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We propose a new deep-learning architecture HIDRA2 for sea level and storm tide modeling, which is extremely fast to train and apply and outperforms both our previous network design HIDRA1 and two state-of-the-art numerical ocean models (a NEMO engine with sea level data assimilation and a SCHISM ocean modeling system), over all sea level bins and all forecast lead times. The architecture of HIDRA2 employs novel atmospheric, tidal and sea surface height (SSH) feature encoders as well as a novel feature fusion and SSH regression block. HIDRA2 was trained on surface wind and pressure fields from a single member of the European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric ensemble and on Koper tide gauge observations. An extensive ablation study was performed to estimate the individual importance of input encoders and data streams. Compared to HIDRA1, the overall mean absolute forecast error is reduced by 13 %, while in storm events it is lower by an even larger margin of 25 %. Consistent superior performance over HIDRA1 as well as over general circulation models is observed in both tails of the sea level distribution: low tail forecasting is relevant for marine traffic scheduling to ports of the northern Adriatic, while high tail accuracy helps coastal flood response. Power spectrum analysis indicates that HIDRA2 most accurately represents the energy density peak centered on the ground state sea surface eigenmode (seiche) and comes a close second to SCHISM in the energy band of the first excited eigenmode. To assign model errors to specific frequency bands covering diurnal and semi-diurnal tides and the two lowest basin seiches, spectral decomposition of sea levels during several historic storms is performed. HIDRA2 accurately predicts amplitudes and temporal phases of the Adriatic basin seiches, which is an important forecasting benefit due to the high sensitivity of the Adriatic storm tide level to the temporal lag between peak tide and peak seiche.

On 7 April 2021, an exceptional bloom of the scyphomedusa Rhizostoma pulmo was observed in the Gulf of Trieste (Italy). Blooms of this species in the northern Adriatic Sea have been reported since the late 1800s: the density of jellyfish observed in 2021 reached more than 10 specimens per square metre. We analyse the bloom from a multi-platform approach using observations and model data at different timescales. We attempt to explain the intensity of the bloom as a consequence of thermohaline and hydrodynamical conditions in the gulf. Meteo-oceanographic conditions that may have contributed to the exceptional aggregation of jellyfish observed along the northernmost coast of the Adriatic Sea are discussed in detail. Specifically, our results indicate that this bloom was enabled by (1) the presence of a high number of jellyfish in the gulf, probably linked to the anomalously warm sea conditions in spring 2020 and winter 2021, which may have favoured a longer reproductive period and enhanced survival of adult R. pulmo, respectively; and (2) strong wind events, such as the bora wind for the Gulf of Trieste, which enhanced upwelling and mixing processes in the gulf, bringing the jellyfish from the deeper waters to the surface and clustering them along the coast.

We propose a new deep-learning architecture HIDRA2 for sea level and storm surge modeling, which is extremely fast to train and apply, and outperforms both our previous network design HIDRA1 and the state-of-the-art numerical ocean model (a NEMO engine with sea level data assimilation), over all sea level bins and all forecast lead times. The architecture of HIDRA2 employs novel atmospheric, tidal and SSH feature encoders, as well as a novel feature fusion and SSH regression block. HIDRA2 was trained on surface wind and pressure fields from a single member of ECMWF atmospheric ensemble and on Koper tide gauge observations during years 2006–2018, and evaluated on the data from June 2019 to December 2020. Compared to HIDRA1, the overall mean absolute forecast error is reduced by 13.9 %, while on storm surge events it is lower by even a larger margin of 25.1 %. Consistent superior performance over HIDRA1 as well as NEMO is observed in both tails of the sea level distribution. Power spectrum analysis indicates that HIDRA2 most accurately represents the energy density peaks centered on the two lowest Adriatic wind-induced free oscillation eigenmodes (seiches) among all tested models. To assign model errors to specific frequency bands covering diurnal and semi-diurnal tides and the lowest two basin seiches, sea level band-pass filtering of several historic storm surge events is applied. HIDRA2 performs well across all frequency bands and most accurately predicts amplitudes and temporal phases of the Adriatic basin seiches. This is shown to be an important forecasting benefit due to the high sensitivity of total Adriatic storm surge sea level to the phase lag between peak tide and peak seiche.

