dataesr/scientific-paragraphs-categorization huggingface dataset:
Atmospheric CO 2 values Data providers can now submit measurements of atmospheric CO 2 mole fraction, made in parallel to surface water f CO 2. A separate WOCE flag will be created for measurements of the atmospheric CO 2 mole fraction in future SOCAT versions. Once quality control has been carried out on the atmospheric CO 2 measurements, such values will be included in the SOCAT data products. In future, atmospheric f CO 2 will be calculated from atmospheric xCO 2 values, both from the measurements and from GLOBALVIEW-CO2 (2014) values. New graphics will enable comparison of surface ocean f CO 2 values to atmospheric f CO 2 values. The graphs will become an important quality control tool. Future data products will contain atmospheric f CO 2 values calculated from atmospheric measurements and from GLOBALVIEW-CO2, in addition to the atmospheric mole fractions from GLOBALVIEW-CO2 already part of the SOCAT data products (Table  9 ).
Additional surface water parameters In 2014, SOCAT scientists decided to allow inclusion of additional surface water parameters accompanying surface water f CO 2 values in SOCAT data output files  (SOCAT, 2014a). Such additional parameters might include dissolved inorganic carbon, total alkalinity, pH, nutrients, methane (CH 4 ) and nitrous oxide (N 2 O) concentrations. SOCAT scientists will not carry out quality control on these additional parameters, but would welcome collaboration with other communities taking responsibility for this. These additional parameters will be made public in parallel to the official SO-CAT releases. The extra parameters will be posted in separate data files to emphasise that they have not been qualitycontrolled. A SOCAT and MEMENTO (MarinE MethanE and NiTrous Oxide;  Bange et al.
, 2009)  working group is considering the way forward for surface water CH 4 and N 2 O measurements  (SOCAT and SOCOM, 2015). 7 Impact and scientific highlights of SOCAT 7. 1 A multi-decade record of surface ocean f CO 2 values SOCAT provides a record of the history of surface ocean CO 2 research (Fig. 3 ). Initial, exploratory surface water CO 2 measurements in the late 1950s, 1960s and 1970s were followed by more frequent CO 2 data collection on research ships in the 1980s and large (inter)national research programs, such as the World Ocean Circulation Experiment (WOCE), the Joint Global Ocean Flux Study (JGOFS) and the Tropical Atmosphere Ocean (TAO) network in the 1990s. The operation of CO 2 instruments on ships part of the Carbon Voluntary Observing Ships (Carbon VOS) programme, also referred to as the Ships Of Opportunity Programme (SOOP), strongly increased the number of available f CO 2 values from the 1990s onwards.
Data availability in the SO-CAT collection has increased 4-fold from 0. 2 to 0. 4 million f CO 2 values per year for the years 1995 to 2000 to 1. 0 to 1. 2 million values per year for 2005 to 2012. Nevertheless, large gaps are notable in the data collection since the year 2000, e. g. in the Indian Ocean, the South Pacific Ocean, the Mediterranean Sea, the East China Sea, the Malay Archipelago and the Sea of Okhotsk. Elsewhere, in the Arctic Ocean, measurements are being reported for the first time. The seasonal distribution of surface ocean f CO 2 values in the relatively data-rich decade from 2000 to 2009 is shown in Fig. 4. This figure highlights the lack of winter data in the high-latitude oceans, as well as the opposing seasonal cycle of surface ocean f CO 2 in the subtropical and temperate oceans  (Takahashi et al.
Impact of SOCAT SOCAT and its data products are cited or named in influential international reports, in more than 100 peer-reviewed scientific publications, PhD and master's theses, book chapters and numerous other publications, as listed on the SO-CAT website (http://www. socat. info/publications. html). Figure  7  shows the rapid increase in such publications, since the initiation of  SOCAT in 2007 (IOCCP, 2007)  and the first SOCAT release in 2011  (Pfeil et al. , 2013; Sabine et al. , 2013). The SOCAT data collection forms the basis of several data products (http://www. socat. info/products. html) and diverse scientific applications. These include a dozen mapping products of surface ocean pCO 2 and air-sea CO 2 fluxes for the global oceans (see overview in  Rödenbeck et al. , 2015). The SOCAT gridded product and one data product based on SOCAT  (Landschützer et al.
