Spatially distributed sea wave measurements

In recent years, there has been growing interest in remote and proximal observation of sea surface waves. This has been partially driven by new technologies allowing the characterization of wave fields in both their spatial and temporal aspects. Typical examples are radar systems and stereo-imaging that permit remote monitoring of oceanic waves (from satellites, platforms, or vessels) with remarkable accuracy and range of use. These new exciting possibilities usually come at the price of being relatively harder to master with respect to traditional “point-like” approaches providing measurements limited to a temporal perspective. This difficulty is not restricted to the technology itself (see, for example, the delicate camera-calibration process required in stereo-imaging) but also on how to properly process, analyze, and assimilate spatio-temporal data. Therefore, in this Special Issue, we decided to embrace a wide range of topics that have led a multitude of multi-disciplinary works in the recent past, including: Wave mechanics and sea surface dynamics; Analysis of the wave climate and its extremes; Data fusion and signal processing; Statistical and probabilistic methods; Assessment of wave models. We did our best to propose recent advancements, not only on the technological aspect of spatially distributed sea waves acquisition but also on the characterization of wave statistics from measured and assimilated data. For the former aspect, we included the work of Vieira et al. [1], proposing the first cheap and simple stereo-based technique to estimate the 3D sea surface elevation from inexpensive smartphones. For the latter, the paper of Serebryany et al. [2] investigates internal waves on a narrow steep shelf of the northeastern coast of the Black Sea using the spatial antenna of line temperature sensors. We also included a discussion on space-time wave extremes in the paper of Benetazzo et al. [3] and a comparison of assimilated coastal wave data by Yukiharu Hisaki [4]. Finally, the work of Ciurana and Aguilar [5] provides an overview of how an ensemble of meteorological buoys and citizen science data can help economic activities to achieve optimal performances (in a case study, to predict optimal surfing days in the Iberian Peninsula). We hope that these works will be interesting both for researchers already working on this topic and for those who want to embrace the new possibilities offered by modern sea wave acquisition techniques

Wave climate of the Adriatic Sea: a future scenario simulation

Abstract. We present a study on expected wind wave severity changes in the Adriatic Sea for the period 2070–2099 and their impact on extremes. To do so, the phase-averaged spectral wave model SWAN is forced using wind fields computed by the high-resolution regional climate model COSMO-CLM, the climate version of the COSMO meteorological model downscaled from a global climate model running under the IPCC-A1B emission scenario. Namely, the adopted wind fields are given with a horizontal resolution of 14 km and 40 vertical levels, and they are prepared by the Italian Aerospace Research Centre (CIRA). Firstly, in order to infer the wave model accuracy in predicting seasonal variability and extreme events, SWAN results are validated against a control simulation, which covers the period 1965–1994. In particular, numerical predictions of the significant wave height Hs are compared against available in-situ data. Further, a statistical analysis is carried out to estimate changes on wave storms and extremes during the simulated periods (control and future scenario simulations). In particular, the generalized Pareto distribution is used to predict changes of storm peak Hs for frequent and rare storms in the Adriatic Sea. Finally, Borgman's theory is applied to estimate the spatial pattern of the expected maximum wave height Hmax during a storm, both for the present climate and that of the future scenario. Results show a future wave climate in the Adriatic Sea milder than the present climate, even though increases of wave severity can occur locally

Vegetation cover analysis using a low budget hyperspectral proximal sensing system

This report describes the implementation of a hyperspectral proximal sensing low-budget acquisition system and its application to the detection of terrestrian vegetation cover anomalies in sites of high environmental quality. Anomalies can be due to stress for lack of water and/or pollution phenomena and weed presence in agricultural fields. The hyperspectral cube (90-bands ranging from 450 to 900 nm) was acquired from the hill near Segni (RM), approximately 500 m far from the target, by means of electronically tunable filters and 8 bit CCD cameras. Spectral libraries were built using both endmember identification method and extraction of centroids of the clusters obtained from a k-means analysis of the image itself. Two classification methods were applied on the hyperspectral cube: Spectral Angle Mapper (hard) and Mixed Tuned Matching Filters (MTMF). Results show the good capability of the system in detecting areas with an arboreal, shrub or leafage cover, distinguishing between zones with different spectral response. Better results were obtained using spectral library originated by the k-means method. The detected anomalies not correlated to seasonal phenomena suggest a ground true analysis to identify their origin

On the Groupiness and Intermittency of Oceanic Whitecaps

The enhancement of wave breaking activity during wave group passage is investigated using coherent field observations of the instantaneous sea surface elevation and whitecap coverage from platform-based stereo video measurements in the central North Sea. Passing wave groups are shown to be associated with a two to threefold enhancement in the probability distribution of total whitecap coverage W whereas the enhancement of active whitecap coverage WA is approximately fivefold. Breaking time scales and intermittency characteristics are also investigated with the inclusion of a secondary data set of W and WA observations collected during a research cruise in the North Pacific. The time scale analysis suggests a universal periodicity in wave breaking activity within a representative sea-surface area encompassing approximately one dominant wave crest. The breaking periodicity is shown to be closely linked to the peak period of the dominant wave components, suggesting that long-wave modulation of wave breaking is a predominant mechanism controlling the intermittency of wave breaking across scales.publishedVersio