On 29 October 2018 a windsurfer's mast broke about 1 km offshore from Istria during a severe scirocco storm in the northern Adriatic Sea. He drifted in severe marine conditions until he eventually beached alive and well in Sistiana (Italy) 24 h later. We conducted an interview with the survivor to reconstruct his trajectory and to gain insight into his swimming and paddling strategy. Part of survivor's trajectory was verified using high-frequency radar surface current observations as inputs for Lagrangian temporal back-propagation from the beaching site. Back-propagation simulations were found to be largely consistent with the survivor's reconstruction. We then attempted a Lagrangian forward-propagation simulation of his trajectory by performing a leeway simulation using the OpenDrift tracking code using two object types: (i) person in water in unknown state and (ii) person with a surfboard. In both cases a high-resolution (1 km) setup of the NEMO v3.6 circulation model was employed for the surface current component, and a 4.4 km operational setup of the ALADIN atmospheric model was used for wind forcing. The best performance is obtained using the person-with-a-surfboard object type, giving the highest percentage of particles stranded within 5 km of the beaching site. Accumulation of particles stranded within 5 km of the beaching site saturates 6 h after the actual beaching time for all drifting-particle types. This time lag most likely occurs due to poor NEMO model representation of surface currents, especially in the final hours of the drift. A control run of wind-only forcing shows the poorest performance of all simulations. This indicates the importance of topographically constrained ocean currents in semi-enclosed basins even in seemingly wind-dominated situations for determining the trajectory of a person lost at sea.

Mediterranean marine heatwaves (MHW), defined as prolonged periods of anomalously warm sea temperatures, have been occurring more frequently and with higher intensity in recent years resulting in a degradation of the status of marine ecosystems. This work, which is part of the Interreg-Med project SHAREMED, aims to spatially assess MHW pressures and impacts on the coralligenous of the North Adriatic Sea. Coralligenous refers to complex biogenic structures made by the outgrowth of encrusting calcareous algae on hard substrata in the mesophotic zone and by several invertebrates, mostly Cnidaria, Polychaeta, Porifera and Bryozoa (Ballesteros et al., 20061). The responses of the coralligenous assemblages to MHW ranges from bleaching, tissue necrosis and mortality events (Kruzic et al., 20142, Cerrano et al., 20003). Data on the distribution of the species and on their responses to temperature anomalous events were obtained by literature review, and database analysis (EMODnet, Reef Check database, Obis). MHW analysis followed the Hobday et al. (20164, 20185) methodology using both satellite data (CMEMS-Multidecadal L4-gridded satellite SST measurements from 1989 till present) and numerical modelling output (CMEMS-Mediterranean Sea Physics Reanalysis; 1987-2019).First, the exposure maps were created in order to identify the overlap between MHW occurrences (in terms of duration, frequency and intensity) and the coralligenous outcrops. The MHW index maps were analysed in comparison to the historical data of mass mortality events reported in the literature (Di Camillo et al., 20126; Sini et al., 20157; Kruzic et al., 20168) to test the occurrence of MHW impacts. A vulnerability index for coralligenous to MHW was developed, taking into account site-specific features such as indexes of diversity, richness and connectivity (Falace et al., 20159; Bandelj et al., 202010), and then used to evaluate the degree of impact on coralligenous formations by MHW following the methodology by Halpern et al., 200811. References:1doi:10.1201/9781420006391-7; 2doi:10.3354/meps10962; 3doi:10.1046/j.1461-0248.2000.00152.x; 4doi:10.1016/j.pocean.2015.12.014; 5doi:10.5670/oceanog.2018.205; 6doi:10.1007/s10750-011-0877-z; 7doi:10.1371/journal.pone.0126253; 8doi:10.1111/maec.12293; 9doi:10.1371/journal.pone.0140931; 10doi:10.1016/J.ECSS.2020.106978; 11doi:10.1126/science.1149345

We present a numerically cheap machine-learning model which accurately emulates the performances of the surface wave model Simulating WAves Near Shore (SWAN) in the Adriatic basin (north-east Mediterranean Sea).A ResNet50 inspired deep network architecture with customized spatio-temporal attention layers was used, the network being trained on a 1970-1997 dataset of time-dependent features based on wind fields retrieved from the COSMO-CLM regional climate model (The authors acknowledge Dr. Edoardo Bucchignani (Meteorology Laboratory, Centro Italiano Ricerche Aerospaziali -CIRA-, Capua, Italy), for providing the COSMO-CLM wind fields). SWAN surface wave model outputs for the period of 1970-1997 are used as labels. The period 1998-2000 is used to cross-validate that the network very accurately reproduces SWAN surface wave features (i.e. significant wave height, mean wave period, mean wave direction) at several locations in the Adriatic basin. After successful cross validation, a series of projections of ocean surface wave properties based on climate model projections for the end of 21st century (under RCP 8.5 scenario) are performed, and shifts in the emulated wave field properties are discussed.

