1. ScicomP9 Bologna, 23 – 26 March 2004 Wind driven circulation in the Gulf of Trieste: a numerical study in stratified conditions Querin, S., Crise, A. Istituto Nazionale di Oceanografia e di Geofisica Sperimentale (OGS) Trieste (Italy)

2. OGS - Dept. Of Oceanology (OGA) ECHO group (Ecologic and Hydrodynamic Modeling) applied hydrodynamics and turbulence modeling applied hydrodynamics and turbulence modeling ecosystem modeling in open sea and coastal areas ecosystem modeling in open sea and coastal areas Short term forecasts for coastal waters environmental protection: environmental protection: coastal ecosystem monitoring and marine protected areas control coastal ecosystem monitoring and marine protected areas control Numerical studies and research activity: operational oceanography operational oceanography water quality problems: water quality problems: pollutants transport, oil spill, sewage discharge pollutants transport, oil spill, sewage discharge

3. Adricosm (ADRIatic sea integrated Coastal areaS and river basin Management system pilot project) implementation of an integrated coastal zone management system in the Adriatic Sea implementation of an integrated coastal zone management system in the Adriatic Sea predictive circulation module: prediction of coastal current variability in Near Real Time (NRT) predictive circulation module: prediction of coastal current variability in Near Real Time (NRT) river basin and wastewater management module: monitoring and modeling of a river basin and river basin and wastewater management module: monitoring and modeling of a river basin and wastewater system in a test site wastewater system in a test site shelf forecasting system for the Northern Adriatic Sea  weekly shelf forecasting system for the Northern Adriatic Sea  weekly forecasts of current dynamics forecasts of current dynamics key technical issues: key technical issues: model (one-way) hierarchical nesting model (one-way) hierarchical nesting asynchronous coupling of coastal forecasting model and river basin management model asynchronous coupling of coastal forecasting model and river basin management model prediction optimized by in situ and satellite data assimilation prediction optimized by in situ and satellite data assimilation partnerships: Italian, Slovenian, Croatian and French institutions partnerships: Italian, Slovenian, Croatian and French institutions project supported by the Italian Ministry for the Environment and project supported by the Italian Ministry for the Environment and Territory Territory companion of MFSTEP (mediterranean sea) and MERSEA projects companion of MFSTEP (mediterranean sea) and MERSEA projects

4. Our goals: studying and modeling the dynamics of the Gulf of Trieste under realistic forcings for short and medium-range forecasts studying and modeling the dynamics of the Gulf of Trieste under realistic forcings for short and medium-range forecasts model validation comparing calculated fields with buoy measurements (MAMBO buoys (OGS), NIB’s buoys) and satellite data model validation comparing calculated fields with buoy measurements (MAMBO buoys (OGS), NIB’s buoys) and satellite data embed the code into ADRICOSM structure (improved resolution: 250 m) embed the code into ADRICOSM structure (improved resolution: 250 m)

5. The Gulf of Trieste (GoT) extensionextension bathymetrybathymetry prevalent windsprevalent winds effects on Adriatic and Mediterranean seaeffects on Adriatic and Mediterranean sea

6. Main features of the dynamics in the Gulf of Trieste GoT is a ROFI (Region Of Fresh water Influence) area (Simpson, 1997) The dynamics are governed by: wind stress wind stress buoyancy fluxes buoyancy fluxes river input river input tides & seiches tides & seiches remote control remote control

7. MITgcm novel aspects: designed to study both atmospheric and oceanic phenomena designed to study both atmospheric and oceanic phenomena includes non-hydrostatic capability  small and large scale processes includes non-hydrostatic capability  small and large scale processes adopts a finite volume technique  treatment of irregular geometries using orthogonal curvilinear grids and shaved cells adopts a finite volume technique  treatment of irregular geometries using orthogonal curvilinear grids and shaved cells developed to perform efficiently on a wide variety of computational platform including MPI parallelizing directives developed to perform efficiently on a wide variety of computational platform including MPI parallelizing directives The numerical model: MITgcm Ocean General Circulation Model (Marshall et al, 1997)

8. Adjustable momentum equation Non-hydrostatic primitive equation model

9. Pressure integration Pressure due to surface elevation (2D) Hydrostatic pressure (vertical pressure gradient, 2D) Non-hydrostatic pressure (3D)

10. Bottom topography discretization: full cells full cells piece-wise constant (‘partial’) cells piece-wise constant (‘partial’) cells piece-wise linear (‘shaved’) cells piece-wise linear (‘shaved’) cells (not yet implemented) FV can accommodate any type of grid FV can accommodate any type of grid the grid defines only the control volume boundaries and need not be related to a coordinates system the grid defines only the control volume boundaries and need not be related to a coordinates system the method is conservative by construction: surface integrals which represent convective and diffusive fluxes are the same for the CVs sharing the boundary the method is conservative by construction: surface integrals which represent convective and diffusive fluxes are the same for the CVs sharing the boundary Finite volume (FV) technique full partial shaved