, 2015)  are integrated with the ESMValTool  (Eyring et al. , 2016)  for routine evaluation of Earth system models. For the same purpose, the SOCAT gridded product is currently being integrated into the Obs4MIPs (Observations for Model Intercomparison Projects) data repository  (Ferraro et al. , 2015). Citation of SOCAT in high-impact reports, scientific applications of SOCAT and scientific findings based on SOCAT are discussed below. The importance of the SOCAT synthesis is highlighted by its citation in three categories of high-impact reports, notably reports on ocean observing systems, assessments of climate change and global carbon budgeting, including carbon observing strategies, and ocean acidification studies. -Reports on ocean observing systems include publications from OceanObs'09  (Borges et al.
Scientific applications of SOCAT SOCAT is used for a variety of scientific applications (Fig. 7b ), some of which imply a wider relevance for SOCAT data products than envisaged during the creation of SOCAT  (IOCCP, 2007). Scientific applications of SOCAT include figures of surface ocean CO 2 observations; use of SOCAT tools and protocols; use of surface ocean f CO 2 in diverse environmental studies; model-data comparison, model evaluation and data assimilation; detection of ocean acidification trends; regional process studies of surface ocean f CO 2 ; quantification of coastal ocean carbon sinks and sources; quantification of the ocean carbon sink and its variation; quantification of the land carbon sink. These applications are roughly listed in order of the increasing importance of the SOCAT synthesis for the studies.
The use of the SOCAT data collection in peer-reviewed, scientific publications is evolving. Initial publications made reference to the ongoing synthesis activity. Actual use of the SOCAT data collection started as soon as version 1 was released in 2011  (Pfeil et al. , 2013; Sabine et al. , 2013). Studies that heavily rely on SOCAT data products, such as modelling, ocean acidification trend analysis and carbon budgeting, represent one-third to half of the scientific publications citing or naming SOCAT from 2013 onwards. Examples of scientific applications of SOCAT are given below. There is no strict separation between the different types of applications identified here, with several studies belonging to more than one type of application. Many of the studies use surface ocean pCO 2 values, derived from the f CO 2 values reported in SOCAT data products.
Figures of surface ocean CO 2 observations. Newly created figures based on the SOCAT data collection and existing figures from SOCAT publications have been used in scientific publications. Such figures generally highlight the availability or lack of surface ocean CO 2 data in specific regions or seasons or over time  (Chierici et al. , 2012; Regnier et al. , 2013; Wanninkhof et al. , 2013a; Ciais et al. , 2014; Majkut et al. , 2014a; Brévière et al. , 2015; Hofmann et al. , 2015). Use of SOCAT tools and protocols. A variety of tools and protocols has been developed in SOCAT. One of these is the definition of a continental margin mask which defines coastal waters as waters within 400 km from land  (Pfeil et al. , 2013). Evans and Mathis (2013)  and  Evans et al. (2015)  use this continental margin mask.
, 2014; McKinley et al. , 2016). In several studies, model data are subsampled to surface ocean pCO 2 observations from SOCAT  (Séférian et al. , 2014; Tjiputra et al. , 2014; Turi et al. , 2014). Cooley et al. (2015)  evaluate surface ocean pCO 2 values from an integrated assessment model with pCO 2 observations from SOCAT and other sources. SOCAT data products are supporting model evaluation in context of the Coupled Model Intercomparison Project (CMIP) and beyond  (Eyring et al. , 2016). The SOCAT data collection is used for assimilation of surface ocean pCO 2 values in global ocean biogeochemical models  (While et al. , 2012; Simon and Bertino, 2013, as cited in Gehlen et al. , 2015). Ocean biogeochemical models have many applications, such as quantification and attribution of trends in the ocean carbon sink (Le  Quéré et al.
Quantification of coastal ocean carbon sinks and sources. SOCAT data products are used for quantification of CO 2 sources and sinks in coastal seas. Such studies are regional or global in extent  (Chen et al. , 2013; Signorini et al. , 2013; Laruelle et al. , 2014 Laruelle et al. , , 2015)). Quantification of the ocean carbon sink and its variation. An important application of the SOCAT data collection is quantification of the ocean carbon sink on seasonal to multiyear timescales with a mapping or gap-filling method. Such studies may be regional or global in extent. Studies tend to be either for the coastal seas  (Signorini et al. , 2013)  or for the open ocean  (Rödenbeck et al. , 2015). The studies interpolate sparse pCO 2 data from a SOCAT or LDEO synthesis product in time and space by a gap-filling method.
