Coastal HF radars in the Mediterranean: Applications in support of science priorities and societal needs

Abstract. The Mediterranean Sea is a prominent climate change hot spot, being their socio-economically vital coastal areas the most vulnerable targets for maritime safety, diverse met-ocean hazards and marine pollution. Providing an unprecedented spatial and temporal resolution at wide coastal areas, High-frequency radars (HFRs) have been steadily gaining recognition as an effective land-based remote sensing technology for a continuous monitoring of the surface circulation, increasingly waves and occasionally winds. HFR measurements have boosted the thorough scientific knowledge of coastal processes, also fostering a broad range of applications, which has promoted their integration in the Coastal Ocean Observing Systems worldwide, with more than half of the European sites located in the Mediterranean coastal areas. In this work, we present a review of existing HFR data multidisciplinary science-based applications in the Mediterranean Sea, primarily focused on meeting end-users and science-driven requirements, addressing regional challenges in three main topics: i) maritime safety; ii) extreme hazards; iii) environmental transport process. Additionally, the HFR observing and monitoring regional capabilities in the Mediterranean region required to underpin the underlying science and the further development of applications are also analyzed. The outcome of this assessment has allowed us to finally provide a set of recommendations for the future improvement prospects to maximize the contribution in extending the science-based HFR products into societal relevant downstream services to support the blue growth in the Mediterranean coastal areas, helping to meet the UN’s Decade of Ocean Science for Sustainable Development and the EU’s Green Deal goals.


(v) Slovenia: has 42 km of coastline and a semi-enclosed coastal area. During 2019, the SAR agency has responded to 9 SAR missions (7 times the rescue boat went out to sea while 2 rescues were of injured people on a moored boat in port). All cases 200 occurred within the 3 nm from the coast (i.e. 3 within 200 meters, 3 around 1 nm and 1 at 3 nm from the coast) https://doi.org/10.5194/os-2021-115 Preprint. Discussion started: 14 December 2021 c Author(s) 2021. CC BY 4.0 License.
(vi) Spain: the 4 SAR responsibility areas cover 1 500 000 km2 of marine surface (3 times the size of the Spanish national territory) and 8 000 km of coastline. The Spanish Maritime Safety and Rescue Agency (SASEMAR hereinafter) is divided in 19 MRCCs plus 1 National Centre, with more than 370 SAR operators. SASEMAR responded to 5 891 missions in 2019, from which almost 88% were SAR operations (being the 12% in response to issues related to marine pollution). Fifty percent of the 205 total SAR incidents occurred within 3 km off the Spanish coastlines. From 7 of the HFR networks operating inside their 4 responsibility areas, 3 of them are located in the Western Mediterranean, monitoring the Strait of Gibraltar (HFR-Gibraltar), the Ebro Delta (HFR-Ebro) and the Ibiza Channel (HFR-Ibiza) and all of them are integrated in the SASEMAR Environmental Data Server. As aforementioned, maritime SAR operations most often depend on leveraging Lagrangian tracking tools using timely and reliable knowledge of surface circulation, near surface winds and, if applicable, surface gravity waves. Surface circulation is 215 generally provided by numerical circulation models but HFR observations can offer valuable insight into marine conditions over the region of the accident and can -especially when coupled to short term prediction models (see Sect. 2.1.3) -act as a complementary input for Lagrangian predictions, hindcasts or back-tracking simulations. Révelard et al. (2021) evaluated the use of HFR-derived trajectories to complement drifter observations for assessing the performance of different models in predicting Lagrangian trajectories. They used the Skill Score metric, based on the Normalized Cumulative Lagrangian 220 Separation distance (Liu and Weisberg, 2011), which is a commonly used metric for assessing Lagrangian performance. They have shown that whereas drifters only provide assessment along their drifting paths, HFR allows obtaining a large number of trajectories, improving not only the robustness of the Skill Score statistics but also the spatial and temporal assessment of the https://doi.org/10.5194/os-2021-115 Preprint. Discussion started: 14 December 2021 c Author(s) 2021. CC BY 4.0 License. model performance (Fig. 2). Since HFR data are quasi-continuous in time, this method can be applied in near-real-time, which is a strong advantage for evaluating extremely scenario-dependent models. Indeed, the quality of any numerical model 225 performance varies with time and can have substantial fluctuations on short temporal and spatial scales even if the model otherwise exhibits good overall forecasting skills. In cases like these, quality controlled HFR observations represent particularly valuable short-term inputs for Lagrangian products assisting SAR efforts. Révelard et al. (2021) also analyzed the Skill Score sensitivity to different forecast horizons and showed that in coastal regions, where most of the SAR incidents occurred in the Mediterranean Sea, an overly long forecast time (i.e. 72 hours) can lead to 230 an overestimation of the Skill Score due to the high variability of the surface currents. A forecast time of 6 hours, consistent with the duration of the search that maximizes survivors in SAR missions, is therefore more appropriate when using HFR as the observing reference. In addition, they have shown that whereas the original definition of the Skill Score from Liu and Weisberg (2011) is correct for analyzing its spatiotemporal distribution, it is not adequate if averages are going to be applied afterward, because of the previous imposition of the negative values to zero. In the aim of estimating the relative average 235 performance of different datasets over an area and/or period, they introduced the novel Skill Score SS*. The SS* is defined as in Liu and Weisberg (2011), but without the imposition of the negative values to zero, allowing to obtain a correct average, as in Fig. 2 where the SS* is temporally averaged over a period of 6 hours. However, as pointed out in Révelard et al. (2021), only values > 0.5 should be interpreted as a good agreement between HFR surface current observations and model outputs.  A further example of the value of quality controlled HFR observations in SAR operations was the recent case of a person lost at sea in Northern Adriatic during a Scirocco storm on 29 Oct 2018. In this case, HFR-NAdr observations were employed for hindcasting and survivor's drift trajectory verification .  Even though in this case part of the survivor's trajectory outside of the HFR-NAdr domain had to be inferred from extrapolated 260 currents, such HFR-based nowcasting products would have been valuable during this and similar rescue attempts. However, since HFR data arrive in near real time, some sort of model-based extension of their prediction horizon is necessary before they can be used for operational nowcasting. One possible solution is data assimilation of HFR data into a numerical model (see Sect. 2.1.2.), followed by a forecasting time window. An alternative and numerically less demanding option, gaining ground in recent years, is the machine learning approach where a neural network model is trained on past data and then used 265 to create short term predictions of surface currents, addressed in Sect. 2.1.3.

