dataesr/scientific-paragraphs-categorization huggingface dataset:
The results have also been aggregated at the level of each Mediterranean country, by computing the CO 2 fluxes (and their relative economic value) for their relative Exclusive Economic Zone (EEZ) areas. The SCC is a central concept for understanding and implementing climate change policies: it represents the economic cost caused by an additional ton of carbon dioxide emissions or its equivalent  (Nordhaus 2016). Since the publication of the previous valuation paper in 2015, however, the number of papers and estimates of the SCC has grown rapidly  (Tol 2018). On parallel, new CO 2 air-sea fluxes datasets have been made available from model re-analysis relative to the period 1999-2018 thus allowing to extend the valuation over a multi-year period and to make comparisons between target years and the climatology  (2004) (2005) (2006) (2007) (2008) (2009) (2010) (2011) (2012) (2013) (2014).
Addressing user needs, the IBISAR service (www. ibisar. es) provides real-time data of the ocean current forecasts available in the Iberian-Biscay-Irish regional seas and evaluates their performance. Built on an existing operational service developed by RPS Ocean Science (www. rpsgroup. com/) it consists of an automated process that helps the user to identify the most accurate ocean current prediction. The service includes three elements (as schematised in Figure  3. 4. 1): (1) the regularly updated database of current forecasts and observations; (2) the graphical user interface, acting as a single access point for serving and visualising all available data; (3) the skill assessment functionality, which evaluates the reliability of the different current forecasts. In this section, we apply and test the quantitative method used by the science-based service for assessing the skill of each data source and discuss the results obtained in two pilot areas with varying dynamical conditions.
3. 4. 5) , one of the observing platforms from the CMEMS new service release of the 16th April 2019. From all Spanish HF radar systems available in the service, those from the Ibiza Channel  (Lana et al. 2015)  and the Bay of Biscay  (Solabarrieta et al. 2014 ) are considered here. With the purpose of obtaining radar-derived Lagrangian trajectories, the generation of HF radar gap-filled products  are required  (Solabarrieta et al. 2016; Hernández-Carrasco, Orfila, et al. 2018 , Hernández-Carrasco, Solabarrieta, et al. 2018). To do this we apply the Openboundary Modal Analysis methodology, implemented by  Lekien et al. (2004)  and further optimised by  Kaplan and Lekien (2007) , using the modules of the HFR Progs Matlab package (https://github. com/rowg/hfrprogs). Since HF radar derived surface currents can also be used as an alternative of the models for backtracking drifting objects, with a demonstrated effectiveness of the HF radar short term predictions  (Zelenke 2005; Barrick et al.
This approach is gaining popularity in evaluating trajectory models for oil spill and SAR operations  (Ivichev et al. 2012; Mooers et al. 2012; Röhrs et al. 2012; Liu et al. 2014)  after being used in the context of the Deepwater Horizon oil spill  (Liu and Weisberg 2011; Mooers et al. 2012; Halliwell et al. 2014). As it is stated in  Liu and Weisberg (2011) , this methodology is particularly useful when the number of drifter trajectories is limited and neither a conventional Eulerian-based velocity nor a Lagrangian-based probability density function may be estimated. However, the current lack of drifter availability in coastal risk-prone areas restrict the robustness of the methodology and consequently it would reduce the potential of the downstream data service based on it. Addressing this drawback, the IBISAR service provides both real-time and historical evaluations according to the data availability.
For this study, the simulated trajectories of virtual particles advected by different surface velocity fields were all computed using the COSMO Lagrangian model (described by Jiménez  Madrid et al. 2016 ) from the Institute of Marine Sciences of Barcelona, which is a free software available in github repository (https:// github. com/quimbp/cosmo, version from 5 Jun 2019, DOI:10. 5281/zenodo. 3522268). It consists of a fifthorder Runge-Kutta integration scheme, bicubic spatial interpolation of the gridded velocity field and third order Lagrange polynomials in time. Although the validation of the Lagrangian model COSMO is out of the scope of this section, it was verified that the trajectories simulated by COSMO using SOCIB-WMOP currents agreed with the ones simulated with CDrift  (Sayol et al.
