dataesr/scientific-paragraphs-categorization huggingface dataset:
Europe, Africa and Middle East (Region 1) In Europe (EU), the use of HFR systems is growing with over 62 HFR sites currently operating and a number in the planning stage. A survey to catalog the status of different HFR systems available in the Europe was launched in June 2016 and has been maintained up to date  (Mader et al. , 2016). The survey gathered responses from 28 European institutions and information on more than 70 HFR systems. From 2004 until 2009 a moderate growth rate of two new HFRs per year was observed and, since 2009, it has increased to around six new HFRs installed per year and up to seven, since 2016 (Figure  5B ). The most popular identified user of the EU HFR data was academia, followed by European or national maritime safety agencies and weather services  (Rubio et al.
The European coordination of HFR systems started with the EuroGOOS HFR Task Team (TT) in 2014, which increased the global visibility of the European HFR systems and enabled a joint integration  In 2018, the HFR EU data node was created as a centralized European competence center to ensure the implementation of the HFR data stream (harvesting, harmonization, formatting, and distribution) from the data providers toward the different EU marine data portals and global data infrastructures. A plan for the inclusion of HFR data into the Copernicus Marine Environment Monitoring Service (CMEMS) through this EU data node is in progress. First steps toward this integration were carried out under the CMEMS INCREASE Project  (Rubio et al. , 2018b). A survey of the CMEMS community by the INCREASE project highlighted the interest shown in having access to HFR current data at a global level and to operational data derived from the advanced processing of the HFR backscatter signals, such as waves and maps of wind direction, which opens future working lines.
The CMEMS In Situ Thematic Centre (CMEMS-INSTAC), will start delivery of near-real time (NRT) total and radial HFR data from certain sites in April 2019 and April 2020, respectively. The data distribution will be made both at a global and regional level, aiming to foster the relationship between users, providers, and the INSTAC regional components inside the regional alliances of EuroGOOS (ROOSes). Other European HFR operators will be supported in their preparation of their involvement, in order to achieve the final goal of distributing all European HFR data within CMEMS-INSTAC, SeaDataCloud and EMODnet platforms. Inside CMEMS-INSTAC the HFR data set is considered part of a global product of ocean surface currents, and will be delivered jointly with the global surface drifter data set. The CMEMS structure is thus ready to embrace a global dimension for the HFR data.
Work is underway to prepare for the inclusion of United States HFR data from the United States IOOS National HFR Node into the CMEMS-INSTAC Global Distribution Unit, planned for April 2020. This preparation phase is being developed with the MARACOOS (IOOS regional association in the Mid-Atlantic) network and is mainly focused on treating the dataflow and the few discrepancies between United States and European standard data models. In parallel, the EU Project JERICO-NEXT is working to provide procedures and methodologies to enable HFR data to comply with the international standards regarding their quality and metadata, within the overall goal of integrating the European coastal observatories  (Corgnati et al. , 2018b). The ongoing MyCoast project aims to build a coordinated coastal operational observatory in the Atlantic Ocean by improving the synergies between observational and forecasting systems.
Morocco The National Meteorological Directorate of Morocco (DMN) operates a network of two 5 MHz long-range HFRs  (Bouksim et al. , 2016 ) located in the Port of Casablanca and in Temara with a measurement range of approximately 200 km offshore, covering an area of around 17,000 km 2 between Casablanca and Rabat. This network was commissioned in April 2016 and represents the first permanent HFR network deployed in Africa. DMN is initially applying HFR surface currents and wave data to validate their operational marine forecast models and to improve their knowledge of the hydrodynamics in this part of the Moroccan coast. In future work, data will also be used for SAR operations, safety in navigation and for better preparedness and response against marine pollution incidents in collaboration with the Royal Moroccan Navy, National Ports Agency and Civil Protection Authority.