Model assessment and improvement
This section addresses one of the main interests and needs of end-users of operational oceanography information: users want to be able to have confidence in modelled data and they need to know how good they are. Addressing end-user overarching concerns, model assessment, essentially built upon comparison to observations, is crucial to evaluate the quality of the diversity 270 of modelling products available in a systematic and long-term routine manner, and to inform users about their usefulness for a given application.
For this reason, seeking also to strengthen end-user loyalty, the validation of Operational Ocean Forecasting Systems against independent measurements constitutes a core activity in operational oceanography (Hernández et al., 2015) since it aids: (i) to infer the relative strengths and weaknesses in the modelling of several key physical processes; (ii) to compare different versions 275 https://doi.org/10.5194/os-2021-115 Preprint. Discussion started: 14 December 2021 c Author(s) 2021. CC BY 4.0 License. of the same operational ocean forecasting system and evaluate potential improvements and degradations before a new version is transitioned into operational status; (iii) to compare coarse-resolution "parent" and nested high-resolution "child" systems to quantify the added value of downscaling; (iv) to inform end-users about the consistency and skill of the modeling products disseminated.
Developments in ocean modelling have clearly advanced to address the challenges associated with the increased resolution 280 and its application to coastal areas, also responding to the high demand of providing 4D estimates of multiple oceanic variables at fine-scales Fox-Kemper et al., 2019). Coastal modeling faces numerous challenges and issues as downscaling and representation of open boundary conditions or land-sea/air-sea interactions, for instance (Kourafalou et al.et al. 2015a). Synergies between models and ocean observations are needed to face these challenges and improve ocean processes representation (Kourafalou et al.2015b;De Mey-Frémaux et al., 2019;Davidson et al., 2019). Additionally, it is worth 285 mentioning the current lack of real-time and historical availability of observations on the coastal areas, which limits the operational capability and reduces the potential of skill assessment operational services aiming to provide synthetic metrics addressing specific user's needs (Révelard et al., 2021).
Within this context, HFR systems play a first-order role thanks to their unique ability to provide fine-resolution maps of the surface currents over broad coastal areas. This ability of the HFR system makes them particularly appropriate for the validation 290 of numerical models in coastal areas, where other observations are scarce and/or their resolutions (i.e. in space or in time) are not high enough to capture the fine scale. Many HFR systems have therefore been used with this purpose in several regions of the Mediterranean Sea including the Northern Current area off Toulon (Berta et al., 2014a), the Ebro Delta area (Lorente et al., 2016;Ruiz et al., 2020;Aguiar et al., 2020;Sotillo et al., 2021), the Northern Adriatic (Vilibić et al., 2016), the Gulf of Naples (Uttieri et al., 2011), the Ibiza Channel Aguiar et al. 2020;Révelard et al., 295 2021;Sotillo et al., 2021) and the Strait of Gibraltar (Lorente et al., 2019a;Aguiar et al., 2020).
An example of this added-value of the HFR data was recently shown in the multi-model comparison exercise performed in the Strait of Gibraltar in 2017 (Lorente et al., 2019a). This comparison was made between the coarser CMEMS-IBI model (Sotillo et al., 2015) and their partially nested SAMPA (Sánchez-Garrido et al., 2013) high-resolution coastal forecast system to elucidate the accuracy of each system characterizing the Atlantic Jet (AJ) inflow dynamics. To this aim, HFR-derived hourly 300 currents at the midpoint of the selected transect (square in Fig. 4,a) were used as a benchmark. The scatter plot of HFR-derived hourly current speed versus direction (taking as reference the north and positive angles clockwise) revealed interesting details (Fig. 4,b): (i) the AJ flowed predominantly eastwards, forming an angle of 78º with respect to the north; (ii) the current velocity, on average, was 1 ms -1 and reached peaks of 2.5 ms -1 . Speeds below 0.5 ms -1 were registered along the entire range of directions; (iii) westwards currents, albeit in the minority, were also observed and tended to predominantly form an angle 305 of 270º (i.e. towards the Atlantic), mostly related to intense easterly winds episodes (Garret, 1983;García-Lafuente et al., 2002;Menemenlis et al., 2007;Péliz et al., 2009;Reyes et al., 2015;Lorente et al., 2019b andBolado-Penagos et al., 2021), as further detailed in Sect. 2.2.1. The scatter plot of SAMPA estimations presented a significant resemblance in terms of prevailing current velocity and direction (Fig. 4,c). Although the time-averaged speed and angle were slightly smaller (0.9 https://doi.org/10.5194/os-2021-115 Preprint. Discussion started: 14 December 2021 c Author(s) 2021. CC BY 4.0 License. ms -1 ) and greater (88º), respectively, the main features of the AJ were qualitatively reproduced: maximum velocities (up to 2.5 310 ms -1 ) were associated with an eastward flow and an AJ orientation in the range of 50º-80º. Besides, surface flow reversals to the west were properly captured. By contrast, noticeable differences emerged in the scatter plot of regional IBI estimations (Fig. 4,d): surface current velocities below 0.3 ms -1 were barely replicated and the AJ inversion was only observed very occasionally. Despite the fact that IBI appeared to properly portray the mean characteristics of the eastwards flow, the model tended to favor flow directions between 60º and 180º and to overestimate the current velocity, with averaged and maximum 315 speeds around 1.17 and 2.80 ms -1 , respectively. In summary, HFR measurements are able to precisely assess the added value of the downscaling performed through the SAMPA coastal system with respect to the CMEMS-IBI MFC regional solution, in which SAMPA is nested. Overall, a steady https://doi.org/10.5194/os-2021-115 Preprint. Discussion started: 14 December 2021 c Author(s) 2021. CC BY 4.0 License. improvement in the Atlantic Jet characterization is evidenced in model performance when zooming from regional to coastal configurations, highlighting the benefits of the downscaling approach adopted and also the potential relevance of a variety of 330 factors at local scale, among others: a more refined horizontal resolution, a tailored bathymetry or the higher spatio-temporal resolution of the atmospheric forcing. Furthermore, SAMPA appeared to better reproduce the reversal events detected with HFR estimations, demonstrating the added value of imposing accurate meteorologically driven barotropic velocities in the open boundaries, imported from the NIVMAR storm surge model , in order to consider the remote effect of the atmospheric forcing over the entire Mediterranean basin, which was only partially included in IBI. 335 During the next phase of CMEMS, the higher focus will be on coastal downstream applications (e.g., very high-resolution ocean models integrated with coastal observatories) for specific stakeholders such as harbors and environmental agencies.
Despite the significant progress in the field of coastal modelling, some storm-induced hazards are still not properly resolved (or even misrepresented) by ocean models due to a variety of factors (e.g. too coarse horizontal resolution, inadequate meteorological forcing, poor representation of land-sea interactions and the related river freshwater outflows, among others) 340 as described by Sotillo et al. (2021). Within this framework, HFR might act as a monitoring cornerstone to calibrate and validate successive, upgraded versions of operational ocean forecasting models with the aim of better capturing extreme events in terms of strength, extension and timing . Aguiar et al. (2020) used the three HFR systems available in the Western Mediterranean Sea (Gibraltar Strait, Ibiza Channeldescribed in Lana et al., 2016 -and Ebro Delta) to evaluate the impact of downscaling on the surface coastal circulation in the 345 case of the WMOP model (Juza et al., 2016;Mourre et al., 2018). The authors showed that the time-average circulation in the coastal areas of the Ebro delta and Ibiza Channel were improved through downscaling. In particular, the nested model showed a better representation of the small-scale coastal flow intensification at the mouth of the Ebro River and a refinement in the characterization of the circulation in the Ibiza Channel. Notice that HFR-Gibraltar, HFR-Ebro and HFR-Ibiza versus model comparisons are updated daily on SOCIB WMOP webpage -https://socib.es/?seccion=modelling&facility=wmedvalidation-. 350 Those HFR systems, among others, are also integrated in the IBISAR science-based data downstream service ) -freely available under registration in wws.ibisar.es-for visualizing, comparing and evaluating the performance of ocean current predictions in the Iberian-Biscay-Irish regional seas. IBISAR allows the identification of the most accurate ocean current dataset in a specific area and period of interest, thus facilitating decision-making to SAR operators and emergency responders. Additionally, those HFR systems are also being used for the CMEMS IBI-MFC model assessment purposes by 355 means of the NARVAL multi-parameter and multi-platform validation tool (Lorente et al., 2019c) for the CMEMS IBI-MFC model validation.
Another added-value of HFR systems is their use to improve model forecast through data assimilation (DA). DA aims at optimally combining observations and models to provide a better representation of the ocean dynamics. In this sense, HFR provides very valuable high-resolution observations in areas where satellite observations tend to suffer limitations due to the 360 vicinity of the coast (Vignudelli et al., 2019). While the assimilation of HFR measurements has been applied in many regions of the world since the first studies from Breivik (2001) and Oke et al. (2002), only a limited number of studies has been https://doi.org/10.5194/os-2021-115 Preprint. Discussion started: 14 December 2021 c Author(s) 2021. CC BY 4.0 License. performed in the Mediterranean Sea. Marmain et al. (2014) assimilated radial observations from Toulon HFR system in a regional model in the Gulf of Lion. They showed how HFR observations can be successfully used to correct the wind forcing used to constrain the model coastal surface circulation. In the Ligurian Sea, Vandenbulcke et al. (2017) were able to correct 365 surface currents and improve the representation of inertial oscillations after the assimilation of all the available hourly radial observations in a regional model of the area. Variational methods were also applied to improve model dynamics through multiplatform data assimilation including HFR in the southern Tyrrhenian Sea  and in the Adriatic Sea surface currents in the Ibiza Channel using the WMOP operational system. They compared the performance of both radial and total daily mean HFR-Ibiza surface currents  for correcting meso and submesoscale circulation using different initialization methods in an operational-like context. An independent Lagrangian validation performed by comparing non-assimilated, assimilated without and with HFR measurements with a set of 14 surface drifters (Tintoré et al., 2014) showed that the best results were obtained when using HFR total observations along with the traditional observation sources (i.e. 375 satellite altimetry, SST and Argo temperature and salinity profiles). After 48 hours, the mean separation distance between virtual buoys and real drifters was reduced by 53% compared to the simulation without any data assimilation, and by 29%  To the best of authors´ knowledge, SOCIB WMOP (https://socib.es/?seccion=modelling&facility=forecast) is presently the only system in the Mediterranean Sea including an assimilation scheme of HFR data in its operational chain. 385 https://doi.org/10.5194/os-2021-115 Preprint. Discussion started: 14 December 2021 c Author(s) 2021. CC BY 4.0 License.