Furthermore, it should be considered that skill scores computed at the model domain boundaries and in areas with higher HF radar observational errors penalises the overall results. Findings highlight the need of including this type of skill assessment services to evaluate and monitor the performance of operational systems and the accuracy of its products in order to unlock their potential for different applications. Section 3. 5: Surface picture of the Levantine Basin as derived by drifter and satellite data Authors: Milena Menna, Giulio Notarstefano, Pierre-Marie  Poulain, Elena Mauri, Pierpaolo Falco, Enrico Zambianchi  Statement of main outcome: Ocean circulation derived from drifter data covers not only oceanographic and climate research but also spread and retention of pollutants. The latter field has a strong societal impact because it is able to give the measure of political action efficiency in such a delicate sector.
The geography of the Mediterranean basin and its general surface circulation scheme contribute to create a sort of re-circulation system of floating debris in which they are distributed into possibly retention and stranding areas within the basin. Recently, Lagrangian models and in-situ data have been used to estimate the drift of floating debris  (Mansui et al. 2015; Liubartseva et al. 2018 ) and the probability of debris particles to reach different areas of the Mediterranean basin  (Zambianchi et al. 2017). The results of the mentioned studies have defined the Southern Levantine basin as a sort of 'garbage patch' of the Mediterranean, where the surface currents contribute to enhance the local increase of floating litter  (Zambianchi et al. 2017). In particular, the southern coast of the Levantine seems to be a site of destination/accumulation of pollution that extent also towards Syria and the Cilician area  (Mansui et al.
Results and discussion Drifter velocities (CMEMS product  Ref. No. 3. 5. 2) , collected in the Levantine basin during the period 1993-2018 (Figure  3. 5. 1), are compared with the concurrent satellite altimetry products (Absolute Dynamic Topography -ADT, CMEMS product  Ref. No. 3. 5. 1)  in order to add new and further insights to the mean and seasonal circulation patterns of this area. More details about the drifter data processing are available in  Menna et al. (2017 Menna et al. ( , 2018)). The two datasets fit rather well (Figure  3. 5. 1(b)) and define the well-known cyclonic coastal circuit in the Levantine sub-basin  (Menna et al. 2012)  with strength as large as 15 cm/s along the southern and eastern coasts (Libyo-Egyptian Current -LEC) and larger than 25 cm/s along the northern coast (Cilician Current -CCand Asia Minor Current -AMC), in agreement with the results of  Menna et al.
2010 ). Altimetry data point out another cyclonic mesoscale structure (centred at 33. 7°N and 25. 3°E) that has never been described before in literature as a stand-alone structure, but sometimes it is included in the WCG system (e. g. Poulain et al. 2012; Pinardi et al. 2015). The occurrence of a recurrent cyclonic structure in this region is confirmed by the DYNED-Atlas database (Le  Vu et al. 2017;  https://dyned. cls. fr/seewater/#!&page=isv-mainPage), that uses the Angular Momentum Eddy Detection Algorithm in the period 2000-2017, to locate and track the surface signature of mesoscale eddies in  10-15 cm/s). The ADT values are generally higher in summer. The SCE is a permanent structure observed in both the seasons with greater intensity during summer (speeds of 18 cm/s); its shape and location are influenced by the seasonal and interannual variability of IG.
Conclusions The Mediterranean drifter dataset updated to 2018 not only provides more data but also guarantees a more complete spatial and temporal coverage in areas that were previously less sampled (like the northern part of the Levantine sub-basin). The improvement of the drifter dataset is fundamental in strengthening and supporting present and future studies on the transport of marine litter. Indeed, a more detailed and robust description of the main currents and sub-basin/mesoscale structures (eddies and gyres) has been provided in this work: the SCE has been mentioned here for the first time and the CC and AMC are now much better tracked in winter seasons. It has been recently declared that the Mediterranean is most likely one of the areas of the global ocean most strongly impacted by the presence of microplastics (see, e.
g. Suaria et al. 2016) ; within the Mare Nostrum, the Levantine sub-basin is a highly marine litter contaminated area and a deeper knowledge of the floating matter propagation is necessary to deeply understand the mechanisms of the waste dispersion. The drifter dataset will help in this context, providing a more robust description of the current field that will favour the learning mechanism of the distribution, retention and accumulation of the marine floating debris in the Mediterranean Sea and in particular in the Levantine subbasin. This implies that enhancing the Lagrangian dataset is of great importance not only for the advancement of the knowledge of the mechanisms governing the dynamical functioning of the Mediterranean, but also for the strong societal impact that a deeper awareness of local dispersion processes may provide to the assessment of marine litter distribution and to the design of possible mitigation strategies of such a critical environmental issue.