The Mediterranean Sea is a prominent climate-change hot spot, with many socioeconomically vital coastal areas being 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 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 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-user and science-driven requirements, addressing regional challenges in three main topics: (i) maritime safety, (ii) extreme hazards and (iii) environmental transport process. Additionally, the HFR observing and monitoring regional capabilities in the Mediterranean coastal areas required to underpin the underlying science and the further development of applications are also analyzed. The outcome of this assessment has allowed us to provide a set of recommendations for future improvement prospects to maximize the contribution to extending science-based HFR products into societally relevant downstream services to support 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., peer-reviewed

Special issue “Advances in interdisciplinary studies at multiple scales in the Mediterranean Sea”. It is a result of the 8th MONGOOS Meeting & Workshop, Trieste, Italy, 3–5 December 2019.-- 57 pages, 9 figures, 1 table, 1 appendix, supplement https://doi.org/10.5194/os-18-997-2022-supplement.-- Data availability: Access to sea level data presented in this review is provided through national and international data portals and repositories quoted in Sects. 2 and 3 and in the Supplement, Employed for over a century, the traditional way of monitoring sea level variability by tide gauges – in combination with modern observational techniques like satellite altimetry – is an inevitable ingredient in sea level studies over the climate scales and in coastal seas. The development of the instrumentation, remote data acquisition, processing, and archiving in the last decades has allowed the extension of the applications to a variety of users and coastal hazard managers. The Mediterranean and Black seas are examples of such a transition – while having a long tradition of sea level observations with several records spanning over a century, the number of modern tide gauge stations is growing rapidly, with data available both in real time and as a research product at different time resolutions. As no comprehensive survey of the tide gauge networks has been carried out recently in these basins, the aim of this paper is to map the existing coastal sea level monitoring infrastructures and the respective data availability. The survey encompasses a description of major monitoring networks in the Mediterranean and Black seas and their characteristics, including the type of sea level sensors, measuring resolutions, data availability, and existence of ancillary measurements, altogether collecting information about 240 presently operational tide gauge stations. The availability of the Mediterranean and Black seas sea level data in the global and European sea level repositories has been also screened and classified following their sampling interval and level of quality check, pointing to the necessity of harmonization of the data available with different metadata and series in different repositories. Finally, an assessment of the networks' capabilities for their use in different sea level applications has been done, with recommendations that might mitigate the bottlenecks and ensure further development of the networks in a coordinated way, a critical need in the era of human-induced climate changes and sea level rise, This research has been partially supported by Horizon 2020 (EuroSea (grant no. 862626) and JERICO-S3 (grant no. 871153)), With the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S)

Due to the semi-enclosed nature of the Mediterranean Sea, natural disasters and anthropogenic activities impose stronger pressures on its coastal ecosystems than in any other sea of the world. With the aim of responding adequately to science priorities and societal challenges, littoral waters must be effectively monitored with high-frequency radar (HFR) systems. This land-based remote sensing technology can provide, in near-real time, fine-resolution maps of the surface circulation over broad coastal areas, along with reliable directional wave and wind information. The main goal of this work is to showcase the current status of the Mediterranean HFR network and the future roadmap for orchestrated actions. Ongoing collaborative efforts and recent progress of this regional alliance are not only described but also connected with other European initiatives and global frameworks, highlighting the advantages of this cost-effective instrument for the multi-parameter monitoring of the sea state. Coordinated endeavors between HFR operators from different multi-disciplinary institutions are mandatory to reach a mature stage at both national and regional levels, striving to do the following: (i) harmonize deployment and maintenance practices; (ii) standardize data, metadata, and quality control procedures; (iii) centralize data management, visualization, and access platforms; and (iv) develop practical applications of societal benefit that can be used for strategic planning and informed decision-making in the Mediterranean marine environment. Such fit-for-purpose applications can serve for search and rescue operations, safe vessel navigation, tracking of marine pollutants, the monitoring of extreme events, the investigation of transport processes, and the connectivity between offshore waters and coastal ecosystems. Finally, future prospects within the Mediterranean framework are discussed along with a wealth of socioeconomic, technical, and scientific challenges to be faced during the implementation of this integrated HFR regional network., This study has been partially developed in the framework of the Interreg MED Strategic Project SHAREMED, co-financed by the European Regional Development Fund under the funding program Interreg MED 2014–2020. Website: https://sharemed.interreg-med.eu/ (last access: 31 March 2022). We are also grateful for the partial support of the (i) the project PO FEAMP 2014/2020 (Misura 2.51) funded by Regione Campania (Italy), (ii) the 2017 PRIN project EMME (Exploring the fate of Mediterranean microplastic: from distribution pathways to biological effects) funded by the Italian Ministry for Research (grant agreement no. 2017WERYZP), and (iii) the CMEMS-INSTAC phase II, which provides the context of the activities for HFR data harmonization, standardization, and distribution. Collaborative discussion on data management harmonization at the European level has also been carried out thanks to the contribution of the projects INCREASE (CMEMS Service Evolution Call for Tenders 21-SE-CALL1) and SeaDataCloud (EU-H2020 GA no. 730960).