Short Term Predictions
Assimilation of HFR data into models is still computationally expensive and a complex issue, not to mention operational capabilities of such a procedure. Because of these constraints, the availability of real-time high-resolution HFR current fields has led to alternative solutions in order to obtain short term prediction (STP) of surface coastal currents, through the direct use of HFR historical and nowcast observations using different approaches (e.g. Zelenke 2005;Frolov et al. 2012;Barrick et al., 390 2012;Orfila et al. 2015;Vilibić et al, 2016).
The above-mentioned studies develop and implement different STP approaches (harmonic analysis of the last hours, genetic algorithms, numerical models, etc.) which often require additional data, or long training periods of data without gaps. Hardware failures due to power issues, communications or environmental conditions often result in spatio-temporal gaps within HFR datasets. Spatial gaps can be filled on a real-time basis but the filling of long temporal gaps is not straightforward. Several gap-395 filling methodologies have been developed for HFR data sets: Open Modal Analysis -OMA -(implemented by Lekien et al., 2004 and further optimized by Kaplan and Lekien, 2007), Data Interpolating EOFs -DINEOF- (Beckers and Rixen, 2003;Alvera-Azcárate et al., 2005;Hernández-Carrasco et al., 2018b, Bourg andMolcard, 2021), and Self-Organizing Maps -SOM- (Kohonen, 1982(Kohonen, , 2000(Kohonen, , 2001Hernández-Carrasco et al., 2018b), Reduced Order Optimal Interpolation -ROII- (Kaplan et al., 1997), Optimal Interpolation -OI- (Kim et al., 2008); Artificial Neural Network -ANN- (Ren et al., 2018) , Variational Analysis 400 (Yaremchuk and Sentchev, 2011), Data-Interpolating Variational Analysis, in n-dimensions -DIVAnd- (Barth et al., 2021). Through the NEURAL project (http://www.izor.hr/neural), an innovative neural network-based ocean forecasting system has been developed, providing gridded hourly surface current forecasts in the northernmost part of the Adriatic for the next 72 hours. The forecasting system is using unsupervised neural network algorithm, Self-Organizing Maps (SOM, Kohonen, 1982;Liu et al., 2006), to train joint solutions coming from the HFR measurements and numerical weather prediction model as hourly surface currents and surface winds, respectively. Once the joint SOM solution has been trained, the surface current forecast 410 follows the predicted surface winds being the closest to the specific SOM solution (Fig. 6). Such a system prerequisites a strong relationship between the predictor (here surface winds) and the predictand (here surface currents), which is largely found in coastal regions of the Mediterranean, yet it can be applied for any other combination of predictors and predictands.
Also to add, high-frequency processes such as tides are removed from the system as being minor to the wind-driven dynamics, yet the tides can be added to the forecast. 415 The quoted northern Adriatic forecast system has been trained using 20 SOM solutions (so-called Best Matching Units, Liu et al., 2006) on HFR data measured between February and November 2008 conjoined with 3-hourly surface winds interpolated to 1-hour resolution coming from Aladin/HR operational model run once a day by the Croatian Meteorological and https://doi.org/10.5194/os-2021-115 Preprint. Discussion started: 14 December 2021 c Author(s) 2021. CC BY 4.0 License.
Hydrological Service (Tudor et al., 2013). The forecasting system performance has been tested in the forecast (hindcast) mode during 2009 and 2010. Unfortunately, the HFR system had substantial problems since 2010, while the antennas were removed 420 in the following years, resulting in a relatively short dataset possibly not sufficient to put a strong reliability to the forecasting system solutions. However, Vilibić et al. (2016) compared this SOM-based forecasting system with the operational ROMS -Regional Ocean Modelling System- (Shсhepetkin andMcWilliams 2003, 2005) ocean model for the Adriatic and found that the SOM-based forecasting system performed better, having lower biases and root-mean-square errors.
As HFR measurements expanded a lot in the last decade, both in space (new HFR systems) and time (longer time series), such 425 a forecasting system that uses self-learning algorithms might be applied to other Mediterranean locations, in particular to those having multi-year surface current datasets. For such sites, the stability of SOM-solutions in time may be tested as well, or the self-learning and training of SOM solutions might change in time to properly reflect long-term changes in oceanographic conditions in a coastal area.

Extreme hazard coastal monitoring
Under the current climate-change scenario, no portion of the coastline is safe from the threat of metocean hazards, which are expected to increase in frequency, duration and virulence during this 21 st century (Mitchell et al., 2006;Stott, 2016). HFR constitute a profitable asset for wise decision-making since it presents a wide range of practical applications, including the effective monitoring in near real time of extreme coastal hazards, such as extreme wind events, severe river discharges, storms and strong flow reversals (see further details in Sect. 2.2.1.), storm surges, tsunamis (more information available in Sect. 2.2.2), typhoons and hurricanes (Barrick and Lipa, 1986;Miles et al., 2017;Lipa et al., 2019).
A detailed characterization of unusual phenomena in coastal areas as well as the increasingly retrieval of waves and winds 440 maps derived from HFRs, is very relevant for the Blue Economy emerging and innovative sectors, including marine renewable energy, among others.

Extreme events monitoring
HFRs have been used to investigate the response of coastal submesoscale structures, shaping surface currents and passive transport, to an extreme wind event in the Ligurian Sea, a sub-basin in the North-Western Mediterranean during October-445 November 2018, as described in Berta et al. (2020). The analysis was based on estimates of kinematic properties' pattern and magnitude from surface currents measured by the HFR-TirLig network before and after the extreme wind event. In particular this work focused on divergence/convergence and vorticity characterization indicative of the evolution of ocean scales at a few kilometers.
During the storm, sea surface vorticity (Fig. 7, top panels) and divergence (not shown but available in Berta et al., 2020)   In the Delta of the Ebro river, also in the North-Western Mediterranean coast, the HFR-Ebro system observations have been crucial to capture the evolution of the most extreme Ebro river freshwater discharge event registered over the last 15 years in April 2018 and the high impact of the freshwater-pulse discharged on the surface circulation pattern (Ruiz et al., 2020). Results 460 show that the surface circulation pattern is highly influenced by the river discharge, exhibiting a clear correspondence with high concentrations of satellite-derived Chl-a concentration. Hovmöller diagrams of HFR derived meridional and zonal currents indicate an increase of the south-eastward velocity during the period of the extreme river discharge. The proper representation of the basic oceanographic features of the HFR-Ebro, as the Ebro river impulsive-type freshwater discharged, was previously reported by Lorente et al. (2015). 465 This same region has been severely impacted by an exceptional storm in January 2020. Particularly for this event,  have recently assessed the ability of the HFR-Ebro to characterize waves and currents under the record-breaking storm Gloria (19-24 January 2020) and evidenced its remote-effect in adjacent choke-points of the NW-Mediterranean, adding to the analyzing the data from the HFR-Ibiza and HFR-Gibraltar. Furthermore, the effect of Gloria on the particle's dispersion at the Ebro river's mouth has been established. The main findings are the identification of: (i) the storm Gloria as an extreme 470 event in the NW Mediterranean Sea, considering the persistent surpassing of the 99th percentile for several parameters (i.e. Gibraltar, which altered the usual water exchanges between adjacent sub-basins. Specifically, the flash pressure drops of about 18 hPa in 27 hours in the Ibiza Channel causes very strong easterly winds of about 11 ms -1 by the end of the 19th January. As 475 a result, surface current speed reached its monthly maximum of 0.6 ms -1 , showing a clockwise veering from NE, to SW during the storm and to NW afterwards. In the Strait of Gibraltar, the Atlantic Jet speed decreased one third and the HFR registered a uniform inversion of the surface circulation with westwards currents above 0.7 ms -1 on the 20th of January. In the HFR-Ebro system the maximum current speed of about 0.87 ms -1 was registered on the 21st of January towards the S-SW, surpassing all values, i.e. the mean value of about 0.16 ms -1 ; the P99 of ~0.34 ms -1 , being more than twice the mean and the peak value of 480 0.53 ms -1 registered during the severe 2017 event (iii) areas of elevated instantaneous rate of separation (IROS) at Ebro river mouth, indicative of high rates of particle dispersion, which reached a peak by January 21st.
Strategically located at the only natural entrance from the Atlantic Ocean to the Mediterranean Sea the HFR system installed in the Strait of Gibraltar (SoG) can be considered to be an appropriate asset to effectively monitor the Atlantic Jet (AJ) inflow (Lorente et al., 2019b). The classical picture of the surface circulation is characterized by current pulses often exceeding 2 ms -485 the AJ and quasi-permanent inversion of the surface inflow during prevalent intense easterlies is a singular phenomenon that deserved detailed exploration (as previously mentioned in Sect. 2.1.2). Under this temporal premise, a monthly Hovmöller diagram was computed for HFR-derived zonal currents at the selected transect to easily detect a 2-day full reversal episode during March 2017, represented by black boxes in Fig. 8, a. The event detected consisted of an abrupt interruption of the 490 eastward inflow and complete reversal of the surface stream through the narrowest Sect. of the SoG (Fig. 8, b). The circulation in the easternmost region of the study domain was accelerated up to 0.8 ms -1 , following clockwise rotation that likely fed the Western Alboran Gyre (WAG), which was out of the picture.
The prevailing atmospheric synoptic conditions were inferred from ECMWF predictions of sea level pressure and zonal wind at 10 m height (U-10), as shown in Fig. 8, c-d. A significant latitudinal gradient of sea level pressure was observed, with high 495 pressures over the Gulf of Biscay and isobars closely spaced in the SoG, leading to extremely intense easterlies (above 10 ms-1), channeled through the Strait due to its specific geometric configuration. Therefore, high pressures and intense, permanent, and spatially-uniform easterlies prevailed over the entire study domain, inducing a westward outflow through the SoG as revealed by the 2-day averaged HFR circulation maps. Local wind forcing at this scale seemed to play a primary role in explaining such AJ collapse and the related inflow reversals in agreement with previous studies (Garret, 1983;García-Lafuente 500 et al., 2002;Menemenlis et al., 2007;Péliz et al., 2009;Reyes et al., 2015;Lorente et al., 2019bLorente et al., , 2019bBolado-Penagos et al., 2021).

