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37th CIESM CONGRESS (Barcelona, 7-11 June 2004). MEDATLAS 2002: database and data management system for the long term monitoring of Mediterranean and Black seas.
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37th CIESM CONGRESS (Barcelona, 7-11 June 2004) MEDATLAS 2002: database and data management system for the long term monitoring of Mediterranean and Black seas C. MAILLARD, E. BALOPOULOS, N. MIKHAILOV, M. FICHAUT, G. MAUDIRE, M-J. GARCIA, B. MANCA, A. SUVOROV, A. GIORGETTI, A. IONA, M. RIXEN and MEDAR Group EC-MAST Concerted Action (MAS3-CT98-0174/ERBIC20-CT98-0103)
Background and Objectives • Long term monitoring requires long time series of marine observations, especially vertical profiles of temperature, salinity and bio-chemicals which represent basic environmental parameters • Long time series of data are also necessary to compute statistics that will be used to qualify new data • Such data are collected by scientific teams of many countries, but in most cases they remain dispersed in heterogeneous formats and systems. Their access is difficult, and due the lack of appropriate archiving, they are frequently in danger to be lost. • Under the frame of the GODAR (Global Ocean Data Archaeology and rescue) and following two pilot projects MODB and MEDATLAS I, the EU regional sconcerted action MEDAR/MEDATLAS-II (MAS3-CT98-0174 & ERBIC20-CT98-0103), was launched in 1998 with the overall objective to make available a comprehensive data product of multi-disciplinary in-situ data and information in the Mediterranean and Black Sea, through a wide co-operation of the bordering countries.
CD-ROM 3: ClimatologyGlobal + W-Mediterranean CD-ROM 4: climatologyBlack Sea + E-Mediterranean Result : a database on A set of 4 CD-ROMs • CD-ROM 1: Documentationon the project and its results Cruise inventory Software QCmedarODV CD-ROM 2: DatabaseObserved data + SELMED interface for extraction (according to various criteria), interpolation and visualization - export formats: MEDATLAS, CSV or ODV.
DATA BASE CONTENT(DATA TYPE) Oldest data set: 1889
QUALITY CHECKS QCO : Automatic check of the format QC1 : Automatic and visual check of the headers QC2 : Automatic and visual check of the data points • a quality flag to each numerical value (GTSPP flag scale)
DATA QUALITY OUT OF STATISTICS DOUBTFUL FALSE GOOD NO QC
CLIMATOLOGY: Methodology • Computation of Climatological Analysis by Variational Inverse Model (VIM) algorithms • Computation made on finite elements and then re-interpolated on a regular grid (0.2 degrees in Latitude and Longitude), with smaller scales for local computations • T, S and bio-chemical climatology reviewed by regional experts and modellers http://modb.oce.ulg.ac.be/Medar
CLIMATOLOGY - Results Selected numerical fields depending on data availability: • Annual , seasonal and monthly climatology • Temperature, Salinity • Annual and seasonal • Oxygen, Silicate, Phosphate • Hydrogen sulphide (H2S) in the Black Sea • Annual only • Nitrate, Nitrite, pH, Ammonium, Alkalinity, Chlorophyll • No climatology • Total Phosphorus, Total Nitrogen
CLIMATOLOGY – Results2500 horizontal maps, vertical sections and stations locationSOME EXAMPLES
Conclusion 1: Present Services MEDAR network disseminate MEDATLAS 2002, presently the best available integrated data base for the Mediterranean & BLack Seas. It provides also further data services: • Extraction and distribution of regional or thematics subsets, to answer specific requests, • Implementation of the common protocols and practices for data formatting and checking for quality, • Additional services at the national levels: continuous compilation, quality checking with feedback to source scientists, perennial archiving and dissemination of new data. Visit our distributed web site: www.ifremer.fr/medar
Conclusion 2:Further needs to meet • Direct internet access to the more complete available data sets : historical data + data released in recent projects including real time data - Use of up-to-date communication technology for data dissemination • Increase in quantity and quality the data and products availability such as estimates of the mean, decadal, seasonal, monthly statistics at basin, regional and shelf scales – requires a large quantity of data of good quality • Improve and document the QC standards and protocols, especially for bio-chemicals and products • Increase efficiency through enhanced international cooperation & capacity building activities - requires more portable software, meetings and training courses • Increase of the public awareness on the data heritage • New concerted actions in preparation: SEA-DATANET