Scientific findings obtained using the SOCAT data collection This section provides an overview of scientific findings obtained using the SOCAT data collection. Model-to-data comparison. Schuster et al. (2013)  carry out a comparison of CO 2 air-sea fluxes for the Atlantic Ocean from data-based methods, ocean biogeochemical models, ocean inversion, and atmospheric inversions. The seasonal cycle and year-to-year variation in the fluxes differ between the various methods for most Atlantic regions. Two studies subsample model pCO 2 data to surface ocean pCO 2 observations derived from SOCAT. The authors conclude that ocean biogeochemical models on average underestimate the spatial and temporal variation in regional and global surface ocean pCO 2 by 10 to 40 %  (Séférian et al. , 2014; Turi et al.
Conclusions SOCAT version 3 represents an important release of the SO-CAT data collection, by creating a 58-year data record and by adding many additional data sets for recent years. The new data set flag of E in version 3 now enables inclusion of calibrated surface ocean f CO 2 measurements from alternative sensors (with an accuracy of better than 10 µatm) made on alternative platforms, such as moorings and drifters, in remote and less remote ocean regions. This article provides an ESSD "living data" update of SOCAT version 3. The launch of the SOCAT automation system will enable annual SOCAT releases from version 4 onwards. The rapid growth of scientific publications using SOCAT (Fig. 7 ) demonstrates the importance of this synthesis activity by the international marine carbon community.
The SOCAT data collection is being used in high-impact, scientific applications such as evaluation of ocean biogeochemical models, carbon budgeting, and trend analysis of the ocean carbon sink and ocean acidification. SOCAT-based studies have informed the Paris climate negotiations, as the 2015 Global Carbon Budget was released at the 21st Conference of the Parties of the United Nations Framework Convention on Climate Change (Le  Quéré et al. , 2015b). However, despite much progress in data synthesis, major uncertainties remain in observation-based studies of the ocean carbon sink and ocean acidification due to (1) inadequate spatial and seasonal data coverage, (2) short data records, and (3) uncertainty in the correction for "natural", pre-industrial oceanic outgassing of land-derived CO 2  (Jacobson et al.
, 2007)  and any anthropogenic perturbation of this outgassing  (Regnier et al. , 2013). Data coverage is particularly poor in the Indian Ocean, the Southern Hemisphere oceans and coastal seas and in the high-latitude oceans, notably in ice-covered regions and in winter  (Figs. 3, 4 and 6). The above reinforces the need for the continuing collection and synthesis of accurate, well-calibrated and welldocumented observations and investment in high-quality surface ocean CO 2 measurements on autonomous platforms. Adequate resources need to continue to be made available for data collection, quality control and data synthesis. Sys-D. C. E. Bakker et al. : A multi-decade record of high-quality f CO 2 data tems should be automated whenever possible. The SOCAT data synthesis highlights the success of a bottom-up approach with buy-in from the international marine carbon community and endorsement by IOCCP, SOLAS and IMBER.
Data availability This manuscript describes how the synthesis product has been created (Sect. 4) and how the individual data set files, synthesis files and gridded products can be accessed (Sect. 5) (Table  8 ). Individual data set files, all combined forming the synthesis product, can be downloaded here: doi:10. 1594/PANGAEA. 849770. Global and regional files are available as compressed zip text files via CDIAC (http: //cdiac. ornl. gov/ftp/oceans/SOCATv3/). The global synthesis product for data sets with flags of A to D is also available in Ocean Data View format (https://odv. awi. de/en/data/ ocean/socat_fCO2_data). The gridded products are available here: doi:10. 3334/CDIAC/OTG. SOCAT_V3_GRID. Further details are in Sects. 4 and 5.
Key characteristics of the SOCAT data products in version 3 (Sect. 5)(afterBakker et al. , 2014). Data products differ in whether they include data sets with flags of A to D or A to E and f CO 2 rec values with a WOCE flag of 2 only or 2 to 4. Two data products provide access to metadata. Quality control comments are available via the Table of Datasets in the Data Set Viewer. The SOCAT website (http://www. socat. info) and the web links in the footnotes provide access to the data products.
