Abstract Re‐analysis and observational data are used to identify the relationship between marine heatwaves and atmospheric heatwaves over the Eastern Mediterranean, and also the precursors of marine heatwaves in the 15‐day before heatwave onset. There has been a clear tendency for more heat extremes in recent years. Even though the specific dates in which marine heatwaves and atmospheric heatwaves occur do not match, most of the precursors are similar for both. These precursors include a weakened Indian monsoon, a strengthened Sahelian monsoon, a weakened Persian trough with a mid‐latitude low‐pressure system from the west, and an upper tropospheric ridge. The weakened Indian monsoon and Persian trough are evident at even earlier leads for marine heatwaves than for atmospheric heatwaves. Both latent heat and incoming shortwave radiation are highly anomalous in the lead‐up to marine heatwaves due to increased near‐surface atmospheric humidity, reduced wind speed, and reduced cloud cover.

Wave measurements from fixed gauges in a flume produce time-series of surface elevation. To characterize the waves and enable a comparison with theory, additional spatial information is needed. This is commonly obtained by simultaneous measurements at pairs of gauges with spacing much smaller than a typical wavelength, assuming the surface profile to be frozen between the gauges. Although a "wave" can be defined as the signal between successive positive or negative zero-crossings, between successive crests, or between successive troughs, experimental measurements are not agnostic to the choice of metric. We show that wave-by-wave measurements of phase velocity or wavelength are most stable and consistent over repeated experiments when using wave-by-wave cross-correlation, as opposed to the passage of zero-crossings, crests, or troughs. The high variability of these other metrics may contribute to some of the difficulty in measuring nonlinear wave properties in flume experiments.

Effective spatio-temporal measurements of water surface elevation (water waves) in laboratory experiments are essential for scientific and engineering research. Existing techniques are often cumbersome, computationally heavy and generally suffer from limited wavenumber/frequency response. To address this challenge, we propose the Wave (from) Polarized Light Learning (WPLL), a learning based remote sensing method for laboratory implementation, capable of inferring surface elevation and slope maps in high resolution. The method uses the polarization properties of the light reflected from the water surface. The WPLL uses a deep neural network (DNN) model that approximates the water surface slopes from the polarized light intensities. Once trained on simple monochromatic wave trains, the WPLL is capable of producing high-resolution reconstruction of the 2D water surface slopes and elevation in a variety of irregular wave fields. The method's robustness is demonstrated by showcasing its high wavenumber/frequency response, its ability to reconstruct wave fields propagating in arbitrary angles relative to the camera optical axis, and its computational efficiency. This developed methodology is a cost-effective near-real time remote sensing tool for laboratory water surface waves measurements, setting the path for upscaling to open sea application for research, monitoring, and short-time forecasting.

This study examines the impacts of climate change on Eastern Mediterranean Sea coastal environment using long-term in situ data. Specifically, it explores three decades of previously inaccessible data on surface waves and sea surface temperature, obtained from two buoys moored off the Israeli coastline, augmented with data from several coastline temperature sensors, and sea level measurements. Our findings reveal a moderate increase in sea surface temperature of 2.65 °C per century, contradicting the current local scientific consensus of faster warming trends, and showing that the reanalysis models grossly overestimate the multiannual trends while underestimating the actual temperature values. We found alteration in the seasonal cooling-warming cycles, with shrinking transitional season periods that are replaced by prolonged summer and winter periods. Marine heatwaves have become more frequent and severe, which may result in significant ecological impacts. Maritime storm activity was observed to intensify, with a sharp increase in storms’ intensity during the early 2000s. The study also documented a rise in the occurrence of Rogue waves, including a notable 11.5-m wave near Haifa in February 2015. The sea level rise trend was found to be 2.3 mm per year. In summary, our study demonstrates the intensification in the occurrence of extreme ocean weather events which may increasingly threaten marine life in the Levant coastal zone.