Sea ice extent, ice probability, ice mobility and start, end and length of the ice period were evaluated based on the satellite remote sensing ice concentration data for the period 1982-2019. All four sub-basins of the Baltic Sea showed similar interannual variations in these ice cover conditions explained by the large atmospheric circulation. Correlation coefficients between the length and end date of the ice period, maximum ice extent and mean NAO index were between -0. 4 and -0. 5 for all subbasins (except maximum ice extent and NAO for the Bothnian Bay). A longer ice formation period than ice melting period is inherent for all four sub-basins of the Baltic Sea. In the Bothnian Bay, the northeastern Gulf of Finland, coastal and archipelago areas, the ice processes are dominated by ice thermodynamics, while in the Bothnian Sea, the southern and central Gulf of Finland and the Gulf of Riga, by the ice dynamics.
Methods The satellite remote sensing data of ice coverage from the years of 1982-2019 is used. Copernicus product reference 4. 2. 1 provides daily sea ice concentration data derived from the Swedish Meteorological and Hydrological Institute's (and the operational product by Finnish Meteorological Institute) high resolution ice charts at a 5 km horizontal resolution for the period of 1982-2011. The near real-time observations (NRT) product reference 4. 2. 2 provides ice concentration data for the period of 2012-2019 on 1 km grid, therefore the data was resampled on the reanalysis grid. The missing data from the Copernicus NRT FTP service were requested directly from the respective Copernicus production unit. The sea ice concentration is an estimated fraction of an area which is covered by ice in the grid cell.
In this context, we will use a CMEMS level 4 reprocessed SST dataset over the period  1982-2018 (product ref. 4. 4. 1)  to quantify spatiotemporal patterns of MHWs in the Baltic Sea during summer 2018. In addition, we use the ERA5 reanalysis dataset (product ref. 4. 4. 2) , a most recent version of European global atmospheric reanalysis produced by European Centre for Medium Range Weather Forecast (ECMWF), to analyse anomalous atmospheric conditions, e. g. geopotential height, air temperature at 2 m elevation and surface heat fluxes and their potential impacts on SST.
Data analysis A database has been set up that merges satellite observations, from altimeters, radiometers, and high- resolution Synthetic Aperture Radars (SAR), with Argo float data. The 6-hour Best-Track data set further provides several parameters over the tropical cyclone life such as position, intensity and specific wind radii  (Product ref. 4. 5. 5). For each track, all available altimeter observations from the L3 CMEMS products were assembled for the different storm positions  (Figure 4. 5. 1, product ref. 4. 5. 2) , keeping only altimeter passes crossing the tropical cyclone wake afterwards. The well-defined trough left behind the tropical cyclones (blue shaded areas on the altimetry tracks in Figure  4. 5. 1) was used to directly estimate the sea surface height anomaly, i. e. the maximum difference between the bottom and the top of the altimeter sea surface height profile.
Introduction During February-March 2018 several storms including Emma, affected the maritime area in the south of Europe. In particular, Emma was characterised by an area of deep low pressure located west of the Iberian Peninsula, channelling strong southwesterly winds over the Gulf of Cadiz, and generating the highest significant wave heights recorded in the region. The impact of these huge waves in the coastal infrastructures was strengthened by less extreme, but still important, sea level and surge. In this paper, this event is studied employing data from the PORTUS system (Product refs: 4. 6. 6 and 4. 6. 7), a series of forecasting models (sea level, waves and wind) and measuring instrumentation (buoys and tide gauges integrated into Copernicus Marine Service) operated by Puertos del Estado at the Spanish Coast.