Tsunami detection
Tsunami early warning and alert is an emerging and promising application of HFR. The main principle underlying the detection is that the abnormal surface current pattern induced by the orbital velocity of the tsunami wave train can be measured and interpreted in real-time by an appropriate detection algorithm. The idea was first proposed by Barrick (1979), but it was only after the 2004 Indian Ocean disaster that the proof of concept was made on the basis of actual HFR data. It was shown 515 numerically with simulated (e.g. Lipa et al., 2006;Gurgel et al., 2011) and real (e.g. Lipa et al., 2011Lipa et al., & 2012Dzvonkovskaya et al., 2012) events that the tsunami signature could be clearly seen in the HFR radial currents and some appropriate detection algorithms were proposed. One strong point of HFR tsunami detection is that it is not bound to the nature of the source (seismic https://doi.org/10.5194/os-2021-115 Preprint. Discussion started: 14 December 2021 c Author(s) 2021. CC BY 4.0 License.
or atmospheric) and can be used as a useful complement to other warning systems in places where those are either not available or non-effective. Today, more than 20 real tsunamis have been detected 'offline' with the reanalysis of HFR data. In view of 520 the growing interest for these new capabilities of HFR, some radar manufacturers now provide commercial toolboxes along with their hardware system for the early detection of tsunamis; such systems have been installed in some places at risk (e.g. Vancouver Island Canada, Oman, New Jersey USA, SW Portugal). To date, the only real-time detection was issued following a meteo-tsunami that occurred on 1 October 2016 in Tofino, BC, Canada (Dzvonkovskaya et al., 2017;Guérin et al., 2018).
However, no such HFR tsunami alert system has been yet installed in the Mediterranean Sea. Nevertheless, there is a non-525 negligible tsunami hazard in this region, as witnessed by very destructive co-seismic events in recent history (e.g. Messina, Sicilia, 1908). Some worst-case scenarios with a strong (M7.8) earthquake in the North Algerian margin predict important tsunami waves with 3-4 meter amplitude on the French-Italian Riviera (BRGM, 2007). Moderate earthquakes such as the M6.9 21 May 2003 Boumerdes-Zemmouri are sufficient to cause 1-3 meter amplitude harbor oscillations within 40-60 minutes in the Balearic Islands, which would be the most impacted spot by seismic sources in North Algeria (Wang et al., 2005;Sahal et 530 al., 2009). The impact in the French Mediterranean coast impacted by a seismic source in the North Algerian margin is shown in Fig. 9. In addition to co-seismic tsunamis, frequent meteo-tsunamis (i.e. tsunamis of meteorological origin) have been reported in the Balearic Islands, named -"rissaga"- (Jansa, 2007), Adriatic Sea -"šćiga"- Orlić, 2015), Sicily Channel -"marrobbio"- (Candela et al., 1999;Zemunik et al., 2021), Malta -milgħuba"- (Drago, 2008), northern Persian Gulf 540 (Kazeminezhad et al., 2021), Black Sea (Vilibić et al., 2021) and Aegean Sea (Papadopoulos, 1993). Even though these events have limited regional impact, they can cause severe local damages in harbors and bays due particularly to the micro-tidal regime, resulting in rapid sea level changes (Vilibić et al., 2021). Indeed, the strongest known meteo-tsunami in the these are mostly the so-called Proudman-, Greenspan-, shelf-resonances in coastal areas which can lead to strong harbor resonances in semi-closed basins (Orfila et al., 2011). Today, the generation of these meteotsunamis is better understood Šepić et al., 2009Vilibić and Šepić 2009;Ličer et al., 2017) but their prediction is still a very 550 challenging task (Denamiel et al., 2019, Romero et al., 2019. When located in the areas affected by the meteotsunamis, HFR-based tsunami early warning systems could be a useful complement to these forecasting systems, helping issuing specific alerts on the basis of the actual observed surface currents 20-40 km offshore a few minutes before the generation of the extreme sea level oscillations. Note that tsunami early warning systems only require a software update of existing HFR and could be installed at reduced cost in some places. However, some 555 strategic spots are not covered yet and would deserve a novel installation to monitor the travel directions of incoming waves from the most probable sources (North Algerian earthquake, West Corsica submarine mass failure, North Ligurian earthquake, etc.). Another related issue is extending the range of these HFR, which would imply operating at lower frequency bands (4-5 MHz or 9 MHz) than those usually employed in the Mediterranean region (13, 16 or 25 MHz). Nevertheless, a software for tsunami detection and warning has been installed in the HFR site located in Sagres (Portugal), which operates at 13 MHz 560 (Roarty et al., 2019). Such a prototype operating at 4.5 MHz with 200-300 km range was developed by the Diginext Ltd. a few years ago (i.e. Stradivarius radar) on the French Mediterranean side to monitor a large part of the Gulf of Lion. A proof of concept was made that such radar could provide early alerts of plausible tsunamigenic sources in the Mediterranean Sea (Grilli et al., 2015). Such HFR systems can serve the double purpose of warning and characterizing abnormal surface current patterns arising from tsunami-like waves of seismic or atmospheric origin. As recently suggested, they can also be used as proxies for 565 the observation of low-pressure fronts of atmospheric gravity waves that could lead to storm surge, if not meteo-tsunamis (Domps et al., 2020).

Environmental Transport Processes
In the Mediterranean, as elsewhere in the world, the coastal zones serve as the main entry point of nutrients, pollutants and sediments into the ocean, being the multi-scale coastal ocean dynamics key drivers for their transport, also impacting their 570 dispersal and retention and the cross-shelf exchanges. HFRs have demonstrated to provide very valuable measurements to continuously monitor the mesoscale structures and frontal dynamics that organize the coastal surface flow and associated transport, by the developments in the understanding of Lagrangian dynamics from HFR data . The comprehension of the coastal ocean conditions and variability underlying ocean productivity that correlate with fish stock abundance, fish recruitment in coastal areas, dispersion and retention of larvae, etc., is critical for a sustainable management of fisheries resources (Sciascia et al., 2018), being also essential to assist water quality management by tracking source and drift of pollution (e.g. chemical, sewage, oil spills or harmful algal blooms). In the Mediterranean Sea, the applicability of HFRs in this field is particularly relevant since, in addition to its limited exchange with the oceanic basins, its microtidal character and its intense internal meso and submesoscale circulation reduces the potential of dilution and dispersion of dissolved and particulate wastes, maximizing the impact of one of the most commonly identified threat (e.g. marine litter and 580 contaminants). In addition, despite being considered one of the most oligotrophic areas in the world ocean, it is also one of the world's hot spots for biodiversity (Coll et al. 2010, Gabrié C., et al. 2012, providing vital areas for the reproduction of pelagic species (e.g. Atlantic bluefin tuna, white shark and sea turtles) and hosting sensitive ecosystems in the shallow coastal waters.

Pollution and floatables tracking
Coastal areas are very sensitive to pollution impact, in terms of environmental and ecosystem impact as well as economic and 585 societal consequences, and can be both source and target of pollution. Coastal regions in the Mediterranean Sea are heavily inhabited with strong tourist and maritime activity resulting in human and industrial waste intentionally or accidentally dumped into coastal waters. These pollutants evolve according to their chemical transformation over time and are caught in the 3D general circulation and carried offshore and to other distant coastal areas by currents. For example, heavy metals or other chemical contaminants that may be present in semi-enclosed harbors (Tessier et al., 2011)  Coastal and littoral areas are also vulnerable target regions for pollution. Detecting, monitoring and cleaning up oil slicks following an offshore spill before they reach the coast is a major challenge. Consequently, monitoring, understanding and forecasting coastal dynamics is a critical step to develop adequate strategies to mitigate the effects of pollution in marine 595 environments, from or towards coastal areas. However, forecasting coastal dynamics is one of the most challenging issues in geosciences due to their strong space-time variability as well as the complexity of the processes controlling the dynamics that interact simultaneously over a broad range of time-space scales, as previously highlighted in Sect. 2.1.2. Thanks to the fast growth of HFR as a key element of coastal observing systems, coastal currents can nowadays be measured in relatively large coastal areas providing a regional synoptic view of the surface dynamics with high spatial and temporal resolution. filaments at sub-grid scales generated by the chaotic mixing, providing an improved description of transport phenomena in geophysical flows and complementing the Eulerian metrics. The Lagrangian framework indeed allows to effectively track the physical processes occurring along the history of the fluid parcels, which clearly is of utmost relevance for biogeochemical 610 and biological dynamics (Hernández-Carrasco et al., 2018a; or for the tracking of pollutants, such as plastics, or for modeling the interaction between different substances, e.g. biofilm-covered microplastics with marine biogenic particles (Michels et al., 2018). Here we provide evidence to support the reliability of the HFR currents for tracking substances at coastal areas. The Lagrangian validation has been performed using data from 8 drifters' trajectories available in the domain of the HFR area of coverage in the Ibiza channel (HFR operated by SOCIB,  during October 2012. Moreover, we use the HFR velocity 630 fields to compute the Lagrangian Coherent Structures (LCS) which are very suitable to provide a template of the fluid flow transport (see Haller, 2015, and references therein), allowing the detection of transport barriers, which are of great relevance for marine dynamics. For example, LCS obtained from ridges of the Finite Size Lyapunov Exponents have been correlated with filaments of remote-sensed Chl-a (Lehahn et al., 2007;Hernández-Carrasco et al., 2014, 2018a, sea bird foraging behavior (Tew Kai et al., 2009), with the modelled extension of oxygen minimum zones (Bettencourt et al., 2015) and with 635 wind forcings (Berta et al. 2014b). At coastal scales, the dynamical picture in the Lagrangian frame has been analyzed using data from HFR currents to identify relevant small-scale transport barriers (Lekien et al., 2005;Gildor et al., 2009;Rubio et al., 2018), some of them focusing on coastal areas of the Mediterranean Sea (Haza et al., 2010;Berta et al., 2014b;Hernández-Carrasco et al., 2018a). As seen in Fig. 10, by integration of Eq. (2) for a set of virtual neutrally buoyant particles initially deployed on the northern and southern flank of a given LCS measured from the HFR-Ibiza in Jan 25th, 17:00 UTC in 2013 (Fig. 10a). Although the location and magnitude of this LCS evolve in time, the LCS persists for several hours manifesting the presence of a coherent transport barrier preventing both sets of particles to be mixed up. A meridional LCS is formed and maintained during the simulated period, limiting water exchanges between the coast and the open ocean (Fig. 10a-c). Besides, coastal waters are enriched in nutrients from river outflows, sediment resuspension and coastal upwelling, that can also contain increased quantities of pollutants (e.g. floating marine litter). The physical mechanisms that contribute to the offshore transport of these mesotrophic coastal waters to the oligotrophic offshore areas are critically important for boosting 650 oceanic primary production and sustaining the trophic chain. The mechanisms that can influence the escape times of these waters in a target area can be monitored by means of the Lagrangian properties derived from the HFR by means of the residence times and the escape rate/times . Using as input gap-filled HFR velocity fields a Lagrangian Particle-Tracking Model (Eq. 2) provides the particle trajectories. From the Lagrangian model outputs, it is possible to infer the characteristic time-scales for transport processes in the HFR footprint area by means of the escape rate of active particles (Fig.  655   11). Thus, HFR shows to be an excellent tool to monitor conditions and identify the different scenarios that favor the local retention and dispersal of shelf waters in two study areas under the influence of ocean boundary currents.