Effective spatio-temporal measurements of water surface elevation (water waves) in laboratory experiments are essential for scientific and engineering research. Existing techniques are often cumbersome, computationally heavy and generally suffer from limited wavenumber/frequency response. To address these challenges a novel method was developed, using polarization filter equipped camera as the main sensor and Machine Learning (ML) algorithms for data processing [1,2]. The developed method training and evaluation was based on in-house made supervised dataset. Here we present this supervised dataset of polarimetric images of the water surface coupled with the water surface elevation measurements made by a linear array of resistance-type wave gauges (WG). The water waves were mechanically generated in a laboratory waves basin, and the polarimetric images were captured under an artificial light source. Meticulous camera and WGs calibration and instruments synchronization supported high spatio-temporal resolution. The data set covers several wavefield conditions, from simple monochromatic wave trains of various steepness, to irregular wavefield of JONSWAP prescribed spectral shape and several wave breaking scenarios. The dataset contains measurements repeated in several camera positions relative to the wave field propagation direction.

The turbulent flow field over a spanwise-heterogeneous vegetative canopy model was investigated to examine the impact of heterogeneity on energy and momentum transport processes. Constant temperature anemometry, paired with a novel Deep Learning-based calibration methodology, enabled high-resolution measurements of velocity components and turbulent kinetic energy (TKE) spectra, spanning several orders of magnitude and resolving dissipation scales. A controlled experimental framework facilitated the collection of multi-point, high-frequency turbulence statistics, capturing the intricate flow dynamics across canopy and open patch regions. In the homogeneous configuration, velocity profiles exhibited minimal variation across spanwise positions, with turbulence intensity peaking near the canopy height, where aerodynamic drag enhanced energy dissipation. Spectral analysis revealed distinct inertial and dissipation ranges, indicating the presence of robust turbulent structures that drive the energy cascade. In the heterogeneous layout, the boundary layer flow transitioned distinctly across the open patch, resembling rough plate behavior. Near canopy edges, elevated turbulence intensity, and TKE signaled strong interactions between vegetation and airflow, while TKE sharply diminished deeper into the open patch. Variations in turbulence length scales, particularly Taylor and horizontal integral scales, highlighted the role of heterogeneity in modulating atmospheric boundary layer dynamics. These findings provide insights into how spanwise heterogeneity influences turbulent energy redistribution and flow characteristics. The results contribute to a better understanding of canopy-atmosphere interactions and may support the refinement of models for predicting wind flow and transport phenomena in heterogeneous environments.

Since the 1990s, modulational instability has been proposed as an alternative to the constructive interference of waves to explain the occurrence of rogue waves in the open ocean. This study questions the relevance of this instability for real rogue waves by analyzing a novel dataset of high-frequency laser altimeter wave measurements collected over an 18-year period ([Formula: see text]) at the offshore Ekofisk platform in the central North Sea. A composite statistics of the ensemble of 27505 half-hourly sea states, accounting for data heterogeneity, show that third-order modulational instabilities do not significantly impact large waves; instead, second-order bound nonlinearities, shaping waves with asymmetric sharper crests and shallower troughs, are the primary factor that enhances the linear dispersive focusing, or constructive interference, of extreme waves.

This study investigates the complex flow field across a spanwise vegetative model canopy edge focusing on turbulent transport processes. Utilizing stereoscopic particle image velocimetry, the three velocity components were measured in wall-parallel planes at various elevations within canopy across the spanwise canopy edge. Conventional ensemble averaged results were contrasted with those obtained by conditionally averaged flow properties across instantaneous internal interfaces in the flow to understand their contribution to the ensemble average. The conditional average captured the strong gradients in mean velocities, Reynolds stresses, vorticity, swirling strength, and turbulent kinetic energy production across the dynamically changing instantaneous interface. In contrast, the conventional ensemble average smeared out the strong gradients. Small magnitudes of advective terms in the turbulent kinetic energy transport equation suggested weak secondary transverse flows in the present model canopy. The turbulent flow structure across the spanwise canopy edge was further investigated using Quadrant-Hole analysis for both averaging approaches. Conventional ensemble averaged results indicated a shift from sweep to ejection dominance when moving from canopy into the open patch, while the conditional average showed only sweep dominated transport. In contrast to a homogeneous canopy layout, below canopy height at the canopy edge, sweeps and ejections lose their dominance in vertical turbulent transport. The present results show that the dynamics of internal interfaces govern the ensemble averaged results and a possible implementation into existing models is proposed. The present results are expected to increase understanding of spanwise turbulent transport and aid in developing strategies to mitigate desertification.