During the event, waves were especially severe there, where the deep water buoy 'Golfo de Cadiz' (WMO: 6200085), part of the PORTUS system and moored since 1996, surpassed its significant wave height record of 6. 6 m, reaching 7. 2 m during the 1st of March. In this paper, the historical information from measurements and model reanalysis from 1992 to 2018 has been analysed, confirming this event as the most severe over the past 20 years. This extreme wave value coincided with extreme high sea levels produced by the combination of spring tides (high tides reaching the 99. 95 percentile of historical high tides) and a storm surge over the 99. 5 percentile of historical surge data as measured by Puertos del Estado tide gauges network in the region. The combined effect of extreme waves and sea levels produced a huge impact at the coast causing serious damages in the harbours of the area.
Data and analysis Description of the forecasting systems and instrumentation: Two wave forecasting systems have been used in this article, the CMEMS system (product refs 4. 6. 4 and 4. 6. 5) used to compare the historical time series and the PORTUS system (product ref 4. 6. 6) used in the forecast and downstream services. Both systems employ, at the regional scale, the same numerical model WAM  (WAMDI Group 1988; Günther et al. 1992 ) but with different implementations, bathymetry and forcing. PORTUS system has, in addition, a set of models to downscale to the harbours. The local domains run SWAN model  (Booij et al. 1999 ) and provide boundary conditions to the MSP model used in Algeciras Bay Port to obtain wave agitation inside the port and a Boussinesq + VOF models  (Losada et al. 2008)  used to obtain overtopping at Tarifa Port.
It combines tide gauge data and surge forecasts, adding the tide at each harbour as the one obtained from the tide gauge data, and allowing correction of the forecasts by means of a nudging technique (by means of operational comparison with recent surge data recorded at the stations, Alvarez  Fanjul et al. 2001). Based on previous validation studies of the Nivmar storm surge forecasting system, the RMSE error of the model forecasted surge is 4. 7 cm in Huelva and 6. 1 cm in Bonanza (Pérez-Gómez 2014). These figures must be considered a qualitative assessment of the model performance at these two stations. Bias of the system is not provided, because this is computed and corrected in near-real time, as already mentioned, by the nudging technique. The instrumentation in the area is composed by a deep-water buoy and two tide gauges.
Data and analysis The HFR-TirLig High Frequency Radar (HFR) network is composed of 3 Codar SeaSonde systems (VIAR, TINO, PCOR) with antennas locations and coverage as shown    D'Alimonte and Zibordi (2003) ,  Volpe et al. (2007). The L3 dataset consists of daily mean gridded (1 km × 1 km) maps of the average Chl-a content at the sea surface. In Figure  4. 8. 1(a) we show Chl-a concentration on 20 October to provide some general information in the area of interest. A complete time series of L3 Chl-a product is not available because of extensively cloudy conditions, especially during the extreme event. One glider track is covering the Eastern Ligurian Sea in the period 19 September to 3 November 2018, with initial and final mission points within the HFR domain  (Figure 4. 8. 1a). During the event, the glider trajectory covers a segment just to the South-West of the HFR coverage (red lines in  Figure 4.
The results of validation of surface currents from the operational model against observations (Figure  4. 9. 4) are shown separately for the zonal (left panels) and meridional velocity (right panels) components. Statistics of agreement between observed and modelled data (Eulerian currents, Stokes drift and wind) are shown in each panel for the respective dataset. The conclusion is, that the model gives accurate estimates of surface currents even for these extreme wind conditions. For comparison, during regular westerly winds,  Ricker and Stanev (2020)  found similar statistics for the German Bight and  Johnson et al. (2007)  for the world ocean. However, even in deeper water Stokes drift cannot be neglected during extreme wind events. Further analyses reveal, that the model performance in terms of velocity direction is almost the same for westerly and reversed wind conditions emphasising the good model performance.
This further enabled us to reconstruct the propagation pathways during the period of strong easterlies in early 2018. The agreement between direct observations of surface currents and the CMEMS products demonstrates that the modelled data are of good quality. Furthermore, it can be concluded that the model replicates ocean dynamics well even under extreme weather conditions. The coastal ocean, here defined as the region extending from the coast to the continental shelf break, is a highly variable environment that provides direct benefits to society, being subject to continental, atmospheric and ocean forcings. In this context, CMEMS models and insitu data products, as well as other complementary datasets, have been used to characterise the impact of an extreme river discharge on the local shelf circulation.