Eddy tracking
Ocean eddies are ubiquitous, pervasive flow structures which dominate the ocean velocity field at several scales, from the meso-to the local scale (Chelton et al., 2011). They play a fundamental role in sea dynamics, being responsible for the energy transfer among different scales (down to the dissipative range) as well as for their ability to transport nutrients, biomass, sediments and pollutants. Mesoscale eddies, produced by geostrophic instabilities, are not able to advance the energy transfer, 665 being constrained by geostrophic and hydrostatic balance (Charney, 1971). When the balance is broken, the downscale may continue through inertia-gravity waves emitted from currents, ageostrophic instabilities, and bottom boundary layer turbulence, which are responsible for the formation of submesoscale eddies. At a lower scale, three-dimensional turbulence proceeds toward the dissipative range (McWilliams, 2019).
The presence of ocean eddies has become more evident in recent years, thanks to the introduction of new oceanographic 670 measurement techniques, while their exhaustive characterization would require synoptic time series of the velocity field in the ocean (Robinson, 1983). Such synoptic observations are made available only through satellite data, however, besides being limited to relatively large scales, and preferably to the open ocean, they do not provide direct measurements of the total velocity field. Indeed, altimetry data can be used to retrieve the surface geostrophic field, which lacks a possibly important portion of the dynamics (Rinaldi et al., 2010;Conti et al., 2016). Other ways to observe eddies from satellites consist in the observation 675 of their presence in the sea surface temperature or in the tracer field patterns, as displayed by ocean color (Robinson, 2010).
Coastal HFRs overcome all the above limitations and provide direct measurements of the total surface velocity field at high spatial and temporal resolution, thus enabling to detect and follow the time history of surface eddies down to submesoscale, at the cost of a reduced spatial extent. 2000; Kirincich, 2016b;Archer et al., 2017;Lai et al., 2017;Arunraj et al. 2018). It is worth noticing that such features may have a strong vertical signature that HFR data fail to account for, and therefore need to be complemented with further information, spanning from direct measurements of the horizontal and vertical velocity profile to indications indirectly derived from, e.g., satellite turbidity measurements (see discussion in Uttieri et al., 2011). 685 A vast HFR network now covers the North-Western Mediterranean coastal areas (see Lorente et al., submitted to this Special Issue), which is characterized by significant mesoscale variability and eddy generation that, in some cases, shows recursive and seasonal patterns. Allou et al. (2010) used HFR to observe and characterize vortex structures, mostly anticyclonic, in the Gulf of Lion. They also argued they were correlated with specific wind patterns. Schaeffer et al. (2011) improved the analysis and employed both HFR measurements and numerical modeling to analyze the eddy generating mechanism. They found it is 690 primarily influenced by wind forcing and its interaction with topographic constraint (northerly offshore wind), and freshwater input from Rhone river (southerly onshore wind). The combination of HFR and in-situ observations, and modelling tools, allowed Guihou et al. (2013) to identify an anticyclonic coastal eddy which was generated in front of Nice by a meander of the Northern Current, and advected downstream toward the Toulon area, interacting with the mean circulation. More recently, the analysis of the long 2012-2019 HFR time-series in Toulon allowed to identify cyclonic and anticyclonic recurrent eddies 695 mainly generated by wind and boundary current undulations (Bourg and Molcard, 2021).  Bagaglini et al. (2020). The former, even though developed for HFR data (and for high resolution numerical model outputs), has found a widespread range of applications to observations collected by different platforms, as witnessed by current oceanographic literature (Liu et al., 2012;Dong et al., 2014). It is a method based on the geometry of the velocity vectors. It was conceived for geostrophic or quasi-geostrophic recirculating features, showing very little divergence. For this reason, it is very suitable to describe mesoscale eddies, but may fail in detecting submesoscale 710 ones, which often are characterized by divergence or convergence and by a high degree of deformation of the velocity field geometry. The YADA (Yet Another eddy Detection Algorithm) algorithm developed by Bagaglini et al. (2020) was conceived specifically to overcome this limitation and be utilized to automatically detect submesoscale eddies, which may exhibit highly non-geostrophic characteristics. It is a hybrid method, which focuses on both the dynamical and geometric features of the velocity field, first identifying the local extrema of a dynamical field characterizing recirculation (e.g., the local normalized angular momentum, see Mkhinini et al., 2014; or the Okubo-Weiss parameter, Okubo, 1970;Weiss, 1991), similarly to the first step from AMEDA (Angular Momentum Eddy Detection and tracking Algorithm) defined by Le Vu et al. (2017), and thereafter analyzing the streamline geometry in a neighborhood of the extremum. The YADA (Bagaglini et al., 2020) has been successfully applied to 1 km-resolution HFR data from the Gulf of Naples, showing its ability to identify strongly asymmetric, convergent or divergent submesoscale eddies. Its application to coastal HFR data from other areas of the Western 720 Mediterranean is presently under way.
The HFR system from LaMMA Consortium (described in Lorente et al., submitted to this Special Issue) covers part of the Ligurian Sea and the Tuscany Archipelago, which is a shallow area separating the Ligurian and Tyrrhenian basins, bordering eastward the Corsica Channel, with complex topography and coastal morphology, also due to the presence of several islands (Elba, Capraia, Montecristo, Gorgona). Sea dynamics are strongly influenced by seasonality and characterized by the presence 725 of the Tyrrhenian boundary current and its bifurcation, the Eastern Corsica Current (Astraldi and Gasparini, 1992;Millot, 1999;Vignudelli et al., 2000). Through drifters, in-situ data, and a numerical model, Poulain et al. (2020)    Furthermore, Fig. 13 shows the results of the application of the algorithm by Nencioli et al. (2010) to the whole year 2019, which provided a seasonal census of anticyclonic and cyclonic eddies in the area sampled by the LaMMA HFR system. The HFR coverage was not uniform during the year with generally lower percentages for the warmer seasons (i.e. spring, summer). 745 The area north of Elba island was characterized by the highest eddy activity throughout the year, with a predominance of anticyclonic eddies in colder seasons, and a clustered pattern in summer, showing anticyclonic eddies east of Capraia island and cyclonic ones toward the coast.
The number of detected eddies depended also on the availability of HFR data; indeed, a smaller number of eddies was found in spring (28) with respect to the other months (62 winter, 68 summer, 62 autumn). Median eddy life-span was around 1.125 750 days for all seasons, even if they were able to survive up to 6 days, except in spring.

Figure 13. Maps of the area covered by the LaMMA HFR network showing the percentage of HFR data availability along 2019 for a) winter; b) spring; c) summer and d) autumn. The Tuscany Archipelago (i.e. Elba island) is at the lower-right corner of the figures. Tracked cyclonic (black) and anticyclonic (red) eddies detected in each season are overlaid. 755
Although the present work is preliminary, it may lay the basis for a detailed analysis concerning the seasonal features of eddy activity within the Tuscany Archipelago, and its effect on the general circulation. Surface currents from HFR can be combined with the numerical model outputs both to bridge the gap relative to the spatial and temporal coverage of data, and to improve reliability with respect to the actual sea dynamics.