Content of the individual data set files (IF) and the synthesis files inSOCAT version 3 (after Bakker et al. , 2014). The global synthesis product is available as zip text files (ZIP) at CDIAC and in Ocean Data View (ODV) format (Table8). Subsets of the global synthesis data set can be created via the Data Set Viewer (DSV), both in the main menu and via the Table of Datasets. The first column lists column headers for the parameters in the files. √.
Acknowledgements. Research vessel Tiglax in Columbia Bay, Alaska, is shown on the website for SOCAT version 3. The Columbia Glacier can be seen at the head of the bay, as well as calved ice from the glacier. The photo was taken by  Wiley Evans. Pete Brown  ( National Oceanography Centre Southampton, UK ) designed the SOCAT logo. IOCCP (via a  US National Science Foundation  grant to the Scientific Committee on Oceanic Research),  IOC-UNESCO  ( International Oceanographic Commission of the United Nations Educational, Scientific and Cultural Organization ), SOLAS and IMBER provided travel and meeting support. Funding was received from the  University of East Anglia (UK) , the  Bjerknes Centre for Climate Research (Norway) , the  Geophysical Institute at the University of Bergen (Norway)  and the  University of Washington (US).
The  US National Oceanic and Atmospheric Administration (NOAA)  made important financial contributions via the  Climate Observation Division of the Climate Program Office , the  NOAA Ocean Acidification Program , the  NOAA Pacific Marine Environmental Laboratory (PMEL) , the  NOAA Atlantic Oceanographic and Meteorological Laboratory (AOML)  and the  NOAA Earth System Research Laboratory. Funding was also received from  Oak Ridge National Laboratory (US ), PANGAEA ® Data Publisher for Earth and  Environmental Science (Germany) , the  Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research (Germany) , the  Antarctic Climate and Ecosystems Cooperative Research Centre (Australia) , the  National Institute for Environmental Studies (Japan)  and  Uni Research (Norway). Research projects making SOCAT possible included the  European Union projects CarboChange  ( FP7 264879 ),  GEOCARBON  ( FP7 283080 ) and AtlantOS (633211), the  UK Ocean Acidification Research Programme  ( NE/H017046/1 ; funded by the  Natural Environment Research Council (NERC)  and the  Departments for Energy and Climate Change and for Environment, Food and Rural Affairs (Defra) ) and the  UK Shelf Sea Biogeochemistry Blue Carbon project  ( NE/K00168X/1 ; funded by  NERC and Defra).
A monthly 0. 25 • × 0. 25 • gridded data set exists for coastal regions. 1 PANGAEA ® : https://doi. org/10. 1594/PANGAEA. 849770. 2 CDIAC: http://cdiac. ornl. gov/ftp/oceans/SOCATv3/. 3 Data Set Viewer: Ocean Data View: https://odv. awi. de/en/data/ocean/socat_fCO2_data/. 4 CDIAC: Table of Datasets via the Data Set Viewer 4 ; select "Table of Datasets". 6 http://ferret. pmel. noaa. gov/SOCAT_Data_Viewer/; select "Data Set", then "Cruise data" and "SOCAT v3 data collection". 5 http://cdiac. ornl. gov/ftp/oceans/SOCATv3/SOCATv3_Gridded_Dat/. 7 Gridded Data Viewer: http://ferret. pmel. noaa. gov/SOCAT_Data_Viewer/; select "Data Set", then "Current Version Gridded (v3)".
Flooded areas are key information to crisis managers, both at local and national level. They help sizing human and material resources to be deployed before and during a flood. These data already exist on several French rivers as they are been produced in a legislative framework but mainly addressing the hundred-year flood. The purpose of the Flood Forecasting Services is to complete water levels forecasting published on www. vigicrues. gouv. fr with forecasting information on spatial flooded areas. State services are developing new flooded areas ranging from first overflows to the hundred-year floods. A national database called VIGInond provides secure web services to access these new data. It was developed in 2015. A key step in the standardization of these new data is the collaboration between various state services.
The access to VIGInond is initially opened to the Ministry of Interior services. This first step allows the operators to test and to understand the impacts of forthcoming flooding. Once tested, it will be made available to other crisis managers through the forthcoming Vigicrues® portal version 2. The new data will be gradually included in Vigicrues® watercourses, while coastal areas and new watercourses will be subsequently added. These new information will increase awareness of flooding risks among stakeholders and citizens in the near future.