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.

Implementing adequate defences for low-lying coastal area against coastal flooding requires thorough knowledge of all potential influences leading to increased sea levels, including low-frequency sea level oscillations. We present and describe several methods applicable for the analysis of low-frequency sea level oscillations in the Mediterranean Sea: wavelet analysis, spectral analysis, moving-periodogram analysis, and rotary spectral analysis. These methods were applied for characterisation of subinertial sea level oscillations with periods greater of the period of inertial oscillation (18 hours in the Northern Adriatic Sea) on measured sea surface elevations and current velocities in the Mediterranean Sea. Preliminary analysis was performed on observations of a storm event in the Adriatic Sea at the end of January and the beginning of February 2014, revealing a peak in the frequency spectrum in the frequency band between 0.3−0.4 day−1. Further analysis was done on long-term tide gauge measurements available for 62 stations in the Mediterranean basin. The application of the selected methods provided a preliminary set of seasonal occurrences and durations of subinertial oscillation. This sets the ground for further investigation into the propagation of low-frequency sea level oscillations throughout the Mediterranean basin and for characterisation of the mechanisms triggering the process, including with regard to climate change.

Interactions between atmospheric forcing, topographic constraints to air and water flow, and resonant character of the basin make sea level modeling in Adriatic a challenging problem. In this study we present an ensemble deep-neural-network-based sea level forecasting method HIDRA, which outperforms our setup of the general ocean circulation model ensemble (NEMO v3.6) for all forecast lead times and at a minuscule fraction of the numerical cost (order of 2 × 10-6). HIDRA exhibits larger bias but lower RMSE than our setup of NEMO over most of the residual sea level bins. It introduces a trainable atmospheric spatial encoder and employs fusion of atmospheric and sea level features into a self-contained network which enables discriminative feature learning. HIDRA architecture building blocks are experimentally analyzed in detail and compared to alternative approaches. Results show the importance of sea level input for forecast lead times below 24 h and the importance of atmospheric input for longer lead times. The best performance is achieved by considering the input as the total sea level, split into disjoint sets of tidal and residual signals. This enables HIDRA to optimize the prediction fidelity with respect to atmospheric forcing while compensating for the errors in the tidal model. HIDRA is trained and analysed on a ten-year (2006-2016) timeseries of atmospheric surface fields from a single member of ECMWF atmospheric ensemble. In the testing phase, both HIDRA and NEMO ensemble systems are forced by the ECMWF atmospheric ensemble. Their performance is evaluated on a one-year (2019) hourly time series from tide gauge in Koper (Slovenia). Spectral and continuous wavelet analysis of the forecasts at the semi-diurnal frequency (12 h)-1 and at the ground-state basin seiche frequency (21.5 h)-1 is performed. The energy at the basin seiche in the HIDRA forecast is close to the observed, while our setup of NEMO underestimates it. Analyses of the January 2015 and November 2019 storm surges indicate that HIDRA has learned to mimic the timing and amplitude of basin seiches.

