Sea waves constitute a natural phenomenon with a great impact on human activities, and their monitoring is essential for meteorology, coastal safety, navigation, and renewable energy from the sea. Therefore, the main measurement techniques for their monitoring are here reviewed, including buoys, satellite observation, coastal radars, shipboard observation, and microseism analysis. For each technique, the measurement principle is briefly recalled, the degree of development is outlined, and trends are prospected. The complementarity of such techniques is also highlighted, and the need for further integration in local and global networks is stressed.

The Italian Data Buoy Network consists of 15 oceanographic buoys, deployed along Italian coasts, on a seabed 100 meters deep. It collects...

Global warming is making extreme wave events more intense and frequent. Hence, the importance of monitoring the sea state for marine risk assessment and mitigation is increasing day-by-day. In this work, we exploit the ubiquitous seismic noise generated by energy transfer from the ocean to the solid earth (called microseisms) to infer the sea wave height data provided by hindcast maps. To this aim, we use a combined approach based on statistical analysis and machine learning. In particular, a random forest model shows very promising results in the spatial and temporal reconstruction of sea wave height by microseisms. The observed dependence of input importance from the distance sea grid cell-seismic station suggests how the reliable monitoring of the sea state in a wide area by microseisms needs data recorded by dense networks, comprising stations evenly distributed along the coastlines.

In this work, we investigated the microseism recorded by a network of broadband seismic stations along the coastline of Eastern Sicily. Microseism is the most continuous and ubiquitous seismic signal on Earth and is mostly generated by the ocean–solid earth interaction. On the basis of spectral content, it is possible to distinguish three types of microseism: primary, secondary, and short-period secondary microseism (SPSM). We showed how most of the microseism energy recorded in Eastern Sicily is contained in the secondary and SPSM bands. This energy exhibits strong seasonal patterns, with maxima during the winters. By applying array techniques, we observed how the SPSM sources are located in areas of extended shallow water depth: the Catania Gulf and a part of the Northern Sicily coastlines. Finally, by using the significant wave height data recorded by two buoys installed in the Ionian and Tyrrhenian Seas, we developed an innovative method, selected among up-to-date machine learning techniques (MLTs), able to reconstruct the time series of sea wave parameters from microseism recorded in the three microseism period bands by distinct seismic stations. In particular, the developed model, based on random forest regression, allowed estimating the significant wave height with a low average error (∼0.14–0.18 m). The regression analysis suggests that the closer the seismic station to the sea, the more information concerning the sea state are contained in the recorded microseism. This is particularly important for the future development of an experimental monitoring system of the sea state conditions based on microseism recordings.

Meteo-marine data are necessary and useful for all tasks and scientific activities of national interest involving the protection, enhancement and improvement of the marine environment. The Institute for Environmental Protection and Research (ISPRA) maintains and manages two monitoring networks in order to gather all physical parameters needed in defining the state of Central Mediterranean Sea: the Sea Level Measurement Network (Rete Mareografica Nazionale, RMN) and the Sea Waves Measurement Network (Rete Ondametrica Nazionale, RON). The RMN includes 36 coastal measurement stations; real-time series of sea-level and meteorological parameters are collected every minute. Tide gauges mainly collect sea level, air and water temperatures, wind speed and direction and relative humidity. The RON consists of 15 real-time directional buoys uniformly distributed along the Italian coastline. They collect the main physical parameters such as significant and maximum wave height, peak and mean wave period, wave direction, sea surface temperature (SST), air temperature, wind speed and direction, atmospheric pressure and relative humidity. In this paper attention is focused on statistical analysis in order to describe wave climates, extreme events, tsunami, sea storms and storm surges and related meteorological information. The statistics taken into consideration are mainly the joint frequency distribution of significant wave heights with respect to direction and peak and mean wave periods. Extreme-event analysis is made through the peak over threshold (POT) method and the generalised Pareto distribution (GPD). Finally, sea-level time series analyses are used to highlight examples of meteorological events (such as tsunami) through harmonic and residual analysis.