10. (3) The Mediterranean Sea Forecast (CMEMS MED-MFC) (product reference 4. 10. 5), which included river runoff for 39 rivers from monthly mean datasets (Global Runoff Data Centre, Raicich 1996, UNEP-MAP, PERSEUS). (  4 ) The SAMOA Puertos del Estado forecast system (product reference 4. 10. 12; García  Sotillo et al. 2019; Fanjul et al. 2018)  were CMEMS downstream services, being the coastal models nested into the regional CMEMS IBI-MFC forecast solution. At the surface, models were forced by water fluxes from the Spanish Meteorological Agency (AEMET) forecast services. This system offers an increasingly higher resolution with a nested approach going down to grid sizes of 350 m near the Ebro coast. (  5  The model intercomparison (Figure  4. 10. 3a) shows that the salinity horizontal variations in the Ebro River plume identified after the extreme event in the suspended matter distribution of the satellite images  (product ref.
s100 COPERNICUS MARINE SERVICE OCEAN STATE REPORT, ISSUE 4 the Mediterranean Sea. The DYNED-Atlas database describes a cyclonic structure whose core is located between 33. 4°N and 34. 3°N and between 24. 7°E and 25. 7°E for over a third of the 17 years analysed. This mesoscale cyclone, located southwest of the IG, is defined hereafter as Southern Cretan Eddy (SCE; speeds of 5-10 cm/s). Drifter derived currents do not clearly identify the edge of the SCE (due to their non-homogenous spatial and temporal sampling) but detect the occurrence of a cyclonic meander in this region. The seasonal variability of the surface currents field was estimated dividing the dataset in two extended seasons, selected following the suggestion of Menna et al. (2012): the extended winter corresponds to January-June (Figure 3.
5. 2(a)), and the extended summer to July-December (Figure 3. 5. 2(b)). The dataset used in this work allows to add more details than the previous literature on the seasonal variability of circulation structures, especially in the easternmost part of the Levantine where, after 2010, a conspicuous amount of drifter data was collected in the framework of some international projects. The WCG, IG, MMG, and the southern limb of the RG are more dynamic in summer (Figure 3. 5. 2 (b); speeds up to 30 cm/s), as well as the CC, AMC and the LTE (speeds larger than 20 cm/s). The CG is more intense in winter (Figure 3. 5. 2(b); speeds of 10-15 cm/s), whereas it appears weaker and zonally elongated during summer (Figure 3. 5. 2(b); speeds of.
3), which provided 10 days of 3D global ocean forecasts daily updated and used coastal runoffs from 100 major rivers from the Dai et al. 2009 database. (2) The Iberian-Biscay-Ireland Monitoring and Forecast Center (CMEMS IBI-MFC) (product reference 4. 10. 4), which produced near-real-time with river discharge inputs daily updated, including discharge for 33 rivers. Combination of daily observations from PREVIMER (Ebro River runoff not included),.
) The Western Mediterranean sea OPerational model,(WMOP, product ref. 4. 10. 9) is a SOCIB (Balearic Islands Coastal Observing and Forecasting System) added value product(Juza et al. 2016; Mourre et al. 2018) that uses the CMEMS Mediterranean Sea Analysis and Forecast products (product ref. 4. 10. 5)as parent model (initial and boundary conditions). The operational version includes daily climatological values over 2009-2016 for 6 rivers from the French HYDRO database and the Spanish hydrographic confederations of Ebro and Júcar river. Particularly, for this study, river forcing using the daily observed runoff of the Ebro River has been considered.
Acknowledgements The development of the presented downstream service is supported by  Mercator Ocean International  throughout the  CMEMS-User Uptake IBISAR  project (CMEMS User Uptake, contract ref. 67-UU-DO-CMEMS-DEM4_LOT7 ). Authors wish to thank  Copernicus Marine Service  for making model and in-situ data products available, the  Spanish Port System (PUERTOS)  for the datasets of SAMOA, SASEMAR for providing the data of the drifter buoys of the  Bay of Biscay  and their feedback on the service, EUSKOOS and the  Directorate of Emergency Attention and Meteorology of the Basque Government  for the HF radar surface current datasets of the  Bay of Biscay  and SOCIB for HF radar data in the Ibiza Channel and the WMOP forecasts. The Lagrangian models developed in the context of the  COSMO  project (ref.