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Michel Rixen 1 , Jean-Marie Beckers 2 and Catherine Maillard 3

A HYDROGRAPHIC AND BIO-CHEMICAL CLIMATOLOGY OF THE MEDITERRANEAN AND THE BLACK SEA: SOME STATISTICAL PITFALLS (modb.oce.ulg.ac.be/medar). The Color of Ocean Data Brussels, Belgium, November 2002. Michel Rixen 1 , Jean-Marie Beckers 2 and Catherine Maillard 3.

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Michel Rixen 1 , Jean-Marie Beckers 2 and Catherine Maillard 3

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  1. A HYDROGRAPHIC AND BIO-CHEMICAL CLIMATOLOGY OF THE MEDITERRANEAN AND THE BLACK SEA: SOME STATISTICAL PITFALLS(modb.oce.ulg.ac.be/medar) The Color of Ocean Data Brussels, Belgium, November 2002 Michel Rixen1, Jean-Marie Beckers2 and Catherine Maillard3 1. SOC, Southampton, UK (myr@soc.soton.ac.uk) 2.GHER, University of Liège, Belgium, (JM.Beckers@ulg.ac.be) 3. SISMER, Ifremer, Centre de Brest, BP70, 29280 Plouzane, France

  2. Task I, II, III, V At 15:20 Recent advances in oceanographic data management of the Mediterranean and Black Seas: The MEDAR/MEDATLAS 2002 data base By C. Maillard and E. Balopoulos (France, Greece)

  3. Task IV: climatology • Objective analysis • Optimal interpolation (OI) (+ sub-optimal schemes) • Successive corrections (SC) (+ sub-optimal schemes) • Variational inverse model (VIM) (stat. Equiv. to OI) • ….

  4. The Variational Inverse Model • Dimensional analysis+Bessel K1 correlation function

  5. Finite element mesh

  6. OI: Information crosses boundaries VIM:no bias

  7. Computational cost OI Field VIM OI Error field VIM

  8. Climatology: some details • 25 standard vertical levels • (Obsolete: automatic QC: • data rejected if outside 3*std locally) • Sandwell bathymetry at 2’ • Used for contours and FEM • Reference field=climatic field • (semi-normed analysis) • T,S,Alkalinity,DOX,NH4,NO2,NO3,PO4, SiO4,H2S,pH,Chl • Climatologic, seasonal, monthly, inter-annual and decadal temporal windows when relevant • 20km x 20 km, 8 km x8 km or 5 km x 5 km resolution • Analyzed and error fields

  9. A good example: enough data

  10. Another good example: enough data

  11. Even more good examples…

  12. VIM and OI: statistical hypotheses - gaussian frequency distributions - statistics are homogeneous and isotrope - uncorrelated noise Alboran, 200m, many data Levantine basin, 200m, few data

  13. Nitrite Salinity Phosphate Silicate Temperature Ph

  14. Vertical distribution of temperature

  15. Yearly distribution of salinity

  16. Monthly distribution (salinity)

  17. Ionian 1980 Months 2 1986 Months 3 4 9 1988 Months 7 1990 Months 10 11 1992 Months 5 1994 Months 1 Levantine 1984 Months 10 1986 Months 8 9 10 11 1988 Months 3 8 9 1990 Months 7 10 11 1994 Months 1 2 Possible bias ? Temp Temp

  18. 2D analysis appropriate?

  19. PO4 at 30m: coastal (<18km) and/or shallow sounding (<50m)

  20. With coastal data Phosphate (mmole/m3) Without coastal data Difference

  21. Ionian (36-37 ºN , 19-20ºE)

  22. Some potential problems… • Statistical hypothesis • Correlation length=100-300km, so at least 200-2000 data homogeneously distributed needed! • Few data at deeper levels: • extrapolate from upper levels? • Coastal data bias beyond the physical diffusion/ advection through correlation length: in several areas the only existing data • Last but not least: obvious errors in the raw data (e.g. instrument calibration)

  23. Selection of robust fields • 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 • So far: (almost) the best we can do…

  24. Future • More data! • Other parameters (e.g. ADCP, DIC, POM, DOC,…) • Multivariate analysis and QC (bio-chemical data!) • 3D Variational analysis? • More high level final products • Your feedback MEDAR Climatology: “modb.oce.ulg.ac.be/medar” Free access to - 2000 fields - 20000 figures - 600 animations

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