Transport of biological quantities and connectivity 760
The necessity to preserve the marine ecosystem equilibrium and the water quality, has fostered the use of HFR data in supporting the coastal zone management and assessing the variability in the dynamics of marine ecosystems. In particular, HFR data have been used worldwide to address ecological and water quality issues such as: to understand the transport and retention processes of plankton or wastewater discharge in some regions of NW Spain (Ria de Vigo)  and Western Mediterranean (Hernández-Carrasco et al, 2018a), at coastal upwelling fronts off central California (Bjorksted and Roughgarden, 1997) and in Monterey Bay (Coulliette et al., 2007); to investigate the enhancement of productivity due to the retain of phytoplankton within the flow in the Santa Barbara Channel (Brzezinski and Washburn, 2011) (Cianelli et al., 2013). An oscillating plankton population dynamic has been also frequently observed in the GoN, at Long-Term Ecological Research 775 station MareChiara (LTER-MC), where plankton abundance is monitored weekly at the since 1984. A proof of concept study (Cianelli et al., 2017), was thus conducted in order to characterize the spatial scales and the provenance of phytoplankton assemblages detected at LTER-MC and to dissect processes regulating plankton dynamics.
The study focused on a year-long analysis carried out for 2009, which was characterized by a very accurate estimate of the surface dynamics, with a reduced number of gaps among ecological measurements and HFR data. The approach followed 780 these conceptual steps: (i) Reconstruction of the annual and seasonal regimes of HFR currents detected at the LTER-MC site; (ii) Running Lagrangian backtracking simulations. Virtual phytoplankton patches (VPPs) were released at LTER-MC on the dates of the weekly oceanographic campaigns and tracked backward in time (up to 96 h earlier) to their zone of origin (Fig.   14, a); (iii) Identifying spatial scales of horizontal transport of virtual phytoplankton patches in the GoN (Fig. 14, b); (iv) Comparison among backtrack Lagrangian reconstruction and ecological analysis based on salinity and chlorophyll a data 785 obtained through weekly sampling at LTER-MC (Fig. 14, c); (v) Identifying different modes of coupled physical and ecological functioning in the GoN as resulting from physical transport and biological processes ('allogenic' and 'autogenic' factors, respectively). The results showed an alternation in plankton dynamics between phases reflecting the influence of coastal (green) and offshore (blue) circulation patterns on the biological community. The phytoplankton community detected at LTER-MC generally originated from the coast, whereas the offshore inflow marginally changed the main traits of phytoplankton assemblages.
Back-tracking simulations and biological data strictly agree, highlighting that the plankton community at LTER-MC during 2009 is affected by the alternation of coastal and offshore influence. 805 Biological autogenic factors drive the modifications of coastal phytoplankton communities during the coastal 'green' phases, thus suggesting that the GoN tends to retain the same communities via coast-ward circulation, especially during summer.
Physical allogenic factors are determinant in driving dilution and species advection of coastal phytoplankton, during the offshore 'blue' phase. This marked alternation between coastal and offshore water masses acts to promote phytoplankton https://doi.org/10.5194/os-2021-115 Preprint. Discussion started: 14 December 2021 c Author(s) 2021. CC BY 4.0 License. diversity, because the dilution in the phytoplankton density may decrease the impact of the dominating species over the 810 available resources.
The integration of long-term biological data and high-resolution current fields represents an optimal tool to investigate the role of surface circulation in structuring the marine plankton community, thus confirming the value of HFR systems to analyze the seasonal fluctuations in marine ecosystems dynamics and to unveil the mechanisms of coastal connectivity.
The GoM is a well-known recruitment area in the Adriatic Sea (Sciascia et al., 2018;Corgnati et al., 2019a). In this region, 815 HFRs have been used to understand the role of ocean currents in the recruitment of small pelagic fishes (i.e. European sardines, Sardina pilchardus). Fig. 15 shows residence times within the GoM, estimated using trajectories of virtual drifters computed from the surface currents measured by HFRs. Months with high (October)/low (February) residence times are associated with weaker/stronger surface currents in the central area of the Gulf. The relatively short (<12-day) average residence times have shown that local spawning is less likely to take place than the transport to the Gulf from remote spawning areas through 820 advection pathways. Results agree with otolith measures, suggesting that the arrival of larvae within the Gulf is characterized by repeated pulses from remote spawning areas that are likely to play a fundamental role in maintaining the nursery.

(left panel) and February 2014 (right panel). Black squares represent the locations of the four HFR antennas along the Manfredonia gulf. Adapted from: Sciascia et al., 2018.
The Malta-Sicily Channel is both the most fished area in western Mediterranean Sea and a very important hotspot of biodiversity (Médail & Quézel, 1999). In this region, Capodici et al., (2018) combined the HFR-CALYPSO surface currents together with satellite images of chlorophyll-a concentration -CHL-and Sea Surface Temperature -SST-, to explain physical 830 driven mechanisms that can help interpret ocean productivity and plan maritime activities in a more adaptive and proactive way. On the one hand, as mentioned by the authors, monitoring water quality data provides valuable insight into the understanding of processes driving spatial and temporal changes in productivity at sea (Behrenfeld et al., 2006). CHL and SST are generally accepted as proxies for water quality and are very helpful to detect upwelling events, which are frequently occurring along the Sicilian coast. In particular, sea currents are responsible for dispersion, transport or retention of nutrients 835 of which CHL is widely used as a proxy variable; moreover, current jets or eddies are often observable as cold or warm areas in the SST maps, respectively. Even if both CHL and SST maps are usually retrieved by means of satellite data maps, cloudiness often reduces the satellite data availability; thus, temporal aggregated products (e.g. at 8 or 16 days) are the only data available. In this framework, the integration of sea surface current data provided by HFRs can fill the gap of knowledge due to the inadequate temporal (and sometimes spatial) resolution of these water quality maps. Capodici et al., (2018)

Discussion and preliminary assessment of the HFR regional capabilities
This initial inventory of HFR applications implemented in the Mediterranean coastal areas have allowed us to know their strengths and weaknesses to further contribute to the regional observing system in addressing the regional environmental 860 threats, the scientific priorities and the society needs. Considering also the current threats and the opportunities ahead along this decade, we have conducted a SWOT (i.e. strengths, weaknesses, opportunities, and threats) analysis, as schematized in the Fig. 17, and as discussed in this section for each one of the three challenges: i) maritime safety; ii) extreme hazards and iii) environmental transport process.
In the sphere of maritime safety, the main strength of HFRs is the provision of high spatio-temporal resolution surface currents 865 in wide coastal areas, where most of the SAR incidents occur. HFRs complement other scarce observations, helping to assess and to improve the ocean models, through data assimilation, or being used as alternatives of the models for backtracking drifting objects in near-coastal risk-prone environments. In addition to that, the machine learning approach where a neural network model is trained on past data and then used to create short term predictions is gaining ground in recent years. The steadily growing of the European HFR network (Rubio et al., 2017;Roarty et al., 2019), increasing both the coastal coverage in many countries and the length of the time series, will allow us to implement these self-learning algorithms in other Mediterranean areas. Nevertheless, there is a strong need for consensus on the methodology to generate these scientific addedvalue products, and on the definition and further adoption of a common data and metadata model as well as the quality control tests, to operationally distribute standardized HFR gap-filled data and derived STPs, helping to unlock HFR data potential for their use in several Lagrangian applications. Moreover, the use of the HFR data for data assimilation and model assessment 875 should be boosted through the provision of data uncertainties (Moore et al., 2019).
As a land-based remote sensing technology, HFRs are able to continuously monitor the surface's coastal ocean response to extreme events, by providing near real-time information of the surface's ocean response on a continuing basis. In this context, HFR strength is based on its no deployment requirement, avoiding the risk to be faced by other observing platforms (i.e. research vessels, ferry boxes or even autonomous instruments), being also unaffected by cloud cover and making also easier 880 their routine maintenance tasks under these severe episodes. Furthermore, it is worth to be highlighted that under severe weather phenomena, near-real time met-ocean information gains value since it is essential to avoid risky situations and to support the emergency response at sea. This capability has allowed us to monitor and deeply investigate the impacts of intense wind episodes, severe river freshwater discharges and record-breaking storms as well as to observe the weakening or even the reversal of main surface currents and jet streams. Furthermore, their demonstrated improved capacities to detect tsunami-885 induced currents make it a valuable complement to other warning systems in the Mediterranean. Nevertheless, and despite the existing tsunami risk and the frequent occurrence of meteo-tsunamis in the Mediterranean Sea, no HFR tsunami alert has still been installed in this region. Facing a growing interest in these HFR new capabilities, several challenges must be previously addressed regarding the installation of new systems to monitor the most probable source areas and the extension of the range by using lower operational frequencies as usual in the Mediterranean Sea to be able to detect the tsunami-induced currents far 890 offshore, to offer early warning.
The recognized capabilities of the continuous HFR observations to analyze the transport properties of the surface flow and to detect and track surface eddies down to submesoscale, have allowed us to understand the phytoplankton distribution, to identify different local retention scenarios, and to investigate the role played by the characteristic mesoscale variability and eddy generation in the transport of biomass, pollutants and in the recruitment and abundance of small pelagic 895 species in the Mediterranean coastal waters. In this regard, it has fostered the use of HFR data in supporting the coastal zone management and assessing the variability in the dynamics of marine ecosystems, becoming an asset of great value to contribute in the achievement of the Good Environmental Status (GES) of the Mediterranean waters. However, it has been found that the number of detected eddies depended also on the HFR data availability, highlighting the need to combine the HFR with numerical model outputs both to bridge the spatio-temporal gap and to improve reliability. It should also be noted that the HFR 900 limited coverage reduces the potential of the larger scale applications and connectivity studies, thus requiring their integration with other in-situ and satellite observations as well as models, being these applications also benefited from the future expansion of the HFR network. Considering the high spatio-temporal resolution of HFR derived surface currents being one of its main competitive strengths when compared versus other observing platforms, it must be recognized that its most serious limitation is that it provides 905 information at the very near surface layer. In order to fully understand ocean dynamics, the knowledge of the water column processes is essential as well. A significant number of coastal ocean observatories in the Mediterranean Sea (as described by Tintoré et al., 2019) encompass a complex multi-platform network including HFRs, aiming to meet the primary but challenging need to monitor both the surface and the water column. This has motivated the development of techniques able to combine the information of the processes in the entire water column, in order to provide a three-dimensional picture of the overall dynamics. 910 The combination of such observations is challenging mainly for two reasons: surface and ocean interior are prone to different processes and forcings with different spatio-temporal scales and at, the same time, the capabilities to resolve and characterize the diverse processes may be different for observing platforms at the sea surface and in the water column. Despite the promising results obtained by Berta et al. (2018) and Guihou et al. (2013) in the Mediterranean Sea, necessary efforts must continue towards the further development of methodologies to combine HFR data with water column measurements and models. 915