This study investigates the potential of ensemble forecasting using full realistic high-reso-lution nested atmosphere–ocean models for the prediction of meteotsunamis in Ciutadella (Menorca, Spain). The sensitivity of model results to the parameterizations of the atmos-pheric model is assessed considering the ten most significant recent meteotsunami events for which observations are available. Different schemes adapted to high-resolution Weather Research and Forecasting model simulations were used for the representation of cumulus, microphysics, planetary boundary layer and longwave and shortwave radiations. Results indicate a large spread of the ensemble simulations in terms of the final magnitude of the meteotsunamis. While the modeling system is shown to be able to realistically trigger tsu-namigenic atmospheric disturbances in more than 90% of the situations, the small-scale characteristics of these disturbances are significantly modified with the change of param-eterizations, leading to significant differences in the magnitude of the simulated sea-level response. No preferred set of parameterizations can be identified that leads to either the largest or the most realistic magnitudes in the majority of situations. Instead, the perfor-mance of a given set of parameterizations is found to change with the meteotsunami event under consideration. Importantly, the observed magnitude of the extreme sea-level oscilla-tions lies within the range of a nine-member ensemble in 70% of the cases. This ensemble approach would then allow to generate a realistic range of possibilities in the majority of events, thus improving the realism of meteotsunami predictions compared to single deter-ministic forecasts.

Interactions between atmospheric forcing, topographic constraints to air and water flow, and resonant character of the basin make sea level modelling in the Adriatic a challenging problem. In this study we present an ensemble deep-neural-network-based sea level forecasting method HIDRA, which outperforms our set-up of the general ocean circulation model ensemble (NEMO v3.6) for all forecast lead times and at a minuscule fraction of the numerical cost (order of 2×10-6). HIDRA exhibits larger bias but lower RMSE than our set-up of NEMO over most of the residual sea level bins. It introduces a trainable atmospheric spatial encoder and employs fusion of atmospheric and sea level features into a self-contained network which enables discriminative feature learning. HIDRA architecture building blocks are experimentally analysed in detail and compared to alternative approaches. Results show the importance of sea level input for forecast lead times below 24 h and the importance of atmospheric input for longer lead times. The best performance is achieved by considering the input as the total sea level, split into disjoint sets of tidal and residual signals. This enables HIDRA to optimize the prediction fidelity with respect to atmospheric forcing while compensating for the errors in the tidal model. HIDRA is trained and analysed on a 10-year (2006–2016) time series of atmospheric surface fields from a single member of ECMWF atmospheric ensemble. In the testing phase, both HIDRA and NEMO ensemble systems are forced by the ECMWF atmospheric ensemble. Their performance is evaluated on a 1-year (2019) hourly time series from a tide gauge in Koper (Slovenia). Spectral and continuous wavelet analysis of the forecasts at the semi-diurnal frequency (12 h)−1 and at the ground-state basin seiche frequency (21.5 h)−1 is performed. The energy at the basin seiche in the HIDRA forecast is close to that observed, while our set-up of NEMO underestimates it. Analyses of the January 2015 and November 2019 storm surges indicate that HIDRA has learned to mimic the timing and amplitude of basin seiches.

On 29 October 2018 a windsurfer's mast broke about 1 km offshore during a severe Scirocco storm in the Northern Adriatic Sea. He was drifting in severe marine conditions until he eventually beached alive and well in Sistiana (Italy) 24 hours later. We conducted an interview with the survivor to reconstruct his trajectory and to gain insight into his swimming and paddling strategy. We then attempted a Lagrangian simulation of his trajectory in two ways. Firstly by performing a leeway simulation using the OpenDrift tracking code using two object types: Person-in-Water-1 and Person-powered-vessel-2. Secondly, we model the trajectory using our own Lagrangian tracking code FlowTrack. In both cases a high-resolution (1 km) setup of NEMO v3.6 circulation model was employed for the surface current component and a 4.4 km operational setup of the ALADIN atmospheric model was used for wind forcing. OpenDrift yields best results using Person-powered-vessel-2 object type, indicating a relatively broad search and rescue area which covers 45 km2 after six hours and rises to 380 km2 after 24 hours. The simulated most probable SAR area envelops the reconstructed drift trajectory and is also temporaly consistent with the reconstruction. FlowTrack yields a search and rescue area with a comparable lateral extent but with much less downwind spread. While both Lagrangian models were able to envelop the reconstructed drift trajectory during this validation, we recommend using OpenDrift for similar search-and-rescue missions in the future due to its flexibility and drifting object dependent calibration on empirical data.