Portugal The Portuguese Hydrographic Institute (IH), the main operational oceanography institution in Portugal, operates a network of five CODAR HFRs  (Fernandes, 2014). The network consists of two 13 MHz HFRs deployed in 2010 deployed in São Julião and Espichel close to Lisbon and three 13 MHz CODAR HFRs installed along the coast of the Algarve in Vila Real, Alfanzinha and Sagres inside the period 2012-2016 by the TRADE project 1. The main goal of the TRADE network is to improve safety in navigation and port operations in the Gulf of Cadiz, from the Straits of Gibraltar (Spain) to Cape St. Vicente (Portugal). Use of the Portuguese HFR data includes validation of numerical surface currents models, tracking of marine pollutants and use in SAR cases. A CODAR Tsunami Detection Software Package has recently been also installed on the Sagres HFR station as part of the OCASO project in order to develop tsunami detection algorithms that are adapted to the very complex bathymetry of the area.
Dalhousie uses surface current data in its coastal circulation and ocean forecasting models. Its Department of Oceanography works cooperatively with Canada's Department of Environment and Climate Change, which is home to the nation's weather forecasting programs and operations. The Atlantic Pilotage Association has also expressed interest in this Halifax R&D network, but from a wave monitoring perspective in support of ship traffic operations. On the Pacific coast, Ocean Networks Canada (ONC)  (Heesemann et al. , 2014).
Mexico The Mexican HF radar Network has its origin starting in 2003, when the Autonomous University of Baja California (UABC) acquired two SeaSonde CODAR systems, which were operational from 2003 to 2005 on Rosarito Baja California. Later in 2005 another two WERA type radars were purchased through a research project funded by the Concejo Nacional de Ciencia y Tecnologia (CONACyT, National Council of Science and Technology). Those two radars were installed in the Gulf of Tehuantepec, and were operational for almost 3 years  (Flores-Vidal et al. , 2014). Those early installations in Mexico had a completely oceanographic research purpose  (Flores-Vidal et al. , 2011 , 2013 , 2018)  but lacked operational continuity with gaps in the time series on the order of two to 3 months for the worse cases, and with absolutely no real time data transfer.
The installation, management and maintenance of this HFR network is being performed by a multi-institutional consortium which include more than 20 universities and research institutes in Mexico. Currently, OCOMEX operates 22 near real-time (NRT) HFR systems in Mexico and is actively working with United States-IOOS personnel to establish a relay to the HFRNet. The report highlights the requirement to collect surface current given its societal importance, and established priority for the location of HFR stations within eleven regional associations (RAs) which guide development of regional ocean observing activities. Furthermore, the plan provides technical design of the National Network to acquire radial current maps from individual HFR stations, process the radial maps into a Real Time Vector (RTV) product and establish requirements for data standards, management and distribution, while providing a metric of performance which is monitored daily.
The report also recognized the importance of staffing structure through academia/federal partnerships. The HFR National Network began collecting radial current maps from participating regions in 2006 (Figure  9 ). The geographic coverage for each region over the entire period of recording is shown for the main regions. Surface currents collected through IOOS HFR National Network are utilized by a number of federal agencies including United States Coast Guard (Search and Rescue), NOAA's Office of Response and Restoration (OR&R) (hazardous spill response), National Ocean Service Center for Operational Oceanographic Products and Services (CO-OPS) (ocean tidal prediction), as well as state and local agencies that use data in water quality management. Additionally, surface current data is distributed to various research and development groups that are assimilating HFR derived surface current into numerical models.
Australia The Australian Ocean Radar facility, based at the University of Western Australia is part of the Integrated Marine Observing System (IMOS), a national collaborative research infrastructure tasked with collection and dissemination of ocean data. The radar facility uses commercial direction-finding (SeaSonde) and phased-array (WERA) HFR systems. Each HFR node is configured primarily to sample ocean currents with a maximum range of over 200 km. Radar freely available from the IMOS portal 3 , are used for scientific research, operational modeling, coastal monitoring, fisheries and other applications  (Kerry et al. , 2016; Mihanovic et al. , 2016; Archer et al. , 2017 Archer et al. , , 2018;; Mantovanelli et al. , 2017; Schaeffer et al. , 2017; Wandres et al. , 2017). Between 2017 and 2018 asset relocation across the country was conducted, aimed at maximizing HFR coverage at a regional scale, and increasing data uptake.
