Black Sea GOOS

The Black Sea GOOS consortium was formed by the Black Sea countries, namely Bulgaria, Georgia, Romania, the Russian Federation, Turkey and Ukraine in 2001. The principles were fixed in a Memorandum of Understanding with the following aims and objectives:

1. To contribute to international planning and implementation of the GOOS and to promote it at national, regional and global level
2. To identify regional priorities for operational oceanography
3. To develop capacity of the regional countries and promote the level to sustain GOOS activities
4. To provide high quality data and time-series for a better understanding of the Black Sea ecosystem
5. To assess the economic and social benefits achieved by operational oceanography

The development of the Black Sea GOOS was originally supported by the EC FP5 project “A Regional Capacity Building and Networking Programme to Upgrade Monitoring and Forecasting Activity in the Black Sea Basin” (ARENA). ARENA is an operational oceanography oriented project aimed at regional capacity building in close collaboration with the regional and other relevant organisations in the Black Sea region. The successor project to ARENA is called ASCABOS (A Supporting programme for CApacity building in the Black sea region towards operational status of Oceanographic Services) which is funded by EC FP6 and is currently ongoing. ASCABOS’s main objectives are [19]:

• Coordination of a flexible and operative infrastructure for data and information exchange between key Black Sea scientific institutions to serve reliably observing and predicting the sea state and the ecosystem state

• Build the scientific capacity of human resources in the Black Sea region aimed at further development, maintenance and improvement of an operational observing and forecasting system through especially designed educational and training programme

• Continuously collecting and updating of the historical databases and metadata bases and extending the access of the end-users to these information sources by development of a Black Sea information system, that will contain all available metadata, compiled in the past (after validation), and efficient updating mechanisms by the Internet

• To organise a cost-effective VOS pilot programme, applying modern technologies and developments for data collection, transmission, storage, use and dissemination

The Black Sea GOOS data exchange is done via the Global Telecommunication System (GTS) using the code forms SYNOP, TEMP, PILOT, SHIP, BATHY, TESAC, BUOY, etc. In 2005, a Pilot experiment on operational functioning of the Black Sea nowcasting/forecasting system within the ARENA project was carried out. The pilot project demonstrated the exchange of data in real-time for target areas in the Black Sea. Only model data was exchanged in this pilot.

A brief description is available of the Black Sea real-time database from the Hydrometeorological Centre of Russia. No information of database type and system is mentioned. This system might be viewed as a segment of the distributed Black Sea database management system.

The ARENA homepage (http://www.arena-blacksea.net) is presenting a metadata service from the Institute of Marine Sciences, Middle East Technical University. These metadata describe the information on cruises and time-series from 1985-2001. Additional Black Sea metadata is on-hand at the European Directory of Marine Environmental Data (EDMED) database, hosted and maintained at the British Oceanographic Data Centre (BODC). This metadata database is used in the SeaDataNet project. Metadata information is unique to station, cruise information, and measurements. The metadata does not deal with the datum itself. In addition, the EDMED database is currently being updated through the ASCABOS project. The outcome of this update will be an upgraded version of EDIOS-Black Sea that directs the end-user to online viewable station information.

All data quality control checks are done within the originating institutes. There is no further information on basin wide checks using climatological datasets.