International Conference and Young Scientists School on Computational Information Technologies for Environmental Sciences: “CITES-2005” Novosibirsk, Russia, March 13-23, 2005 Atmosphere-Sea Hydrodynamic-Ecosystem model study in the sea Rein Tamsalu (University of Tartu)

Introduction Today the environmental science are very much coupled with everyday life. Management policies need answer to concrete questions concerning the response of nature to both natural and manmade changes in enviromental forcing factors and loding. Numerical Hydro-Ecological modelling is an important tool for a better undrstanding of relations between the processes, and for forecasting these responses.

Atm.-Sea-Hydro-ecological forecasting modelling The goal of our activities is to answer to concrete questions concerning the response of nature to both natural and man-made changes in marine environment. *

Concrete Questions The influence of the Port of Tallinn reconstruction to the Muuga Bay marine environment

The influence of the Port of Tallinn reconstruction to the Muuga Bay marine environment Baltic Sea  =3’  =6’Gulf of Finland  =1’  =2’ Talsingi  =0.25’  =0.5’ Gulf of Muuga  =0.05’  =0.1’

Atm.-Hydro-Ecological forecasting modelling In the Atmosphere-Sea-Hydro-Ecological modelling system are coupled several sub-models: *

Atm.-Sea-Hydro-Ecological Models System

Meso-Scale Atmosph. Model TU-EMHI model ETA model is based on the reference HIRLAM model, ETB is the non-hydrostatic version. A pre-operational version of nonhydrostatic HIRLAM is used at the Estonian Meteorological Hydrological Institute (EMHI) to test the non-hydrostatic kernel of the model. Two modelling domains, as illustrated in Figure 1, are in use. Grid size of the larger domain ETA is 11km and the smaller domain ETB 3km. As the limited area models require boundary fields from larger models, the ETA model is nested to the FMI operational HIRLAM and ETB to the ETA.

Meso- Scale Atmospheric Model

Marine Circulation Models There are many different models barotropic baroclinic hydrostatic nonhydrostatic

Measured Temperaure Vertical Stucture in the Muuga Bay

Velocity Measurements In Muuga Bay Recording Doppler Current Profiler RDCP 600 ( Aandera Instruments AS, Bergen, Norway.)

Marine Circulation Model It is clear that we need Baroclinic Nonhydrostatic Circulation Model

Marine Circulation Model The governing equations of the circulation model are: Momentum equation for velocity vector U (u,v,w) Continuity equation for incompressible fluid Transport-diffusion equations for: Salinity S Temperature T State equation for buoyancy b=f(T,S) Two-equation turbulent model for Kinetic energy k and generic length scale quantity  or  sea level fluctuation , hydrostatic pressure p* and nonhydrostatic pressure p’ Pressure components are calculated

Wind wave calculation Surface wind waves are an integrated effect, in space and time, of driving wind fields. The wind wave model computes the two-dimensional wave action spectra through integration of the transport equation, where the right hand side consists of several terms describing different evolution mechanisms, such as energy input from wind ; the non-linear transfer of energy through the spectrum ; different kinds of dissipation mechanisms. Interactive atmospheric input term is used in the Miles’ form. In this model the so-called narrow-directional approximation is used. This approximation is based on well-known fact that wind waves have a narrow angular spreading function of spectra. The latter circumstance plays a key role in parameterization of nonlinear term. *

Size-Dependent Pankton Community Model Size- dependent plankton community food web is formed by  autotrophs (A i ) i=1,2,…,N P  heterotrophs (H i ) i=1,2,…,N P  bacterioplankton (B ) This plankton community forms the N P triplet stucture. Size- dependent plankton community food web is formed by  autotrophs (A i ) i=1,2,…,N P  heterotrophs (H i ) i=1,2,…,N P  bacterioplankton (B ) This plankton community forms the N P triplet stucture. Zooflag. Microzoopl. DIP DIN DIC DIP+DOP DIN+DON DOC Picophyto. Bacteriopl. ESD (  m) I Phytoflag. Nanozoopl. II Nanophyto. III Netphyto. Mesozoopl. IV – 1250

Growth reactions There are two energy flows to the plankton community The first one is the uptake of dissolved inorganic nutrients by autotrophy and it is directed from the autotrophy toward heterotrophy trough grazing. The other is the uptake of dissolved organic and inorganic nutrients by bacterioplankton and it is directed from bacterioplankton towards heterotrophy trough predation. |

Loss reactions Energy is lost through autotrophy exudation, mortality and respiration heterotrophy excretion, mortality and respiration bacterioplankton excretion and respiration detritus decay |

Different grid resolutions Baltic SeaGulf of Finland Talsinki area Muuga Bay open boundary I * 3.0 nm II * 1.0 nm III- ¼ * ¼ nm IV- 1/20 * 1/20 nm

Horizontal velocity on the surface layer Muuga Bay

HORIZONTAL VELOCITY IN THE BOTTOM LAYER Muuga Bay

Velocity on the cross-section Muuga Bay

Wind Waves In TALSINKI area during SW Storm

Ecological compounds calculation Autotrophs in the beginning of May Heterotrophs in the beginning of May

Suspended Material Calculation Spawning place Reconstruction area

Oil Spill calculation Stranding of oil and shoreline interaction The following oil spill processes are modeled: Transport and deformation of an oil slick due to time and spatially varying winds and currents Diffusion and dispersion of oil on the sea surface and in the water column Evaporation of a multi-component mixture of oil Sinking of oil in water, and consequent sedimentation Formation of oil-in-water emulsion Weathering of oil, resulting in changes in density, viscosity, and water content, due to evaporation and emulsification processes Oil spreading at the sea surface due to positive buoyancy

Oil Spill calculation The probability of the oil accident consequence in the NW part of the island Saaremaa in the summer time during three months.

The influence of the Wind Waves to the Baroclinic Circulation

Surface Temperature after 30 days calculation No Wind Waves Wind Waves are included

Bottom Temperature after 30 days calculation No Wind Waves Tmax=10Tmin=6.5 Wind Waves are included Tmax=10Tmin=6.5

Temperature profile after 30 days calculation No Wind Waves Tmax=10 Tmin=6.5 Wind Waves are included Tmax=10 Tmin=6.5

Eddy Viscosity profile after 30 days calculation No Wind Waves Wind Waves are included Kmax=100cm2/s. Kmin=0.1 cm2/s.

Surface velocity after 30 days calculation No Wind Waves Wind Waves are included

Bottom Velocity after 30 days calculation No Wind Waves Wind Waves are included