Intense atmospheric disturbances, which impact directly on the sea surface causing a significant increase in wave height and sometimes strong storm surges, have become increasingly frequent in recent years in the Mediterranean Sea, producing extreme concern in highly populated coastal areas, such as the Gulf of Naples (Western Mediterranean Sea, Central Tyrrhenian Sea). In this work, fifty-six months of wave parameters retrieved by an HF radar network are integrated with numerical outputs to analyze the seasonality of extreme events in the study area and to investigate the performance of HF radars while increasing their distances from the coast. The model employed is the MWM (Mediterranean Wind-Wave Model), providing a wind-wave dataset based on numerical models (the hindcast approach) and implemented in the study area with a 0.03° spatial resolution. The integration and comparison with the MWM dataset, carried out using wave parameters and spectral information, allowed us to analyze the availability and accuracy of HF sampling during the investigated period. The statistical comparisons highlight agreement between the model and the HF radars during episodes of sea storms. The results confirm the potential of HF radar systems as long-term monitoring observation platforms, and allow us to give further indications on the seasonality of sea storms under different meteorological conditions and on their energy content in semi-enclosed coastal areas, such as the Gulf of Naples.

<p>Starting our work on model-based coupling microplastic (MP) and the low-trophic level marine biota, we present a contemporary overview of existing models, both the Lagrangian and Eulerian ones.</p> <p>MP biofouling has been modeled by Kooi et al. (2017), who develop a 1D Lagrangian model to describe size- and density specific vertical motion of MP. They have found that</p> <ul> <li>Denser particles settle sooner than the less dense particles when they have the same size.</li> <li>The settling velocity decreases with decreasing particle size.</li> <li>MP particle can oscillate due its buoyancy controlled by biofouling. MP density is balanced by the source-and-sink terms in a biofouling equation for algae attached to the MP surface.</li> <li>Oscillation periods increase with decreasing particle size.</li> </ul> <p> </p> <p>Lobelle et al. (2021) improve the Kooi et al. (2017) model developing a 3D Lagrangian model with horizontal and vertical advection. They consider a global distribution of MP of different size and density and note that the timescale is largely size-dependent as opposed to density dependent.</p> <p>Finally, Fischer et al. (2022) modify the physics part of the model by Lobelle et al. (2021), focusing on the vertical movement, both vertical advection and vertical turbulence diffusion. Additionally, they add two loss terms in the biofouling equation. They conclude that the vertical movement of particles is mainly affected by wind induced mixing within the upper mixed layer and by biofilm dynamics in the deep ocean.</p> <p>Biofouling as a possible mechanism of the MP removal from the surface has been incorporated into a 3D Lagrangian model for 6 size classes of MP (Tsiaras et al., 2021). In the water column, a sub-surface maximum in MP abundance is obtained, with increasing contribution of smaller particles in deep layers.</p> <p>MP has been embedded in a biogeochemical 3D Euler model by Kvale et al. (2020), who consider the processes of MP aggregation in sinking marine snow and faecal pellets in the global ocean. In the subsequent work (Kvale, 2022), a two-way coupling developed in the model allows finding a way of the MP influence on global marine carbon cycling and climate.</p> <p>Biofouling, the MP transport by marine snow and fecal pellets have been simulated by Berezina et al. (2021), who incorporate MP into a biogeochemical 2D Euler model with translational symmetry. They reveal that the so-called “biological pump” (or vertical transport of MP by marine snow and fecal pellets)<strong> </strong>can be one of the important drivers controlling the distribution of MP in the water column and bottom sediments in the Oslo Fjord.</p> <p>A new Lagrangian model that we plan to implement in the future will help to advance our understanding of biota-mediated processes in MP transport and fate in the Mediterranean Sea.</p>

HF radar systems have the potential to measure the wind direction, in addition to surface currents and wave fields. However, studies on HF radar for wind direction determination are rare in the scientific literature. Starting with the results presented in Saviano et al. (2021), we here expand on the reliability of the multiannual wind direction data retrieved over two periods, from May 2008 to December 2010 and from January to December 2012, by a network of three SeaSonde high-frequency (HF) radars operating in the Gulf of Naples (Central Tyrrhenian Sea, Western Mediterranean Sea). This study focuses on the measurements obtained by each antenna over three range cells along a coast–offshore transect, pointing to any potential geographically dependent measurement. The scarcity of offshore wind measurements requires the use of model-generated data for comparative purposes. The data here used are obtained from the Mediterranean Wind–Wave Model, which provides indications for both wave and wind parameters, and the ERA5@2km wind dataset obtained by dynamically downscaling ERA5 reanalysis. These data are first compared with in situ data and subsequently with HF-retrieved wind direction measurements. The analysis of the overall performance of the HF radar network in the Gulf of Naples confirms that the HF radar wind data show the best agreement when the wind speed exceeds a 5 m/s threshold, ensuring a sufficiently energetic surface wave field to be measured. The results obtained in the study suggest the necessity of wind measurements in offshore areas to validate the HF radar wind measurements and to improve the extraction algorithms. The present work opens up further investigations on the applications of wind data from SeaSonde HF radars as potential monitoring platforms, both in coastal and offshore areas.

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