11. Adopted numerical schemes Pressure method Hydrostatic /non- hydrostatic Surface Variables in time Time * stepping 1Semi-implicitHydrostatic Rigid lid Co-located Adams- Bashforth (AB) 2Semi-implicitHydrostatic Free surface Co-located AB\backward implicit 3Semi-implicitHydrostatic Rigid lid or free surface Staggered(AB) 4Semi-implicit Non- hydrostatic Rigid lid or free surface Co-located(AB) 5Semi-implicitHydrostatic Non linear free surface Co-located or staggered (AB) * Horizontal: explicit quasi second order Adams Bashford Vertical: implicit backward method/Crank-Nicholson Vertical: implicit backward method/Crank-Nicholson

12. Vertical Mixing: KPP profile for ocean interior Reference: Large, W.G., McWilliams, J.C. and Doney, S.C., 1994 (Rev. Geophys., 32, 363 - 403) Processes : resolved shear instability mixing resolved shear instability mixing unresolved shear instability due to internal wave field unresolved shear instability due to internal wave field double diffusion double diffusion Parameterization of diffusivity and viscosity: parameterized in terms of gradient Richardson number constant (Peters et al., 1988; Large et al., 1994) function of double diffusion density ratio

13. Vertical Mixing: KPP profile for surface boundary layer Processes : wind driven mixing wind driven mixing surface boundary fluxes surface boundary fluxes convective instability convective instability Parameterization of diffusivity and viscosity: G : polinomial function h b : boundary layer thickness Surface boundary layer thickness: minimum depth at which bulk Richardson number exceeds the critical Richardson number Ri c =0.3 Reference: Large, W.G., McWilliams, J.C. and Doney, S.C., 1994 (Rev. Geophys., 32, 363 - 403)

14. Parameterization A h 4 ÷ 40 m 2 /s A v constant (or KPP profile)10 m 2 /s K h 4 ÷ 40 m 2 /s K v constant (or KPP profile)4 ÷ 10 m 2 /s

15. Goals: wide range of phenomena wide range of phenomena wide range of platforms wide range of platforms high computational performance high computational performanceArchitecture: core numerical code core numerical code “pluggable” packages “pluggable” packages support framework: WRAPPER (WRappable Application Parallel Programming Environment Resource) support framework: WRAPPER (WRappable Application Parallel Programming Environment Resource) Software Architecture

16. Communication primitives Domain decomposition (2D) Parallel implementation Domain decomposition (3D)

17. Speed-up: 3,5 with 4 processors 5,8 with 8 processors 9,8 with 16 processors Use of up to 16 processors with a domain decomposition characterized by 4 x 4 spatial boxes Performance Performance (IBM SP4 computer at CINECA)

18. f-plane, 250 m spatial resolution f-plane, 250 m spatial resolution 30° rotation for domain optimization 30° rotation for domain optimization integration domain: 88 x 128 x 25 integration domain: 88 x 128 x 25 25 (1 m thick) levels 25 (1 m thick) levels bathymetry: bathymetry: linear kriging interpolation linear kriging interpolation no filtering procedures no filtering procedures small manual adjustments small manual adjustments I.C.: I.C.: derived from MAMBO buoy profiles derived from MAMBO buoy profiles B.C.: B.C.: adiabatic adiabatic lateral free-sleep lateral free-sleep quadratic bottom friction quadratic bottom friction open/closed boundary conditions open/closed boundary conditions Design of the numerical experiments for the Gulf of Trieste

19. Initial conditions: MAMBO (Monitoraggio AMBientale Operativo) buoy data set Time/depth Hovmoller diagram of parameters measured by MAMBO buoy Depth dependent temperature and salinity profiles

20. Layout of numerical experiments Averaged wind regime in Trieste during the period 1991-2000 (after Stravisi)

21. Wind driven upwelling in the GoT during a Bora episode (28-29 July 2003) Wind driven upwelling in the GoT during a Bora episode (28-29 July 2003) ETA 1/6° LAM Model: 29/07/03 06.00 GMT U10m NOAA-12 AVHRR Sea Surface Temperature

22. Temperature after 3 days of bora Constant bora: 14 m/s wind stress curl = 0 Meridionally sheared bora: 14 - 7 m/s wind stress curl > 0 Vertical section

23. KPP profile - 8 days (4 Bora + 4 no wind) Constant bora Sheared bora

24. Wind driven circulation Coexistence of mixing and upwelling phenomena: a proof using a Large-Eddy Simulation 18 °C 22 °C Buoymeasurements Buoy measurements Model results

25. Results application of the model to a real case study application of the model to a real case study good qualitative match with experimental observations good qualitative match with experimental observations successful implementation on a parallel environment successful implementation on a parallel environment

26. Ongoing work nesting with larger model (active BC) nesting with larger model (active BC) ‘realistic’ wind forcing (2.5 km spatial resolution) ‘realistic’ wind forcing (2.5 km spatial resolution) Isonzo river input dynamics Isonzo river input dynamics buoyancy fluxes buoyancy fluxes Real-time oceanographic forecasts