1. Operational Monitoring and Forecasting in the Aegean Sea Kostas Nittis National Centre for Marine Research, Athens, Greece National Centre for Marine Research, Athens, Greece Review of existing monitoring and forecasting systems Present capabilities Problems - Limitations Perspectives

2. Overview

3. Research efforts on O.O.  POSEIDON Project (1997-2000, 14.1 Meuro EFTA+HMNE) Integrated monitoring and forecasting system: real-time data from buoy network, daily forecasts, end-user products Partners: NCMR, ΟCEANOR, UoA, UoT, NTUA Operational since May 2000  MFS (1998-2001, 2002-2004): Development of multiparametric M3A station, VOS Measurements, High resolution regional and coastal models  MARSAIS (2001-2003): Synergy between SAR and buoy data, Validation of Algorithms, Detection and forecasting of oil-spills  FerryBox (2002-2005): Implementation of a European network for FerryBox measurements, Operational phase: 2002-2003  MAMA (2002-2004): Coordination on Mediterranean Scale, Capacity building, MERSEA (2002-2003): Towards GMES (2008)

4. * Height: 7.9 m * Width: 1.75 m * Weight: 900 kgr * Energy: Solar panels + batteries * Communication: Imarsat C, GSM every 3 hours The POSEIDON buoy network SeaWatch Buoys 4 Meteorological Sensors l Air Temperature l Atm. Pressure l Wind Speed/Direction 4 “Blue” Sensors l Temperature l Salinity l Current l Waves 4 “Green” Sensors l Dissolved Oxygen l Chlorophyll-A l Light Attenuation l Radioactivity

5. End-user products POSEIDON Products 4On-line data (“meteo”, “blue” and “green”) 4Processed Data (statistics etc.) 4Meteorological Forecasts 4Sea-State Forecasts (waves) 4Hydrodynamic model Forecasts (currents, T,S) 4Dispersion of Pollutants (oil-spills) 4Near-shore wave conditions www.poseidon.ncmr.gr

6. Surface circulation characteristics Nittis et al., GAOS 2002

7. High frequency variability Nittis et al., MPB 2001

8. Tracing of Water Masses Nittis et al., GAOS 2002

9. Spring bloom monitoring

10. The Μ3Α System

11. M3A Measurements

13. Limiting factors: Bio-fouling

14. Ferry Box Systems

15. Based on DAUT model (2d generation) Based on DAUT model (2d generation) Resolution: 5km Resolution: 5km Buoy data assimilation Buoy data assimilation Products : Height, Direction and Period fields Products : Height, Direction and Period fields Based on POM Based on POM Resolution: 5km, 31lev Resolution: 5km, 31lev Rivers and Dardanelles outflow simulation Rivers and Dardanelles outflow simulation Products: 3-D Velocity, Temperature and Salinity fields Products: 3-D Velocity, Temperature and Salinity fields Based on ETA LAM Based on ETA LAM Resolution: 20/10 km Resolution: 20/10 km Products: Wind, Air temperature, Relative Humidity, Precipitation, Cloud cover, Atm. Pressure, Fog, … Products: Wind, Air temperature, Relative Humidity, Precipitation, Cloud cover, Atm. Pressure, Fog, … Operational Models: POSEIDON (1 st generation)

16. New generation Wave Model (WAM) Mediterranean Wave Model Based on : WAM Resolution : 0.25 o Forced by the coarse (20km) atmospheric model Aegean Wave Model Nested to Mediterranean model Resolution : 0.05 o Forced by the fine (10km) atmospheric model

17. New Generation HD Model Eastern Mediterranean Model Based on : POM Resolution : 10 km Vertical Res. : 19 sigma levels Forced by the coarse (20km) atmospheric model Dardanelle's (open boundary) / Rivers Parameterisation Aegean Sea Model Nested to EMED model Resolution : 5 km Vertical Res. : 31 σ-levels Forced by the fine (10km) atmospheric model Boundary values updated every 1h (T, S, U, V, W, Z + free radiation) Initial + boundary values: MODB 12 years climatology, 95- 99 ECMWF analysis, operational 1999-now Interactive estimation of fluxes (heat-water)

18. Forecasting Skill Evaluation a) Buoy data Model Against Buoy data Atmospheric Model Statistics M: 24 hours forecasts O: Buoy observations

19. Forecasting Skill Evaluation b) XBT data

20. Forecasting Skill Eval. c) mesoscale features SST 1 October 2000: 24h forecast Forecasted Sea Level Elevation during Summer 2000 AVHRR SST

21. POSEIDON Operational Oil-spill Model Based on: PARCEL model (Koutitas 1988, Johansen 1985) Processes: Evaporation (Stiver et al. 1989) Emulsification (Rasmussen 1985) Beaching and sedimentation (Gundlach 1987) Advection – diffusion: 3-D current field Horizontal and vertical mixing coefficients from hydrodynamic model (Smagorinsky, Mellor-Yamada) Wave field Additional data: Date and the position of the “event” Initial volume of the pollutant Density of the different elements Evacuation time (Density of evaporation and emulsification, retention time) Products: Oil Concentration Beaching Evaporation, emulsification Pollani et al., MPB 2000

22. Synergy with SAR data: oil slicks detection Synthetic Aperture Radar: ERS1/2, RADARSAT, ENVISATERS1/2, RADARSAT, ENVISAT 0,056 μm, 5,3 GHz0,056 μm, 5,3 GHz Repeat cycle: 35 daysRepeat cycle: 35 days Resolution: 30mResolution: 30m Swath width: 100 km (400km Envisat)Swath width: 100 km (400km Envisat)

23. Towards forecasting in Coastal Areas Saronikos Gulf Model Resolution : 1.8 km Vertical Res. : 16 σ-levels Forced by the fine (10km) atmospheric model Nested to Aegean 5km model: Initial + boundary conditions Boundary values updated every 1h (T, S, U, V, W, Z + free radiation)

24. Next steps ?   Extend the current observing capacity Deeper layers (0-500 / 0-1000m) New platforms (eg HF radars) Operational RS products   Continue / Intensify efforts in coastal areas   Coordinate efforts with pan-european monitoring and forecasting efforts – Towards GMES (GMES Forum, EuroGOOS conference 3-6 December, Athens)