From SeaDataNet to SeaDataCloud: historical data collections and new data products

Temperature and Salinity historical data collections covering the time period 1900-2013/2014 were created for each European marginal sea (Arctic Sea, Baltic Sea, Black Sea, North Sea, North Atlantic Ocean, and Mediterranean Sea) within the framework of SeaDataNet2 Project and they are available as ODV collections through a web catalog (https://www.seadatanet.org/Products/Aggregated-datasets). Two versions have been published and they represent a snapshot of the SeaDataNet database content at two different times: V1.1 (January 2014) and V2 (March 2015). A Quality Control Strategy (QCS) was developped and continuously refined in order to improve the quality of the database content and create the best data products. The QCS consists of four main phases: 1) data harvesting from the data infrastructure; 2) file and parameter aggregation; 3) secondary quality check analysis; 4) correction of data anomalies. The approach is iterative to facilitate the upgrade of the database content and it allows a versioning of data products. Regional temperature and salinity monthly climatologies have been produced from V1.1 historical data collections and they are also available (https://www.seadatanet.org/Products/Climatologies). Within the new SeaDataCloud Project the release of updated historical data collections and new climatologies is planned. SeaDataCloud novelties are the introduction of decadal climatologies at various resolutions, the development of climatologies for the Global Ocean and a task dedicated to new data products, like Mixed Layer Depth climatologies, Ocean Heat Content estimates, coastal climatologies from HF radar data. All SeaDataCloud products are available through a dedicated web catalogue together with their relative Digital Object Identifier (DOI) and Product Information Document (PIDoc) containing all specifications about product’s generation, quality assessment and technical details to facilitate users’ uptake. The presentation will briefly overview the existing SeaDataNet products and introduce the SeaDataCloud products’ plan, but the main focus will be on the first release (February 2018) of SeaDataCloud Temperature and Salinity historical data collections, spanning the time period 1900-2017, their characteristics in terms of space-time data distribution and their usability.SeaDataCloud ProjectPublishedVienna4A. Oceanografia e clim

SeaDataNet regional climatologies: an overview

In the frame of the SeaDataNet project, several regional climatologies for the temperature and salinity are being developed by different groups. The data used for these climatologies are distributed by the 40 SeaDataNet data centers. Such climatologies have several uses: 1. the detection of outliers by comparison of the in situ data with the climatological fields, 2. the the optimization of locations of new observations, 3. the initialization of numerical hydrodynamic models. 4. definition of a reference state to identify anomalies and to detect long-term climatic trends Diva (Data Interpolating Variational Analysis) software is adapted to each region by taking into account the geometrical characteristics (coastlines, bathymetry) and the distribution of data (correlation length, signal-to-noise ratio, reference field). The regional climatologies treated in this work are: - JRA5: North Atlantic - JRA6: Mediterranean Sea - JRA7: Baltic Sea - JRA8: North Sea, Arctic Sea Several examples of gridded fields are presented in this work. The validation of the different products is carried out through a comparison with the last release of the widespread World Ocean Atlas 2005

DiSSCo Prepare WP7 –D7.3 Assessment tools and direction map to the implementation of common DiSSCo policies

The Distributed System for Scientific Collections (DiSSCo) Research Infrastructure will operate a number of e-services, all of which will have policy requirements for participating institutions. These policies include those related to digital and physical access to specimens, digital image and specimen metadata, and FAIR / Open Data. Previous projects have shown that the policy landscape is complex, and Task 7.3 has developed a policy self-assessment tool that will allow DiSSCo to assess policy alignment across the consortium. This deliverable describes the development of the policy self-assessment tool and provides a walkthrough of the key features. The same technical framework was used to create a digital maturity tool, which was initially proposed by Task 3.1, and this is also described within this document. A set of recommendations are included that outline the future direction for the development of the policy tool.The Distributed System for Scientific Collections (DiSSCo) Research Infrastructure will operate a number´of e-services, all of which will have policy requirements for participating institutions. These policies include those related to digital and physical access to specimens, digital image and specimen metadata, and FAIR / Open Data. Previous projects have shown that the policy landscape is complex, and Task 7.3 has developed a policy self-assessment tool that will allow DiSSCo to assess policy alignment across the consortium. This deliverable describes the development of the policy self-assessment tool and provides a walkthrough of the key features. The same technical framework was used to create a digital maturity tool, which was initially proposed by Task 3.1, and this is also described within this document. A set of recommendations are included that outline the future direction for the development of the policy tool

SeaDataCloud Data Products for the European marginal seas and the Global Ocean

Data products, based on in situ temperature and salinity observations from SeaDataNet infrastructure, have been released within the framework of SeaDataCloud (SDC) project. The data from different data providers are integrated and harmonized thanks to standardized quality assurance and quality control methodologies conducted at various stages of the data value chain. The data ingested within SeaDataNet are earlier validated by data providers who assign corresponding quality flags, but a Quality Assurance Strategy has been implemented and progressively refined to guarantee the consistency of the database content and high quality derived products. Two versions of aggregated datasets for the European marginal seas have been published and used to compute regional high resolution climatologies. External datasets, the World Ocean Database from NOAA and the CORA dataset from the Copernicus Marine Service in situ Thematic Assembly Center, have been integrated with SDC data collections to maximize data coverage and minimize the mapping error. The products are available through the SDC catalogue accompanied by Product Information Documents containing the specifications about product’s generation, characteristics and usability. Digital Object Identifiers are assigned to products and relative documentation to foster transparency of the production chain, acknowledging all actors involved from data providers to information producers

SeaDataCloud Temperature and Salinity Historical Data Collections for the North Sea (Version 1)

The SeaDataCloud Temperature and Salinity Historical Data Collection for the North Sea includes open access in situ data on temperature and salinity for the period 1893 – 2017. The data were retrieved from the SeaDataNet infrastructure at the end of October 2017. The dataset format is ODV binary collections [3]. The quality control of the data has been performed with the help of ODV software. Data Quality Flags have been revised following common recommended procedures defined under SeaDataNet 2 project [2] in conjunction with visual expert check. Trajectories (“underway” data) and “discrete” data (CTD, XBT, discrete water samplers) have been handled separately

SeaDataCloud Temperature and Salinity Climatology for the North Sea (Version 1)

The SDC_NS_CLIM_TS_V1 product contains Temperature and Salinity Climatologies for the North Sea including annual, seasonal and monthly fields covering the time periods 1955-2014 and seasonal fields for 6 decades starting from 1955 to 2014 (1955-1964, 1965-1974, 1975-1984, 1985-1994, 1995-2004, 2005-2014). The climatological fields were computed with a dataset that combines data extracted from 2 major sources: 1) the SeaDataNet infrastructure and 2) the World Ocean Database 2018. The computation was done with the DIVAnd (Data-Interpolating Variational Analysis in n dimensions), version 2.3.1

Design of an oceanographic data base

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