1. Department of Physical Oceanography Lab of Remote Sensing and Spatial Analysis Lab of Sea Dynamic

2. Lab of Remote Sensing and Spatial Analysis Investigations based on: satellite data (AVHRR, SeaWiFS, Meteosat) own measured data by HRPT Data Receiver Sonda STD Tethered Spectral Radiometer Buoy FluorometerTachymetr Coulter counter Beam transmittance meter exchange of data between: IO PAS, MI, MFI, RDANH Models (M3D_UG, ICM, ECMWF, HIROMB) Projects:

3. HRPT Raw AVHRR data HRPT Raw AVHRR data ASDIK System of Automatic Registration, Geometric and Geographic Correction of AVHRR Data ASDIK System of Automatic Registration, Geometric and Geographic Correction of AVHRR Data PRODUCTS Quicklooks & UTM maps of: SST, Brightens temperature, Albedo, cloudiness PRODUCTS Quicklooks & UTM maps of: SST, Brightens temperature, Albedo, cloudiness Data base of raw data Data base of product WWW interface The sattelite monitoring

4. Lab of Sea Dynamic Long-term changes hydrometeorological of climate Long-term changes of the Baltic Sea level Patterns of circulation in the Baltic Ecohydrodynamic model of the Baltic Sea Coastal upwellings in the Baltic Sea Sea state modelling using system identification methods Modelling of nearshore currents induced by wind waves Modelling of the interaction between currents and surface waves Investigations focused on: hydrology, waves and ecohydrodynamic

5. Correlation between the NAO index and runoff from selected sub-catchment areas into the Baltic Sea

8. Sea state modelling using system identification methods Comparison of System Identification modelling (right) and spectral wave model WAM results (left) for significant wave height (upper) and mean wave period (down) for 1100 hrs UTC on March, 7th, 2000. Methods are based on finding simple, mathematical transformations between two sets of variables (e.g. wind field and wave characteristics).

9. Modelling of nearshore currents induced by wind waves Example of the longshore current model results (upper) along multi- bar bottom crossection (down). Incoming deep wave water parameters: H o = 0.8m, T o = 6s, θ o = 65 o Significant influence on the coastal zone circulation has a wave breaking. Energy, which is dissipated in this process, causes coastal wave-driven currents. Analytical and numerical models of coastal zone circulation are based on radiation stress concept.

10. Operational System for Coastal Waters of Gdańsk Region Hydrodynamic model M3D Meteorological forecasts UMPL Model ICM ProDeMO ecosystem model Network of sea level river discharges chemical and biological stations Remote Sensing Monitoring Observations and hydrological forecasts IMWM Operational observations BOOS

13. Ecohydrodynamic model P rocesses included in the ProDeMo: 1) nutrient uptake by phytoplankton, 2) phytoplankton grazing by zooplankton, 3) phytoplankton respiration, 4) phytoplankton decay, 5) sedimentation, 6) nutrients release from sediment, 7) atmospheric deposition, 8) denitrification, 9) mineralisation, 10) zooplankton respiration, 11) sedimentation of phosphorus adsorbed on particles, 12) detritus sedimentation, 13) zooplankton decay 14) nitrogen fixation 15) nutrient deposition. influenced the dissolved oxygen: 16) reaeration, 17) flux to atmosphere due to the over saturated conditions, 18) zooplankton respiration, 19) phytoplankton respiration, 20) assimilation, 21) mineralisation, 22) nitrification, 23 ) denitrification

14. Validation of the ProDeMo model

15. Spatial distribution of the nutrients – June 1999

16. The impact of the Vistula river on the coastal water of the Gulf of Gdansk Scenarios analysis by ecohydrodynamic model The lowest biological productivity has been obtained for Deep green scenario - 7.5 % less than in the reference year 2002. Due to reduction of phosphorus loads from 40.9 % for the policy target low to 45.5 % for Deep green scenario and nitrogen loads less than 10%, the phosphorus becomes a limiting nutrient in the Gulf of Gdansk in the analyzed scenarios.

17. stability surface

18. spring stability autumn