, 2008). Topics include site setup of HFR equipment, power and cooling considerations, software/hardware configuration, data management and site maintenance. Additionally, HFR vendors provide guidance to HFR operators to assist with the goal of collecting the highest quality data as different locations may have specific issues and concerns and there is no "one size fits all" approach to HFR site deployment. In Europe, the EuroGOOS HF Radar Task Team was established in 2014, with the goals of: (i) promoting joint progress through networking and scientific synergies for key questions; (ii) developing best practices and tools exchange; (iii) improving administrative procedures and regulations (e. g. , the cross-border agreement for oceanographic radars in the 13-16 MHz band operating in the Western Mediterranean Sea in Spain, France and Italy was signed in February 2018); (iv) looking for complementary of HFRs with other multi-platforms and model products 6.
Simultaneously, definition of best practices in the implementation and use of HFR systems as well as the testing of methodological improvements on HFR retrievals and products is reported in the context of JERICO-NEXT project. Dealing with one of the main risks foreseen in order to ensure HFR sites sustainability (i. e. , downtime, outages and failures), the EU HFR data node, aligned with the leading efforts of MARACOOS, have shared best practices for the creation of HF Radar outages database  (Updyke, 2017)  as an aid for operations and maintenance. In spite of the fruitful collaborations between the HFR national networks, operators recognized the necessity for a centralization of methodologies and best practices documentation to increase efficiency, reproducibility and interoperability of the coastal HFRs network design, operation and maintenance tasks, In this context, the Ocean Best Practices (OBP) System 7  is emerging as the unified, sustained and readily global accessible knowledge based of interdisciplinary best practices in the ocean observing value chain to foster innovation and excellence.
Particularly, in the case of HFR, best practices documentation related to the EU network current status, QA/QC HFR surface current data, deployment & setup of HFRs and HFR data management are currently available at the IODE OBP repository 8. Nevertheless, an extra effort is required from the global HFR network to document best practices and to promote their propagation. Moreover, the involvement of HFR experts from different networks may contribute to the internal peer-review of best practices documents.
Quality Assurance/Quality Control Within the United States, IOOS strives to collect the highquality data for 34 identified core variables, which include ocean currents. To this goal, the Quality Assurance/Quality Control (QA/QC) of Real-Time Oceanographic Data (QARTOD) Project Plan was finalized in 2012, and established quality control procedures for the 26 core variables representing physical, chemical, biological, and multidisciplinary ocean observations (U. S. Integrated Ocean Observing System [IOOS], 2017). Coordinated effort between manufacturers, academic researchers and federal scientists created the Manual for Real-Time Quality Control of High Frequency Radar Surface Current Data published in 2016 (U. S. Integrated Ocean Observing System [IOOS], 2016). The manual incorporates existing QA/QC procedures from a group of HFR experts, and identified a number of tests to ensure QA/QC of both radial current measurement and total current vector measurement.
Efforts to implement these tests in the real time data stream are ongoing and occurring at the radial current collection sites, and at the National Network. In order to deliver high quality HFR data for scientific, operational and societal applications and to enforce discovery and access for HFR data, the European HFR community defined a standard model for data and metadata for producing NRT HFR surface current data, aimed at ensuring efficient and automated HFR data discovery and interoperability. This data model will be the operational data delivery model since the entry in service of HFR data distribution in CMEMS-INSTAC occurs in April 2019. The model has been implemented according to the standards of Open Geospatial Consortium (OGC) for access and delivery of geospatial data, and compliant with the Climate and Forecast Metadata Convention CF-1.
Data Access and Visualization Within the United States, the HFR National Network data management system relies on robust communications between the individual HFR installations and centralized data repositories that are updated in NRT. Radial surface currents are measured hourly at HFR installations (a site) and synced with one of 9 local regional operations centers (a portal) that aggregate radial current data from all HFR sites within a RA. In turn, data from the portals are accumulated at two redundant data repositories (a node) which are housed at Scripps Institution of Oceanography (SIO) and the National Data Buoy Center (NDBC). The primary node, located at SIO, serves the hourly radial current files to HFRNet processing machines which produce near real-time total vector (RTV) product generated on grids with multiple resolutions (500 m, 1, 2, and 6 km).