The Australian Government established the National Flood Risk Information Project (NFRIP). The project aims to improve the quality, availability and accessibility of flood information across Australia, and raises community awareness of flood risks. NFRIP is committed to delivering a number of significant outputs, including the development of an online portal (http://www. ga. gov. au/flood-study-web/) to provide a single point of access to existing flood risk information. Only historical and localized information are provided, very few spatial data are available. In the USA, DATABASE is to gather and unify information about flash flooding from different sources and detailed spatial investigations  [1]. This project is dedicated to the gathering of observed flooded areas and their visualization on the application.
The project is integrating : x the production of several expertized scenarios for flooded areas by the FFC, each scenario being linked to a specific water level at the gauging station; x the development of a database to store and manage flooded areas dataset at national level, as well as import features on a unique environment, called VIGInond ; x the establishment of interoperable data flow and tools for dissemination in order to easily provide VIGInond data. The produced VIGInond dataset can be used in two contexts: x preparation of flood crisis by sharing and appropriating the content of such data between crisis managers; x management of the crisis for the areas where operational data sets can be used to better anticipate the flooding based on the forecast.
A national database to store three types of information VIGInond -the national database of flooded areaswas developed under the contracting authority of SCHAPI and transferred to the FFC in February 2015. It stores the cartographic layers of the flooded areas in a specific format. Three types of geographical information can be stored in the database (see Fig. x the ZIP area representing the extent of the flooded surface for a water level at the hydrometric gauging station as representative as possible for the related sector. It is characterized by its outline and its upstream and downstream limits which best delimit the influence zone around the hydrometric station(s). x the areas flooded for a number of Water Height Classes for each ZIP: they represent the submersion heights related to the natural ground level.
Since 2013, several satellite missions were also conducted in the framework of the End-User Thematic Part of the ORFEO Accompaniment Program. This new high resolution information were tested during a project for rapid cartography within a partnership between CNES (the Spatial Agency), SCHAPI and SERTIT (the technology transfer Center for Earth Observation data of the University of Strasbourg  [4]. The results show that the satellite system is sufficiently agile and that the obtained data match the needs of crises managers. Besides pooling the aerial datasets at national level, a methodological guide has been produced by the services of the Environment Ministry. describes a protocol for assisting services on collecting highest water levels after a flood, as well as technical and organizational aspects.
A national leadership SCHAPI, as French National Flood Forecasting Service, is part of Environment Ministry and has been appointed to lead the consolidation of these new datasets. By encouraging a national approach for the forecasting of flooded areas, SCHAPI became responsible for the organization of the data collection on potential flooded area. This task includes also the coordination of any local actions related to the implementation and the broadcasting of this new reference data. The Floods Directive has led to the development of several tools based on open source software in order to meet the requirements for an industrial production of data on flooded areas. The use of high resolution DTM LIDAR topographic data raised questions about their use and the weight given to data during processing.
Tools, such as Cartino  [6]  developed by CEREMA (Center for Studies and expertise on the risks, the environment, mobility and planning) or Cartalin developed by the Rhône-Alpes regional service of the Ministry of Environment helped initiate answers about the resampling of DTM LIDAR and the reduction of output data  [7]. Based on these early experiences, SCHAPI and the FFC initiated a tool to meet the specific requirements of flood forecasting : CartoZI, developed on Open Source GIS software -QGIS -has been porting at a national level. CartoZI offers to the users a series of modules especially developed to take account of hydraulic and topographical data into the definition of flood zones. The method underlying the tool are the basic principles of flood mapping : x Step 1: Establish the profile along the water surface based on 3 different methods: reconstitution of the water surface for an observed event, by using all available historic data for this event : flood marks or water marks, aerial photographs or satellite images from the flooded area ; linear interpolation of water surface from existing records ; calculation of a water surface with a 1D model.
This optional process changes the contours to mitigate these effects. Two types of smoothing can be applied: x the raster smoothing. The idea is to use a neighbor pixel to assign values. This neighborhood and its attributed weighting are defined by a matrix filter. For each pixel, the module performs a weighted average of neighboring pixels, and assigns the new value to the central pixel. is smaller than the tolerance set by the user. CartoZI is planned to be distributed to data producers, but only to services on the ministry network for the first half of 2016.