Near real-time monitoring of significant sea wave height through microseism recordings: An application in the Ligurian Sea (Italy)

Ferretti, Gabriele; Barani, Simone; Scafidi, Davide; Capello, Marco; Cutroneo, Laura; Vagge, Greta; Besio, Giovanni

doi:10.1016/j.ocecoaman.2018.08.023

Cited by 14 publications

(32 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…4 illustrated for the hydroacoustic background, Fig. 5 shows that when the weather conditions deteriorate and the waveforms increase, the level of the hydrodynamic background amplitude increases [29,30,31]. The determination of hydroacoustic and hydrodynamic background levels will be an important factor in determining the detection threshold for vessels from hydroacoustic and hydrodynamic signals under severe weather conditions.…”

Section: Resultsmentioning

confidence: 99%

Detection of Floating Objects Based on Hydroacoustic and Hydrodynamic Pressure Measurements in the Coastal Zone

Buszman

Gloza

2020

Polish Maritime Research

View full text Add to dashboard Cite

The development of coastal infrastructure and related maritime transport necessitatesthe intensification of vessel traffic monitoring. Navigation systems used in this research are traditionally based on the information transmitted by radio waves. Marine traffic safety requires constant supervision carried out by dedicated systems, the operation of which may be limitedby difficult environmental conditions. The possibilities of supporting navigation systems with underwater observation systems are explored here. The research was carried out using an underwater measurement system. Local disturbances of the hydroacoustic and hydrodynamic field from the moving vessels were analysed. The potential for identifying a moving vessel, for example for offshore infrastructure security purposes, is demonstrated.

show abstract

Section: Resultsmentioning

confidence: 99%

Detection of Floating Objects Based on Hydroacoustic and Hydrodynamic Pressure Measurements in the Coastal Zone

Buszman

Gloza

2020

Polish Maritime Research

View full text Add to dashboard Cite

show abstract

Section: Description Of Wave Datamentioning

confidence: 93%

“…On the contrary, Ligurian Sea is one of the most active areas of cyclogenesis in the Mediterranean. Moreover, this area is characterized by very strong and rapid variability of meteorological conditions [80]. Given the original (random) sample of pairs of one linear and one directional variable ( , ), say { } =1 , the procedure of the adopted bootstrapping is summarized in the following steps for estimating the confidence intervals of the extreme value parameters:…”

Section: Description Of Wave Datamentioning

confidence: 99%

Directional Extreme Value Models in Wave Energy Applications

2020

View full text Add to dashboard Cite

A wide range of wave energy applications relies on the accurate estimation of extreme wave conditions, while some of them are frequently affected by directionality. For example, attenuators and terminators are the most common types of wave energy converters whose performance is highly influenced by their orientation with respect to the prevailing wave direction. In this work, four locations in the eastern Mediterranean Sea are selected with relatively high wave energy flux values and extreme wave heights are examined with wave direction as a covariate. The Generalized Pareto distribution is used to model the extreme values of wave height over a pre-defined threshold, with its parameters being expressed as a function of wave direction through Fourier series expansion. In order to be consistent with the analysis obtained from the independent fits for directional sectors, the estimation of parameters is based on a penalized maximum likelihood criterion that ensures a good agreement between the two approaches. The obtained results validate the integration of directionality in extreme value models for the examined locations and design values of significant wave height are provided with respect to direction for the 50- and 100-year return period with bootstrap confidence intervals.

show abstract

“…The monitoring of sea state is a fundamental task for economic activities in coastal areas, such as transportation, tourism, and design of infrastructures, e.g., [1,2]. In particular, the importance of monitoring sea wave height for marine risk assessment and mitigation is increasing day-by-day.…”

Section: Introductionmentioning

confidence: 99%

“…In this paper, by both statistical and machine learning approaches, we will explore the relationship between microseism amplitude, recorded by seismic stations located in Eastern Sicily (Italy), and the sea wave height in the Ionian Sea, Tyrrhenian Sea, and Sicily Channel. Following the idea by [2], the latter data have been provided by hindcast maps, which show several advantages with respect to other measured data, such as high spatial resolution, widespread coverage on large areas, and temporal continuity of the information (hindcast maps are always available, as they are not affected by instrument breakage). In particular, we will try to answer the question of whether, and to what extent, it is possible to reconstruct the spatial distribution of sea wave height by using microseisms recorded at distinct stations and in different frequency bands.…”

Section: Introductionmentioning

confidence: 99%

Unravelling the Relationship Between Microseisms and Spatial Distribution of Sea Wave Height by Statistical and Machine Learning Approaches

et al. 2020

View full text Add to dashboard Cite

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.

show abstract

Near real-time monitoring of significant sea wave height through microseism recordings: An application in the Ligurian Sea (Italy)

Cited by 14 publications

References 26 publications

Detection of Floating Objects Based on Hydroacoustic and Hydrodynamic Pressure Measurements in the Coastal Zone

Detection of Floating Objects Based on Hydroacoustic and Hydrodynamic Pressure Measurements in the Coastal Zone

Directional Extreme Value Models in Wave Energy Applications

Unravelling the Relationship Between Microseisms and Spatial Distribution of Sea Wave Height by Statistical and Machine Learning Approaches

Contact Info

Product

Resources

About