The sea surface temperature increase due to global warming is causing rapid iceberg melting and increased condensation of clouds, each project to a global consequence in the form of sea surface temperature drop during storms, marine heatwaves, sea level rise, and increase in intensification and rate of recurrence of storm weather events.Here we present the analysis of 30-year-long measurements of sea surface temperature and instantaneous water surface elevation, measured by two buoys moored in separate locations in the climate hotspot area in the Eastern Mediterranean Sea at the depth of 24 meters, two kilometers off the Israeli coastline. Additional long-term measurements of sea level rise from several stations along the Israeli coastline are also integrated into the analysis. The increase in storm weather events was examined in terms of storms’ significant wave height statistics, using peak-over-threshold analysis over the historic data. The results showed occurrences of sea surface temperature drop events following storms and of marine heatwaves, positive trends were observed in sea level and in sea surface temperature rise. The last two decades are shown to be characterized by storm intensification. The sea surface rise was correlated against the measured sea surface temperature trends as obtained by the buoys and compared to Copernicus satellite data with remarkable conclusions.

The hydrodynamical process of breaking water waves is still a source of many unsolved questions. An extensive research work has been carried out during the last decades in order to quantify and define the associated energy redistribution, which directly influences a wide range of climate processes, maritime applications, and oceanic phenomena.Naturally, waves become steeper toward the inception of breaking; however, there is still a lack of unanimity regarding the relationship between breaking probability statistics and wave steepness. Here we present a detailed analysis of different sea states from the Black Sea measurements and from a closed wind-wave flume experiments. Together with the wind-derived parameters, the water wave statistics were gathered using an innovative breaking wave detection algorithm. The algorithm was recently developed to allow accurate detection of breaking waves based on the phase-time approach and wavelet analysis to identify breaking-associated patterns in the instantaneous frequency variations of surface elevation fluctuations. The in-depth analysis of breaking and non-breaking wave statistics included wave-by-wave calculations resulting in steepness and celerities of the local wave, derived from the local wave frequency and wavenumber. Finally, the findings, after investigation and validation, presented a skewed Gaussian-like steepness histogram, revealing that both non-breaking and breaking waves can reach steep profiles, above the Stokes limit.

Accurate and cost-effective sea state measurements, in terms of spatio-temporal distribution of water surface elevation (water waves), is of great interest for scientific research and various engineering, industrial, and recreational applications. To this end, numerous measurement techniques have been developed over the years. None of these techniques, however, are universally applicable across various ocean and laboratory conditions and none provide near-real-time data. We utilized the latest advances in polarimetric imaging to develop a new remote sensing method based on machine learning methodology and polarimetric reflection measurements for inferring surface waves elevation and slope. The method utilizes a newly available, inexpensive polarimetric camera providing images of the water surface in a high spatio-temporal resolution at several linear polarization angles. Algorithms based on artificial neural networks ( ANN s) are then trained to obtain high-resolution reconstructions of the water surface slope state from those images. The ANN s are trained on laboratory-collected supervised datasets of prescribed mechanically generated monochromatic wave trains and tested on a stochastic wave field of JONSWAP spectral shape. The proposed method, based on inferring the surface slope from polarimetric images, provides a dense estimate of the water surface. The results of this study pave the way for the development of accurate and cost-effective near-real-time remote sensing tools for both laboratory and open sea wave measurements.

We investigated the dynamics of highly turbulent thermally driven anabatic (upslope) flow on a physical model inside a large water tank using particle image velocimetry (PIV) and a thermocouple grid. The results showed that the flow exhibited pronounced variations in velocity and temperature and, importantly, could not be accurately modeled as a two-dimensional quasi-steady flow. Five significant findings are presented to underscore the three-dimensional nature of the flow, namely, the B-shaped mean velocity profiles, B-shaped turbulent flux profiles, synthetic streaks that revealed particles flowing perpendicular to the laser sheet, average vorticity maps revealing helical structure splitting, and identified vortices shooting away from the boundary toward the apex plume. Collectively, these findings offer novel insights into the flow behavior patterns of thermally driven complex terrain flows, which influence local weather and microclimates and are responsible for scalar transport, e.g., pollution.

