us to study the probability distributions of the significant wave height along the coasts and define a hazard index based on a fitted Weibull probability distribution function.

Abstract. Addressing coastal risks related to sea storms requires an integrative approach
which combines monitoring stations, forecasting models, early warning systems,
and coastal management and planning. Such great effort is sometimes possible
only through transnational cooperation, which becomes thus vital to face,
effectively and promptly, the marine events which are responsible for
damage impacting the environment and citizens' life. Here we present a
shared and interoperable system to allow a better exchange of and elaboration on
information related to sea storms among countries. The proposed integrated web
system (IWS) is a combination of a common data system for sharing ocean
observations and forecasts, a multi-model ensemble system, a geoportal, and
interactive geo-visualisation tools to make results available to the general
public. The multi-model ensemble mean and spread for sea level height and wave
characteristics are used to describe three different sea condition scenarios.
The IWS is designed to provide sea state information required for issuing coastal
risk alerts over the analysed region as well as for being easily integrated
into existing local early warning systems. This study describes the
application of the developed system to the exceptional storm event of
29 October 2018 that caused severe flooding and damage
to coastal infrastructure in the Adriatic Sea. The forecasted
ensemble products were successfully compared with in situ observations. The
hazards estimated by integrating IWS results in existing early warning systems
were confirmed by documented storm impacts along the coast of Slovenia,
Emilia-Romagna and the city of Venice. For the investigated event, the most
severe simulated scenario results provide a realistic and conservative
estimation of the peak storm conditions to be used in coastal risk management.

Abstract. This paper reviews the state of the art in storm surge forecasting and its particular application in the northern Adriatic Sea. The city of Venice already depends on operational storm surge forecasting systems to warn the population and economy of imminent flood threats, as well as help to protect the extensive cultural heritage. This will be more important in the future, with the new mobile barriers called MOSE (MOdulo Sperimentale Elettromeccanico, Experimental Electromechanical Module) that will be completed by 2021. The barriers will depend on accurate storm surge forecasting to control their operation. In this paper, the physics behind the flooding of Venice is discussed, and the state of the art of storm surge forecasting in Europe is reviewed. The challenges for the surge forecasting systems are analyzed, especially in view of uncertainty. This includes consideration of selected historic extreme events that were particularly difficult to forecast. Four potential improvements are identified: (1) improve meteorological forecasts, (2) develop ensemble forecasting, (3) assimilation of water level measurements and (4) develop a multimodel approach.