Distribution of the RTV and 25-hr average products is accomplished through a Thematic Real-time Environmental Distributed Data Services (THREDDS) server  9. THREDDS provides an interface to data access using a number of open source protocols including OpenDap, Web Mapping Service (WMS), Web Coverage Service (WCS), NetCDF Subset, and others. Sample code is available for utilizing these services with popular data processing platforms such as MATLAB and Python/Matplotlib. Vector tiles of all RTV products are available to web mapping applications via a publicly accessible application programming interface 10. In addition to RTV products, the diagnostic information included in the HFR radial files is stored in a database and displayed to site operators through the HFRNet diagnostics portal. Diagnostic information includes hardware specific data such as system voltages, transmitted and reflected power and radial vector data such as range, number of solutions and signal to noise ratio.
Finally, overall IOOS network performance is evaluated using diagnostics from individual sites contributing to HFRNet through a real-time metric that is reported to the IOOS program manager and site operators. This metric categorizes when a radial file passes certain criteria, which are based on long term statistics of similar sites within the HFRNet archive. These criteria include the arrival time of a radial file (file must be received at HFRNet within 24 h of its collection) and the number of solutions (the number of valid radial solutions in the file must exceed a baseline). In addition to THREDDS for both NRT and delayed mode (DM) products, the Australian Ocean Data Network (AODN) is making publicly available aggregated HFR data through their portal 11. This includes surface currents, wind and wave maps.
Within Europe the major platform for marine data distribution are CMEMS-INSTAC and the SeaDataNet infrastructure (SDN/SDC). They operate through a decentralized architecture based on National Oceanographic Data Centers (NODC) Production Units (PUs) organized by region for the global ocean and the six European seas and a Global Distribution Unit (DU). The core of CMEMS-INSTAC and SDC is to guarantee for the users the quality of the product delivered is equivalent wherever the data are processed. In this framework, in order to enforce and make operational the efficient management of HFR data for INSTAC PUs, other CMEMS Thematic Centers (TAC) and Marine Forecasting Centers (MFC), the establishment of the HFR data stream has to be organized in a coordinated way, in collaboration with the regional alliances of EuroGOOS and the regional and global components of the CMEMS In Situ TAC.
The implementation of the HFR data stream will be operated by a centralized European competence center: the EU HFR Node. This implementation will be performed in the frame of CMEMS In Situ TAC with the established formats and standards on QC flags and tests, dimension, naming, definition and syntax of coordinated variables. The EU HFR Node will act as focal point with the European HFR data providers, the key EU networking infrastructures and the Global HFR network. The key roles of the EU HFR Node will be the connection with data providers for NRT and reprocessed (REP) data, the connection with CMEMS-INSTAC for NRT and REP data, the connection with SeaDataNet for REP data. The node will also ensure optimal visibility of HF radar data and foster the applications based on HF radar data. The EU HFR Node will facilitate the management and integration of any potential data provider according to a simple and very effective rule: if the data provider can set up the total surface current data flow according to the defined standards, the HFR central node only has to link coordinated approach in Mediterranean Sea on SAR applications was made during the Tosca Project  (Bellomo et al.
, 2017). This event occurred on October 14th, 2016, when a series of severe storms were impacting the Eastern Pacific coasts. These storms were the remnants of Typhoon Songda, thus the triggering event was atmospheric in origin and there was no seismic alert issued at that time. An in-depth a posteriori analysis of the meteorological data gathered during the event, together with the recorded HF radar data in the light of an improved tsunami detection algorithm, clearly showed that two successive abnormal long waves impacted the coast, which was a meteotsunami  (Guérin et al. , 2018). This tsunami was first detected by the HFR 60 km offshore, about 45 min before its arrival on the coast. The meteotsunami cleared the lowest threshold of the WERA detection software and then triggered a detection at the higher threshold 20 min later, thereby confirming the presence of the oncoming wave.