The effect of spanwise canopy heterogeneity on the turbulent wind flow field and associated evaporation rates was investigated by combined stereoscopic particle image velocimetry (stereo-PIV) and evaporation rate measurements on a model canopy in an atmospheric boundary layer wind tunnel. The model was designed to simulate a mature corn canopy, based on a similar wall-normal distribution of the projected frontal area index. Stereo-PIV measurements were performed in wall-parallel planes across the spanwise heterogeneity at several elevations. For comparison, measurements were also performed for a homogeneous canopy layout. For the heterogeneous layout, large spanwise gradients of the mean streamwise velocity at the canopy edge were observed, resulting in high shear and high peak values of the in-plane Reynolds shear stress component. Local evaporation rates were measured directly utilizing a specially designed wicks based system. Measurements were conducted at three locations positioned in a line, perpendicular to the incoming flow, across the heterogeneity. The spanwise heterogeneity did not alter the well-accepted sweep-ejection mechanism, sweeps dominated flow was recorded at the sheltered wick positions. Evaporation rates increased with local mean streamwise velocity and power-law based correlations for the Sherwood number versus Reynolds number were derived for sheltered and exposed evaporating wicks. Turbulent flow structures, in the form of sweeps and ejections, were important both in wall-normal and transverse directions (for a heterogeneous canopy). The results indicated that in arid regions, dry air transported in the transverse direction into the canopy is likely to lead to increased evaporation rates at canopy edges.

We develop a new methodology for the deterministic forecasting of directional ocean surface waves based on nonlinear frequency corrections. These frequency corrections can be pre-computed based on measured energy density spectra and, therefore, come at no additional computational cost compared to linear theory. The nonlinear forecasting methodology is tested on highly nonlinear synthetically generated seas with a variety of values of average steepness and directional spreading and is shown to consistently outperform a linear forecast.

<p>Recent years have seen an extensive increase in maritime activity, including new coastal and offshore infrastructure, increased cargo transport, and research on wave energy converters. While long-term macro-scale wave forecasting has been extensively researched (e.g. Günter & Hasselmann, 1991), with several forecasting models available today, there is a noticeable gap in local-scale deterministic wave forecasting models. Such models are needed to improve the efficiency of the design and operation of offshore installations and vessels, providing close-to-real-time data and short-term predictions of waves and wave-induced forcing.</p><p>We will report on the development of a new, computationally efficient model, allowing for weak nonlinearities in directional wavefields, based on previous studies on the unidirectional case (Stuhlmeier & Stiassnie, 2021). The model is capable of providing a deterministic forecast of the wavefield inside the prediction domain in time and space, based on measurements conducted over an initial region (Figure 1).</p><p>The mathematical framework used is the Zakharov equation, which determines the nonlinear cross-corrections to the frequencies between the various modes in the spectrum (Stuhlmeier & Stiassnie, 2019), used to derive the actual velocities at which the various wave field components are propagating.</p><p>The presentation will elaborate the full mathematical framework, alongside explanations of its benefits with respect to linear predictions. The model’s performance is validated using numerical data of nonlinear directional wavefields, generated using the higher order spectral (HOS) method.</p><p><img src="https://contentmanager.copernicus.org/fileStorageProxy.php?f=gnp.57170f819cb365142033761/sdaolpUECMynit/32UGE&app=m&a=0&c=ad32d4181b35dfcd0a5c5bc36649b67b&ct=x&pn=gnp.elif&d=1" alt=""></p><p><em>Figure 1 – Predictable region in time (vertical axis) based on measurements at initial domain η<sub>0</sub>(x,y)</em></p><p><strong>References</strong></p><p>​​Günter, H. & Hasselmann, S., 1991. <em>Wamodel cycle 4</em>, Hamburg: German Climate Computing Centre.</p><p>Raphael Stuhlmeier and Michael Stiassnie. Deterministic wave forecasting with the Zakharov equation. <em>J. Fluid Mech.</em>, 913:1–22, 2021.</p><p>Raphael Stuhlmeier and Michael Stiassnie. Nonlinear dispersion for ocean surface waves. <em>J. Fluid Mech.</em>, 859:49–58, 2019.</p>

The underwater release of air from the sudden rupture of a finite canister was studied by time-resolved pressure and interfacial geometry measurements. Two distinct dynamical regimes for the air were identified: an inertial regime, in which the air oscillated with increasing frequency, and a capillary pinch-off regime, in which emerging air bubbles pinched off from the air remaining in the canister. The temporal scales for these regimes were identified, and the inertial regime was shown to follow Rayleigh–Plesset dynamics, and was characterized by an empirically defined length scale associated with the air volume. The behavior of the two regimes in frequency-space was modeled by a modified Rayleigh–Plesset equation accounting for volume losses, turbulent damping, and a time-dependent capillary forcing.