Future prospects for HFR applications and recommendations
Finally, after the description of the current implementation status of the HFR applications in the Mediterranean coastal areas, and based on the results obtained from the SWOT analysis, we present here the prospects for the future and a set of key 920 recommendations. These recommendations aim to ensure that the potential of HFR is fully exploited in the development of operational monitoring systems at the regional level, helping also to derive the added-value achieved by the European HFR network (i.e. centralization of the data management and standard data distribution, new products development, crossdisciplinary emerging applications, training schools, etc). These recommendations should be part of the long-term monitoring strategy for structuring the ocean observation at the regional level, for the development and integration of the COOSs towards 925 addressing key scientific questions and meeting the societal challenges related to the Mediterranean coastal regions, being always aligned with the European strategies to ensure the integration.
Although the future prospects for the HFR data use and applications at the regional level are shared far beyond the geographical borders of the Mediterranean Sea, the regionalization of the recommendations constitutes a benefit: i) to coordinate crossnational efforts; ii) to account for regional specificities (in terms of scientific key priorities, societal needs and existing 930 environmental threats) and iii) to map the existing and potential HFR data end-users, also facilitating the interaction with them. Therefore, we specifically address them in this section, as follow: In this regard, it should be noted that the spatio-temporal scales currently provided by the HFRs in the Mediterranean allow us to monitor the current environmental threats adequately, but always in limited coastal areas, thus reducing the potential of the larger scale applications (e.g. transport of organic matter and pollutants, connectivity studies, 940 data assimilation into models, etc). Therefore, aiming to improve regionalization of the observatories for a better understanding of region-specific processes towards a fit-for-purpose design, an increased monitoring effort by expanding and improving the HFR network is required, allowing for a covering of a large geographical area on a routine basis. Accordingly, it is needed a previous review of major scientific and social questions, the environmental stressors and their impacts in the Mediterranean waters and blue sectors, identifying the benefit of the new deployments, in coordination with the current monitoring actions 945 (e.g. to identify gaps for monitoring these risks, ensuring cost-effectiveness of observations, etc). To this end, the cross-border coordination activities are key for the involvement of other countries bordering the Mediterranean Sea in the eastern and southern coastlines and to address issues related to frequency sharing for avoiding interferences, as highlighted in Lorente et al., submitted to this Special Issue. https://doi.org/10.5194/os-2021-115 Preprint. Discussion started: 14 December 2021 c Author(s) 2021. CC BY 4.0 License. b) Reinforcing the Mediterranean's leadership for continuing to be a major European focus of HFR activity. The 950 Mediterranean institutions are key players in the European and international HFR research effort in multidisciplinary fields and in the development of applications, as mostly covered in the Sect. 2 of this work. In addition to that, HFR experts from the Mediterranean institutions are currently and actively contributing in the definition of the European HFR network roadmap, leading crucial tasks aiming to define the standard model, increase the availability and accuracy of the HFR wave parameters and to reach a consensus on the methodology for the provision of the HFR data gap-filling products . The 955 creation of partnerships between different research groups and institutions in the context of European, regional and national projects (Lorente et al., submitted to this Special Issue) is contributing to move forward both the expansion of the HFR network and the main research areas, also fostering the HFR data interoperability and distribution, helping to unlock the HFR data potential, discovery and usage.

c) Keep promoting the HFR data interoperability and distribution at the regional level: as a result of international and 960
European efforts made in recent years towards the HFR data harmonization and distribution, it has already been defined the common data and metadata model for HFR surface currents (Corgnati et al., 2018(Corgnati et al., , 2019bMantovani et al., 2020), the tools for near real-time and historical data processing (as defined in Corgnati et al., 2020 andCorgnati et al., 2019c, respectively), the guidelines (Reyes et al., 2019) and the training activities. Despite that, only 23% of the near real-time and 15% of the historical data from the Mediterranean HFR sites are integrated to the European HFR node (Lorente et al.,submitted to this 965 Special Issue), established in 2018 as a focal point for data management and distribution. In order to reduce the bottlenecks that hinder the HFR data harmonization and their provision as open data (i.e. without requiring authentication or authorization to access them), a data sharing agreement between the parties providing and receiving data should be defined and put in place.
It might also partly resolve the difficulties for sharing the HFR data held by companies or compromised to the private sector, who partially or fully funded the installations. The collaboration with international initiatives will ensure convergence and 970 interoperability. The HFR data harmonization and sharing will ultimately contribute to provide the research community with continuous and more valuable coastal data and to underpin the development of the HFR applications. d) Enhancing data discoverability, access and usability: a clear stakeholder engagement strategy will allow us to identify, categorize and analyze their needs, thus reinforcing the links and the loyalty with current users and enabling new communities and sectors to discover and use the HFR data. The EuroGOOS HFR Task Team has already taken the first steps towards the 975 definition of this strategy , building a database of current and potential stakeholders, with the input of some Mediterranean institutions. However, a stronger involvement is needed to avoid imbalances between countries and greater efforts are required to move it forward by means of programs that promote networking and coordination. Tight interactions with stakeholders on a fit-for-purpose basis and the enhancement of the societal impact of the HFR data are major elements of the strategy, especially, towards ensuring long-term sustainability. Boosting the regional involvement in this strategy will 980 result in the spreading of end-user applications at the regional/local level, stimulating also the development of new ones in response to the users' feedback. should be noted that HFRs applications are diverse being able to focus on multiple threat-and different compartment, widening their use at the coastal areas: i) to monitor eutrophication in high-productive coastal waters, combining HFR surface currents with thermistor chains, oxygen and turbidity sensors at various depth increments, and to address physical-biological interactions in coastal basins (Cianelli et al., 2017;Hernández-Carrasco et al., 2018a); ii) to monitor the transport of floating marine litter and other contaminants using surface current fields from HFRs and models (Declerck et al., 2019); iii) for ship-990 tracking (Dzvonkovskaya et al., 2007;Laws et al., 2016); iv) for early tsunami/meteo-tsunami detection (Lipa et al. 2006;Monserrat et al., 2006;Guèrin et al., 2008 ;Lipa et al. 2011Lipa et al. & 2012Gurgel et al. 2011, Dzvonkovskaya et al. 2012; v) for freshwater monitoring (Meadows et al., 2013); vi) for extracting new information from the HFR signals aiming to advance the understanding of key processes at the coastal areas, such as stratification (Shrira and Forget, 2015), air-sea interaction (Berta et al., 2018) and mixing in the upper ocean, near-surface current shear, etc; viii) for promoting the HFR use for supporting 995 marine renewable energy resource assessment (i.e. winds, currents, waves) in the coastal zone (Wyatt, 2012;Basáñez and Pérez-Nuñunzuri, 2021;Mundaca-Moraga et al., 2021), etc. Additionally, since the intensity of the multiple stressors (e.g. climate change effects, habitat loss and degradation, eutrophication, introduction of alien species, fishing practices, etc) is increasing throughout most of the Mediterranean basin, temporal analyses are progressively needed to inform effective current and future marine policies and management actions, also contributing to underpin longer-term scientific objectives. 1000 f) Extension of the HFR time series that would enable the widespread implementation of novel data science methodologies: by guaranteeing the long-term sustainability, it is expected that the HFR measurements will be expanded in the next decade, increasing the availability of multi-year surface current datasets, for the benefit of the HFR derived STPs that uses self-learning algorithms, allowing also to test the stability of SOM-solutions in time. The further development of short-term predictive systems based upon HFR surface current fields and their adaptation to the Mediterranean HFR network by incorporating non-1005 tidal component of current will enhance the STPs' integration into operational maritime safety applications, where it has been demonstrated their capacity to reduce the searching area (Roarty et al., 2010). g) Fostering the HFR data integration with other in-situ and satellite data: Exploiting the nature of their measurements, HFRs are currently being used for filling the gaps of other sparse or lower spatio-temporal resolution observations in coastal areas, as well as for improving and assessing satellite observations. In this context, it should be considered the opportunity that 1010 will offer the launch of the wide-swath Surface Water & Ocean Topography (SWOT) altimeter in 2022, which should be complemented with other remote and in-situ sensors to fully resolve the typical Mediterranean mesoscale structures of 10-100 km (Gómez-Navarro et al., 2018). Additional complementarities might be fostered with the monitoring of surface current worldwide using the information from the Automatic Identification System -AIS-data streams (Benaïchoucheet al., 2021), where HFR measurements can be used as a consistent ground-truth dataset for validation purposes and for increasing the spatial 1015 resolution of the AIS-reconstructed fields at coastal areas. The integration of HFR measurements with other multi-platform https://doi.org/10.5194/os-2021-115 Preprint. Discussion started: 14 December 2021 c Author(s) 2021. CC BY 4.0 License.
observations (e.g. ADCP as in Manso-Narvarte et al., 2020, glider data) have already been implemented and tested, particularly under the umbrella of the Jerico-Next project (see Griffa et al., 2019), for a better understanding of the three-dimensional coastal circulation, allowing the broadening of the HFR applications (i.e. below the surface). Data fusion and integration will contribute to increasing the societal and scientific value of all observations, not only HFR ones. 1020 h) Boosting the HFR data assimilation for model improvement: As shown in the Sect. 2.1.2 of the present work, HFR surface current data assimilation have demonstrated to improve the model performance in many studies (Paduan and Shulman, 2004;Barth et al., 2008;Hernández-Lasheras et al., 2021). Furthermore, the HFR standard data distribution in near real-time throughout the main European marine data portals, facilitating the data access and ensuring the timeliness, make them an ideal dataset for efficient data assimilation in operational modelling (Capet et al., 2020). However, WMOP is the only one regional 1025 operational model from the Mediterranean, which is systematically assimilating HFR data (Hernández-Lasheras et al., 2021).
As highlighted by Capet et al., (2020), the lack of expertise, training and capacity building is limiting the uptake of assimilation practices.
i) Expansion of the pool of expertise by including not only HFR technology, but data management and applications, satellite remote sensing, ocean modelling, data assimilation, training aspects, and exchanging and sharing knowledge, tools, data, 1030 know-how between diverse research groups at the European, regional and global levels. j) Training of the new generations of HFR technicians and scientists are needed to ensure the knowledge exchange, the sufficient expertise to allow for a significant expansion of the coverage and the sustainability of the operations and the HFR applications. This is currently being done in the context of periodic workshops and summer schools (such as the recent ISSOR and SICOMAR+ summer schools, etc) in the academia context. Moreover, the development of best practices for 1035 demonstrations are not only key to reach satisfactory quality standards but also for fostering the learning process. However, additional technical training courses provided by the manufacturers at the HFR operator level are recommended. Furthermore, the participation of Mediterranean institutions and companies in the creation of an international, intersectoral and interdisciplinary qualified supporting training network will contribute to boost knowledge and know-how exchanges, involving all actors (e.g. academia, operators, manufacturers, private sector, etc). 1040 k) Strengthening partnerships: (i) at the regional level, by enhancing inter-institutional collaboration, to exchange expertise, to build consortia and for sharing job opportunities in this field. In this sense, the Mediterranean HFR network is being benefited from the activities carried out in the context of EuroGOOS HFR Task Team, whose main mid-term milestones are summarized in Rubio et al., (2021), and from the ongoing regional joint projects and the existing national HFR coordination structures, as listed in Lorente et al. (submitted to this Special Issue). It is also highly recommended the participation in annual 1045 fora led by stakeholders, like the 1 st MED-FORUM that brought together the Heads of maritime services or Coast Guards of almost all Mediterranean States, aiming to develop a regional policy in the field of maritime safety and to improve the efficiency of SAR services in the Mediterranean area (Trevisanut et al., 2010); (ii) at the European level, by being aligned with ongoing initiatives and projects, contributing to the EuroGOOS HFR Task Team and the main marine data portals (e.g. Copernicus Marine Service, EMODnet, SeaDataNet), that will avoid duplication of effort; (iii) at the Global level, by collaborating with the international institutions that are world leaders in HFR and ocean observation as well as with the Global HFR network, to ensure the consistency in the data standards and best practices; (iv) with the private sector, by transferring the knowledge and the applications from the academia to the operational oceanography industry turn them into commercial services, improving the links between research and new technologies. The development of the existing and potential applications will also assist the HFR manufacturers in marketing their technologies. 1055 l) Seeking for funding is a compulsory task in order to support, together with the stakeholder's engagement and the training of the new generations, the long-term sustainability of the HFR network, their data and applications at national, regional and European levels. To this end, EuroGOOS HFR Task Team has taken early steps to prepare a competence matrix that will facilitate the building of effective, interdisciplinary, intersectoral and well-balanced consortia, grounded in shared research interests and goals, aiming to prepare competitive bids and applications for funding, taking advantage of the expertise of the 1060 team in diverse grant calls . m) Regional contribution to long-term major effort towards building a sustained and fit-for-purpose European Ocean Observing System capable to support the UN Decade of Ocean Science for Sustainable Development and the European Green Deal should be two-fold: i) On the one hand, the Mediterranean HFR network outcomes should be scientifically grounded to further ensure the extension of the science-based added-value products into societal relevant downstream services (Tintoré et 1065(Tintoré et al., 2019 and, ii) on the other hand, the Mediterranean HFR community's long-standing cooperation must be further strengthened towards a co-designed and sustained regional network, contributing to and, simultaneously, benefited by the European HFR Task Team endorsement, roadmap and main achievements (as recommended by Lorente et al., submitted to this Special Issue).