A physics-driven CNN model for real-time sea waves 3D reconstruction

One of the most promising techniques for the analysis of Spatio-Temporal ocean wave fields is stereo vision. Indeed, the reconstruction accuracy and resolution typically outperform other approaches like radars, satellites, etc. However, it is computationally expensive so its application is typically restricted to the analysis of short pre-recorded sequences. What prevents such methodology from being truly real-time is the final 3D surface estimation from a scattered, non-equispaced point cloud. Recently, we studied a novel approach exploiting the temporal dependence of subsequent frames to iteratively update the wave spectrum over time. Albeit substantially faster, the unpre-dictable convergence time of the optimization involved still prevents its usage as a continuously running remote sensing infrastructure. In this work, we build upon the same idea, but investigat-ing the feasibility of a fully data-driven Machine Learning (ML) approach. We designed a novel Convolutional Neural Network that learns how to produce an accurate surface from the scattered elevation data of three subsequent frames. The key idea is to embed the linear dispersion relation into the model itself to physically relate the sparse points observed at different times. Assuming that the scattered data are uniformly distributed in the spatial domain, this has the same effect of increasing the sample density of each single frame. Experiments demonstrate how the proposed technique, even if trained with purely synthetic data, can produce accurate and physically consistent surfaces at five frames per second on a modern PC

Analysis of the effect of fish oil on wind waves and implications for air-water interaction studies

Surfactant layers with viscoelastic properties floating on the water surface dampen short gravity-capillary waves. Taking advantage of the known virtue of fish oil to still angry seas, a laboratory study has been made to analyse wind-wave generation and the interaction between wind waves, paddle waves, and airflow. This was done in a tank containing a thin fish-oil film uniformly spread on the water surface. The research was aimed, on the one hand, at quantifying for the first time the effectiveness of this surfactant at impeding the generation of wind waves and, on the other, at using the derived conditions to disentangle relevant mechanisms involved in the air-sea interaction. In particular, our main interest concerned the processes acting on the wind stress and on the wave growth. With oil on the water surface, we have found that in the wind-only condition (no paddle waves) the wave field does not grow from the rest condition. This equilibrium is altered by irregular paddle (long) waves, the generation and evolution of short waves (in clean water and with oil) being modified by their interaction with the orbital velocity of the long waves and their effect on the airflow. Paddle waves do grow under the action of wind, the amount being similar in clean and oily water conditions, a fact we ascribe to the similar distortion of the wind vertical profile in the two cases. We have also verified that the wind-supported stress on the oily water surface was able to generate a surface current, whose magnitude turns out to be comparable to the one in clean water. We stress the benefits of experiments with surfactants to explore in detail the physics at, and the exchanges across, the wavy and non-wavy air-water interface.

A low-cost stereo video system for measuring directional wind waves

Typical oceanographic instruments are expensive, complex to build, and hard to deploy and require constant and specialized maintenance. In this paper, we present a cheap and simple technique to estimate a three-dimensional surface elevation map, n (x, y, t), the directional spectrum, and the main sea state parameters using inexpensive smartphones. The proposed methodology uses Time Lagged Cross Correlation (TLCC) between the audio signals from two independent video records to perform the frame synchronization. This makes the system much easier to deploy, where the main requirement is a fixed or moving platform close to the sea. The time records are mostly limited by the equipment storage space and battery life, although it can be easily replaced or recharged. Here, we pose the basis for an inexpensive yet powerful stereo reconstruction device and discuss its capabilities and limitations. The smartphone system capabilities were illustrated here by near shore experiment, at Leme beach in the Southeast of Brazil, and the results were compared against a pressure sensor. For this particular setup, the root mean square error in terms of significant wave height is of the order of 11% with perfect estimation of the peak period. The results are promising and demonstrate the validity and applicability of the technique

A data set of sea surface stereo images to resolve space-time wave fields

Stereo imaging of the sea surface elevation provides unique field data to investigate the geometry and dynamics of oceanic waves. Typically, this technique allows retrieving the 4-D ocean topography (3-D space + time) at high frequency (up to 15–20 Hz) over a sea surface region of area ~104 m2. Stereo data fill the existing wide gap between sea surface elevation time-measurements, like the local observation provided by wave-buoys, and large-scale ocean observations by satellites. The analysis of stereo images provides a direct measurement of the wavefield without the need of any linear-wave theory assumption, so it is particularly interesting to investigate the nonlinearities of the surface, wave-current interaction, rogue waves, wave breaking, air-sea interaction, and potentially other processes not explored yet. In this context, this open dataset aims to provide, for the first time, valuable stereo measurements collected in different seas and wave conditions to invite the ocean-wave scientific community to continue exploring these data and to contribute to a better understanding of the nature of the sea surface dynamics

Three-dimensional imaging of waves and floes in the marginal ice zone during a cyclone

The marginal ice zone is the dynamic interface between the open ocean and consolidated inner pack ice. Surface gravity waves regulate marginal ice zone extent and properties, and, hence, atmosphere-ocean fluxes and ice advance/retreat. Over the past decade, seminal experimental campaigns have generated much needed measurements of wave evolution in the marginal ice zone, which, notwithstanding the prominent knowledge gaps that remain, are underpinning major advances in understanding the region’s role in the climate system. Here, we report three-dimensional imaging of waves from a moving vessel and simultaneous imaging of floe sizes, with the potential to enhance the marginal ice zone database substantially. The images give the direction–frequency wave spectrum, which we combine with concurrent measurements of wind speeds and reanalysis products to reveal the complex multi-component wind-plus-swell nature of a cyclone-driven wave field, and quantify evolution of large-amplitude waves in sea ice