When the prevailing geostrophic flow is parallel to the heterogeneity, large secondary spanwise circulations emerge within the flow that affect surface fluxes of momentum, heat, and mass. By means of wind-tunnel measurements, the influence of spanwise heterogeneity on the possible appearance of secondary circulations and their effect on evaporative fluxes is investigated. The experiments were performed at the environmental wind-tunnel at the Technion. A 5-m long canopy, modeled after available leaf-area index data for corn, consisted of triangular perforated sheet elements (h = 20 cm) arranged in an in-line setup. The atmospheric boundary layer conditioned by spires and a shear generator has a boundary layer thickness of about 70cm. Measurements were performed by combined hot wire anemometry and stereo-PIV enabling to resolve the turbulent flow characteristics both spatially and temporally. Measurements were performed at a bulk flow velocity of 3.0 m/s (Reh = 38400). Several sets of stereo-PIV measurements in fifteen wall-parallel planes positioned between 0.5h to 1.5h were acquired. In addition, the evaporation rates at various locations within the canopy were obtained by means of in-house made sensors. Measurements were performed for a homogeneous canopy and one that exhibited spanwise heterogeneity under the bulk flow conditions. Turbulent flow characteristics, including turbulence production terms, will be presented. The effects of the heterogeneity on the coherent structures near the canopy top are analyzed using quadrant and spectral analyses.

Water wave breaking represents one of the most arduous problems in fluid mechanics. Understanding the process of wave breaking and developing an ability to quantify the associated energy losses and redistribution are critical across a wide range of coastal oceanic applications, maritime navigation, and climate and hydrodynamic research. Naturally, waves become steeper toward the inception of breaking; however, there is still a lack of unanimity regarding the relationship between breaking probability statistics and wave steepness. Here, we present a detailed investigation of breaking vs non-breaking statistics estimated using a recently developed method for accurate detection of breaking waves, based on the phase-time approach to identify breaking-associated patterns in the instantaneous frequency variations of surface elevation fluctuations. The findings are based on data collected both in the open sea and in a laboratory wind wave flume. An in-depth examination of celerities and steepnesses of breaking and non-breaking waves is presented. The analysis, which involved wave-by-wave examination, produced skewed Gaussian-like steepness histograms, revealing that non-breaking waves and breaking waves can reach steeper profiles, above the Stokes limit. All extreme steepness values were investigated and are presented here.

The study of naturally occurring turbulent flows requires ability to collect empirical data down to the fine scales. While hotwire anemometry offers such ability, the open field studies are uncommon due to the cumbersome calibration procedure and operational requirements of hotwire anemometry, e.g., constant ambient properties and steady flow conditions. The combo probe-the combined sonic-hotfilm anemometer developed and tested over the last decade-has demonstrated its ability to overcome this hurdle. The old-er generation had a limited wind alignment range of 120 degrees and the in-situ calibration procedure was human decision based. This study presents the next generation of the combo probe design, and the new fully automated in-situ calibration procedure implementing deep learning. The elegant new design now enables measurements of the incoming wind flow in a 360-degree range. The improved calibration procedure is shown to have the robustness necessary for operation in everchanging open field flow and environmental conditions. This is especially useful with diurnally changing environments or non-stationary measuring stations, i.e., probes placed on moving platforms like boats, drones, and weather balloons. Together, the updated design and the new calibration procedure, allow for continuous field measurements with minimal to no human interaction, enabling near real-time monitoring of fine-scale turbulent fluctuations. Integration of these probes will contribute toward generation of a large pool of field data to be collected to unravel the intricacies of all scales of turbulent flows occurring in natural setups.