Summary and conclusions 1070
The socio-economically vital and heavily human and environmentally stressed coastal areas of the Mediterranean Sea are ones of the most exposed regions in the world due to the impact of climate change, being also highly vulnerable target regions for maritime safety, oil and marine litter pollution, fish stocks overexploitation and met-ocean hazards. The high spatio-temporal variability of the coastal dynamics requires the monitoring of these (sub)mesoscale processes at the right scale. HFRs are nowadays the only technology for remotely continuously monitoring surface currents (increasingly waves and winds) at 1075 unprecedented high spatio-temporal resolution in the coastal areas and with relatively low cost-effort, when compared with other traditional observing platforms. Their integration in ocean observing has boosted the progress in the research of smallscale features and their interaction with larger scales, also underpinning the further development of applications. In this work, we present a review of the existing advanced and emerging scientific and societal applications using HFR data, developed to address the major challenges identified in the Mediterranean coastal waters, organized around three main topics: i) maritime 1080 safety; ii) extreme hazards and iii) environmental transport processes. In addition to previous studies carried out at global and at the European scale on this topic, this work also provides a list of strengths, weaknesses, opportunities and threats of the https://doi.org/10.5194/os-2021-115 Preprint. Discussion started: 14 December 2021 c Author(s) 2021. CC BY 4.0 License. existing HFR applications in the Mediterranean Sea. Finally, we discuss the prospects for the future of the HFR applications and we provide a set of recommendations aiming to maximize the contribution in extending the science-based HFR products into societal relevant downstream services to support the blue growth in the Mediterranean coastal areas, helping to meet the 1085 UN's Decade of Ocean Science for Sustainable Development and EU's Green Deal goals.
Considering the capabilities of the existing HFR applications, it can be concluded that HFR technology and its increasingly integration in the operational ocean monitoring systems is playing a key role in the production and use of services for continuous advances in the scientific understanding of coastal ocean dynamics, technological development and in support of the sustainable blue growth in the Mediterranean Sea. However, still major efforts should be done for unlocking the HFR 1090 interoperable data access and potential as well as for the further development of HFR scientific and societal applications at the regional level, thus, delivering greater uptake, use and value. Fortunately, the opportunities provided in the framework of the UN Decade of Ocean Science for Sustainable Development and the European Green Deal can help to ensure the full exploitation of this HFR potential. In this sense, the collaboration at regional level is crucial to address region-specific processes towards a fit-for-purpose and coordinated design of the monitoring actions, to identify the environmental threats and 1095 their impacts in the environment and in the blue sectors, to easily identify the existing stakeholders, also fostering the interaction with them and to engage the potential users. This will help improve the long-term sustainability together with the training activities to the next generations and the seeking for funding. Certainly, this regionalization should always be aligned with the European strategies to ensure the integration, benefiting from the European HFR roadmap and the availability of near real-time and long-term HFR interoperable data that will boost the research and to underpin the further development of the 1100 HFR scientific and societal applications at regional level.
This manuscript constitutes the second part of a double contribution, which complements the comprehensive overview on the current status, achievements, challenges and roadmap of the HFR network in the Mediterranean, provided in the first part (Lorente et al., submitted to this Special Issue).

Author Contributions 1105
ER and PL conceived the idea of this manuscript and fostered the collaboration as MONGOOS-HFR co-chairs, being in charge of overall direction and planning. All authors contributed to the writing of the different sections of the manuscript, as follows: ER took the lead in writing the abstract, and Sect. 1, 3, 4 and 5, contributing also to Sect. PL (designed the Fig. 4), BM, JHL (designed the Fig. 5), EA, and ER wrote the Sect. 2.1.2. 1115 IHC, AO, HM (designed Fig. 6), IV, VD took the lead in writing the Sect. 2.1.3. Fig. 7), AG, LC, CM contributed to the data analysis and text drafting in Sect. 2.2.1, in particular for the case study in the Ligurian Sea. In this section, PL (designed Fig. 8) and ER addressed two cases studies in the Delta Ebro and one in the Strait of Gibraltar.

MB (designed
CAG took the lead in writing the Sect. 2.2.2, where BM, ML and MJF also contributed. 1120 AM, ACE, IHC (designed Fig.10 and Fig.11), AO contributed to the writing of the Sect. 2.3.1.

Acknowledgements
This work has been possible thanks to MONGOOS (Mediterranean Operational Network for the Global Ocean Observing 1130 System) collaborative network, aimed toward long-term synergies between multi-disciplinary working groups in the Mediterranean Sea in order to launch strategic initiatives and pursue funding for innovative research projects. This work was supported by the EuroSea (EU Horizon 2020 research and innovation programme, grant agreement ID 862626).

Competing interests
Authors MF, RG and PL are currently employed at Qualitas Instruments Lda, at HELZEL Messtechnik GmBH and at NOLOGIN Consulting SL, respectively. However, authors have not advertised commercial products and the research has not been sponsored by any one of the companies. 1195 AO and VC are guest members of the editorial board of the Special Issue from the Journal. The peer-review process was guided and overseen by another member of the editorial board.
The remaining authors declare that there are no relevant financial or non-financial competing interests to report.