The SeaDataNet data products: regional temperature and salinity historical data collections

• Main Authors: Simoncelli, Simona, Coatanoan, Christine, Back, Orjan, Sagen, Helge, Scory, Serge, Myroshnychenko, Volodymyr, Schaap, Dick, Schlitzer, Reiner, Iona, Sissy, Fichaut, Michele
• Format: Conference Object
• Language: English
• Published: EGU 2016 - European Geosciences Union General Assembly 2016. 17-22 April 2016, Austria. 2016
• Subjects: Arctic; Climate change; North Atlantic
• Online Access: https://archimer.ifremer.fr/doc/00326/43753/43286.pdf; https://archimer.ifremer.fr/doc/00326/43753/43292.pdf; https://archimer.ifremer.fr/doc/00326/43753/

Temperature and Salinity (TS) historical data collections covering the time period 1900-2013 were created for each European marginal sea (Arctic Sea, Baltic Sea, Black Sea, North Sea, North Atlantic Ocean, Mediterranean Sea) within the framework of SeaDataNet2 (SDN) EU-Project and are available as ODV collections trough the SeaDataNet web catalog at http://sextant.ifremer.fr/en/web/seadatanet/. Two versions have been published and they represent a snapshot of the SDN database content at two different times: V1.1 (January 2014) and V2 (March 2015). A Quality Control Strategy (QCS) has been implemented and continuously refined in order to improve the quality of the SDN database content and to create the best product deriving from SDN data. The QCS was originally implemented in collaboration with MyOcean2 and MyOcean Follow On projects in order to develop a true synergy at regional level to serve operational oceanography and climate change communities. The QCS involved the Regional Coordinators, responsible of the scientific assessment, the National Oceanographic Data Centers (NODC) and the data providers that, on the base of the data quality assessment outcome, checked and eventually corrected anomalies in the original data. The QCS consists of four main phases: 1)data harvesting from the central CDI; 2) file and paramenter aggregation; 3) quality check analysis at regional level; 4) analysis and correction of data anomalies. The approach is iterative to facilitate the upgrade of SDN database content. SDN data collections and the QCS will be presented and the results summarized.