Cross-shore currents show strong seasonality at Cape Mendocino (∼40N) and other major headlands, where topography can steer the currents (e. g. , deflection of the strong alongshore current) and mesoscale eddies can develop and persist (e. g. , 1-year persistence of 100-km eddy off Cape Mendocino in 2008,  Halle and Largier, 2011). Along the east coast of the United States, similar long-term datasets show the distinct differences in mean and seasonal surface circulation between coastal waters and the Gulf Stream offshore. Plots of annual mean alongshelf flow show a gradual increase with distance offshore in the Mid-Atlantic Bight reaching a maximum near the shelf break (Figure  12B ). The interannual variability of the alongshore current measured so far has a range between 3 and 11 cm/s. New insights from HFR also elucidate the eddy-driven exchange of water between coastal and offshore regions here and elsewhere (e.
g. ,  Kim et al. , 2011; Rypina et al. , 2016). Over a decade of HF Radar data is also available from northern Japan, providing an unprecedented view of the distinct seasonal variation in the Soya Warm Current. Hokkaido University, has operated five HF radars along the northern coast of Hokkaido since August 2003  (Ebuchi et al. , 2006). The radars cover the Soya/La Perouse Strait between Hokkaido, Japan, and Sakhalin, Russia. The Soya Warm Current enters the Sea of Okhotsk from the Sea of Japan through this strait and flows along the coast of Hokkaido as a coastal boundary current. Figure  13  shows the monthly averaged profiles of the alongshore surface current across the eastern outlet of the Strait with respect to the distance from the coast line of Hokkaido, Japan. The error bars indicate the standard deviation over 15 years from 2003 to 2018.
Environmental Management HF Radar data are increasingly being used in support of environmental management, including short-term pollution events and long-term resource management. Specifically, data have been used in tracking the fate of runoff  (Rogowski et al. , 2015)  and wastewater discharges in southern California, residence time in Monterey Bay  (Coulliette et al. , 2007) , and source-sink of water parcels off northern California  (Kaplan and Largier, 2006). Further, HFR data have been used in identifying circulation features that account for plankton blooms, including harmful algal blooms imported to the Ria de Vigo  (Piedracoba et al. , 2016)  and phytoplankton delivery to the rich ecosystems of Cordell Bank and the Gulf of Farallones  (Halle and Largier, 2011). Other unpublished work has used these surface current data in designing networks for marine protected areas, and assessment of transport of juvenile salmonids in coastal waters.
Ocean Model Validation and Assimilation In addition to direct use of HFR data in operational and retrospective assessment, HFR surface current data are distributed to various research and development groups that assimilate HFR-derived surface current into numerical models that simulate 3-dimensional circulation and water properties in the coastal ocean. Because of the large spatial extent and high-frequency sampling of surface currents that resolve tidal variability and small-scale topographic effects, the assimilation of these data has been shown to greatly improve model realism and confidence (e. g. ,  Chao et al. , 2018). Increasingly, this is a preferred way to deliver the value of HFR datasets as it combines the benefits of models and real data. A number of publications already exist on the assimilation of both surface currents and wave HFR data  (Breivik and Saetra, 2001; Paduan and Shulman, 2004; Barth et al.
, 2008 Barth et al. , , 2011;; Waters et al. , 2013; Marmain et al. , 2014; Ren et al. , 2015; Sperrevik et al. , 2015; Stanev et al. , 2015; Iermano et al. , 2016; Hernández et al. , 2017 , to mention only a few examples). For the entire United States west coast, the large-scale, high-resolution West Coast Ocean Forecast System (WCOFS) is developing a capability to assimilate HFR surface currents into a 2-km-resolution, Regional Ocean Modeling System (ROMS) numerical model  (Kurapov et al. , 2017). Typically, radial data are used for assimilation into regional models. An effort is underway led by University of California Santa Cruz in evaluating the impact of ocean observing system measurements on ocean analysis and forecast systems -including assessment of the best data type and the best data locations in terms of improved model realism and confidence.