We use a high resolution nested ocean modelling system forced by synthetic atmospheric gravity waves to investigate Balearic meteotsunami generation, amplification and propagation properties. We determine how meteotsunami amplitude outside and inside of the Balearic port of Ciutadella depends on forcing gravity wave direction, speed and trajectory. We quantify the contributions of Mallorca shelves and Menorca Channel for different gravity wave forcing angles and speeds. The Channel is demonstrated to be the key build-up region determining meteotsunami amplitude in Ciutadella while northern and southern Mallorca shelves serve mostly as barotropic wave guides but do not significantly contribute to seiche amplitude in Ciutadella. This fact seriously reduces early-warning alert times in cases of locally generated pressure perturbations. We track meteotsunami propagation paths in the Menorca Channel for several forcing velocities and show that the Channel bathymetry serves as a focusing lens for meteotsunami waves whose paths are constrained by the forcing direction. We show that faster meteotsunamis propagate over deeper ocean regions, as required by Proudman resonance. We estimate meteotsunami speed under sub- and supercritical forcing and derive a first order estimate of its magnitude. We show that meteotsunamis, generated by supercritical gravity waves, propagate with a velocity which is equal to an arithmetic mean of the forcing velocity and local barotropic ocean wave speed.

We have studied the performances of (a) a two-way coupled atmosphere–ocean modeling system and (b) one-way coupled ocean model (forced by the atmosphere model), as compared to the available in situ measurements during and after a strong Adriatic bora wind event in February 2012, which led to extreme air–sea interactions. The simulations span the period between January and March 2012. The models used were ALADIN (Aire Limitée Adaptation dynamique Développement InterNational) (4.4 km resolution) on the atmosphere side and an Adriatic setup of Princeton ocean model (POM) (1°∕30 × 1°∕30 angular resolution) on the ocean side. The atmosphere–ocean coupling was implemented using the OASIS3-MCT model coupling toolkit. Two-way coupling ocean feedback to the atmosphere is limited to sea surface temperature. We have compared modeled atmosphere–ocean fluxes and sea temperatures from both setups to platform and CTD (conductivity, temperature, and depth) measurements from three locations in the northern Adriatic. We present objective verification of 2 m atmosphere temperature forecasts using mean bias and standard deviation of errors scores from 23 meteorological stations in the eastern part of Italy. We show that turbulent fluxes from both setups differ up to 20 % during the bora but not significantly before and after the event. When compared to observations, two-way coupling ocean temperatures exhibit a 4 times lower root mean square error (RMSE) than those from one-way coupled system. Two-way coupling improves sensible heat fluxes at all stations but does not improve latent heat loss. The spatial average of the two-way coupled atmosphere component is up to 0.3 °C colder than the one-way coupled setup, which is an improvement for prognostic lead times up to 20 h. Daily spatial average of the standard deviation of air temperature errors shows 0.15 °C improvement in the case of coupled system compared to the uncoupled. Coupled and uncoupled circulations in the northern Adriatic are predominantly wind-driven and show no significant mesoscale differences.

A new mercury (Hg) evasion model for the Adriatic Sea was developed accounting for the ocean mixed layer depth in order to decrease Hg depletion at the surface. Previously modelled airborne Hg species and measured Hg in the ocean were used. Simulations were run using one- and two-way coupled atmosphere-ocean models. Discrepancies in evasion between the applied coupling schemes were shown to be insignificant. The model was evaluated by applying various wind parameterisations and diffusive coefficient formulae. Relatively high discrepancies among the applied methods were observed. The results of a shorter simulation were extrapolated over a one-year period by applying a measurement-based adaptation. We obtained good agreement with previously published data on Hg evasion in the entire Mediterranean area, thus confirming the suitability of the new model for Hg evasion simulations. Model computations performed for the Adriatic Sea resulted in levels of evasion approximately two times lower than previously estimated.

[1] High resolution high frequency (HF) radar observations of surface currents in the Gulf of Trieste (GoT) are presented and compared to moored subsurface current measurements and to high-resolution simulations from the Northern Adriatic Princeton Ocean Model (NAPOM) oceanographic model. Dominant circulation modes of the GoT were resolved and numerical model capabilities in reconstructing them were assessed. The time frame covers March 2011 through October 2012. NAPOM reconstructs the dominant surface circulation features observed by the radar, such as the general basin-wide cyclonic circulation scheme and the coastal jet outflowing the GoT, but is in general less energetic than radar currents. Comparisons between radar, ADCP, and model currents suggest that the model underestimates originate within the low-frequency, diurnal, semidiurnal, and inertial bands, and that both radar and model currents do not reproduce the diurnal tidal ellipse structure observed by the moored current meter. However, radar-model results for the semidiurnal tides are spatially consistent. Using empirical orthogonal function (EOF) decomposition, the coherent spatial scales and corresponding temporal scales were extracted. Findings suggest that HF radar current observations complement model simulations in regions of enhanced topographic variability where variance of model currents at the surface is distorted by the effects of the sigma layer grid. On the contrary, model results complement radar observations in areas with poor radar coverage, and furthermore provide spatial and temporal continuity of ocean state forecasts.

We study the performances of (a) fully two-way coupled atmosphere–ocean modeling system and (b) one-way coupled ocean model (forced by the atmospheric model hourly output), as compared to the available in situ (mooring and CTD) measurements during and after an strong Bora wind event in February 2012, which led to extreme air–sea interactions and record breaking seawater cooling and dense water formation in Northern Adriatic. The simulations span the period between January and March 2012. The models used were ALADIN (4.4 km resolution) on the atmospheric side and Adriatic setup of POM (1°/30 × 1°/30 angular resolution) on the ocean side. The atmosphere–ocean coupling was implemented using the OASIS3-MCT model coupling toolkit. We show, using in situ seawater temperature measurements, that the two-way atmosphere–ocean coupling improves the ocean response to Bora because it captures transient Bora-induced cooling better than the one-way coupled version of the ocean model. We show that this difference stems mainly from an underestimation of air–sea temperature difference in one-way coupled system during the Bora episode, leading to an underestimation of sensible heat losses from the ocean in the one-way coupled system. We show these losses exhibit significant impact on baroclinic circulation on synoptic timescales. We use CTD observations in the Gulf of Trieste to show that when compared to the one-way setup, the two-way coupled system produces a similar estimation of salinities and density anomalies before the Bora episode, but a significantly better estimation of these quantities afterwards.

The recent developments in pollutant measurement methods and techniques necessitate improvements in modelling approaches. The models used so far have been based on seasonally averaged data, which is insufficient for making short-term predictions. We have improved the existing modelling tools for pollutant transport and dispersion on three levels. We significantly refined the numerical grid; we used temporally and spatially non-uniform meteorological parameters for predicting pollutant dispersion and transformation processes; we used grid nesting in order to improve the open boundary condition. We worked on a typical contaminated site (The Gulf of Trieste), where mercury poses a significant environmental threat and where an oil-spill is a realistic possibility. By calculating evasion we improved the mass balance of mercury in the Gulf. We demonstrated that the spreading of river plumes under typical wind conditions is different than has so far been indicated by model simulations. We also simulated an oil-spill in real time. The improved modelling approaches and the upgraded models are now suitable for use with the state-of-the-art measurements technology and can represent an important contribution to the decision-making process.

We present a mean-field theory for charged polymer chains in an external electrostatic field in the weak and strong coupling limits. We apply the theory to describe the statistical mechanics of flexible polyelectrolyte chains in a hexagonal columnar lattice of stiff cylindrical macroions, such as DNA, in a bathing solution of a uni-univalent salt (e.g. NaCl). The salt effects are first described in the Debye-Huckel framework. This yields the macroion electrostatic field in the screened Coulomb form, which we take to represent the mean field into which the chains are immersed. We introduce the Green's function for the polyelectrolyte chains and derive the corresponding Edwards equation which we solve numerically in the Wigner-Seitz cylindrical cell using the ground state dominance ansatz. The solutions indicate the presence of polyelectrolyte bridging, which results in a like-charge attraction between stiff macroions. Then we reformulate the Edwards theory for the strong coupling case and use the standard Poisson-Boltzmann picture to describe the salt solution. We begin with the free energy which we minimize to obtain the Euler-Lagrange equations. The solutions yield self-consistently determined monomer density and electrostatic fields. We furthermore calculate the free energy density as well as the total osmotic pressure in the system. We again show that bridging implicates like-charge attractions of entropic origin between stiff cylindrical macroions. By analyzing the osmotic pressure we demonstrate that, in certain parts of the parameter space, a phase transition occurs between two phases of the same hexagonal symmetry.