Towards a regional rapid response multi-disciplinary system for the Adriatic SeaA. RUSSO 1, N. Pinardi 2, C.J. Lozano 3, A.R. Robinson 3, E. Paschini 1

1 C.N.R. - I.R.PE.M., L.go Fiera della Pesca, Ancona, Italy Web: http://adria.irpem.an.cnr.it e-mail: russo@irpem.an.cnr.it2 C.N.R. - I.M.G.A., Via Gobetti 101, Bologna, Italy3 Dept. of Earth and Planetary Sciences, Harvard University, Cambridge, USA

2)A basic version of HOPS has been applied to two cruises carried out during spring 1993 in the western part of the Mesoadriatic Depressions, also called Pomo (italian) or Jabuka (croatian) Pits (Fig. 1). This is a transition zone between the very shallow Northern Adriatic sub-basin (average depth 35 m) and Southern Adriatic sub-basin, where open sea characteristics can be found.

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Fig. 2 Positions of the CTD stations performed during the first (left) and the second (right) cruise.

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Fig. 1 Adriatic Sea bathimetry; the red lines separates sub-basins (northern, central and southern), the square delimits the area of the experiment.

Fig. 7 Barotropic transport forecast at 2, 6, 10 and 14 days for the third simulation.

Fig. 8 Same as Fig. 7, but with atmospheric fluxes

4)The principal parameters chosen for the examined simulations were the following: •39x39 points with 2 km horizontal resolution; •20 levels in vertical (5 of which flat for resolving the mixed layed-upper thermocline, the remaining 15 in terrain following sigma co-ordinates); •time step 5 min; The model domain is open on all the sides, the boundary conditions chosen were:•Orlanski radiation (implicit) on tracers, velocity and transport streamfunction;•Spall and Robinson boundary conditions on vorticity.The model was initialised with the objectively analysed temperature, salinity and dynamic height fields; after few time steps, the model adjusted by itself. Atmospheric fluxes were computed from the 6 hours ECMWF analysis, one grid point is inside our domain.

3)The area investigated (about 80x80 km2) was sampled at nearly mesoscale resolution (Fig. 2 with detailed bathimetry), in about 3 days. The maximum depth of the area is about 250 m; the available 5’ bathimetry was not enough accurate (its maximum depth being less than 220 m), a well refined model bathimetry (Fig. 3) was determined by melding 5’ bathimetry and the CTD stations echosoundings.

8)Fig. 9 shows a complex circulation scheme in the domain, with a weak coastal current directed toward SE, a main flow following the bathimetry with an anticiclonic sense, while right in the middle of the domain there is a ciclonic circulation. In Fig. 10 it can be seen that the introduction of the atmospheric fluxes caused wide variations, and in the central and eastern part of the domain the circulation is now reverted.

Fig. 3 Model bathimetry.

5)In Fig. 4 the simulations executed are summarised. The first two runs were initialised with the first May cruise data, the only difference between the two being the atmospheric fluxes applied in the second one. The third and fourth runs were as the previous ones, but initialised with data of the second cruise.

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Fig. 4. Simulations table.

HOPSHarvard Ocean Prediction System

6)The simulations show a flow generally slow, with velocities usually less than 10 cm/s.The main characteristic common to all the simulations was the substantial barotropic behaviour of the flow in the depressions, while currents in the area closer to the coast showed a dominant baroclinic component; Fig. 5 is a typical example of this.

Fig. 5 Cross-section of temperature, density anomaly, total velocity and internal velocity (normal to the transect) along the 4th line of stations (italian coast toward left) after 13 days of integration (first simulation).

Fig. 6 Barotropic transport forecast at 2, 6, 10 and 14 days for the first simulation.

7)The first and the second simulation produced results very similar (Fig. 6 shows the evolution of barotropic transport during the first run). Instead, the absence or the presence of the atmospheric fluxes affected significantly the simulations that started from the second cruise (Fig. 7 and 8).

Fig. 9 Salinity with total velocity at 40 m depth for the 3rd simulation (day 9)

Fig. 10 Same as Fig. 9.a, but with atmospheric fluxes

Future work and perspectives. More work and studies should be carried out based on this data set. Atmospheric forcing could be improved using ECMWF reanalysis and/or meteo data from offshore platforms in the area; data of the second cruise can be assimilated; some ecosystem components could be introduced.Next step would be the use of HOPS for biogeochemical OSSEs (Observing System Simulation Experiments) and real time forecasting in an Adriatic Sea area; this will also be a test of a prediction system rapidly deployable in any area of the Adriatic Sea in occasion of emergencies or special events. Moreover, it would be a starting point for more sophisticate HOPS and nested ecosystem models. These activities could be developed in connection with the Adriatic component of MFSPP, and both systems could benefit of relevant improvements.

1)The Harvard Ocean Prediction System (HOPS) is a flexible, portable and generic interdisciplinary system for nowcasting, forecasting and simulations which can be rapidly deployed to any region of the world ocean: coastal and deep ocean and across the shelf break. Schematized on the left is shown the presently most comprehensive form, with all modules and models attached. The extreme modularity of the system facilitates efficient configuration for specific applications; configured for a particular application, the system will generally be less complex.The central idea for nowcasting and forecasting the multiscale ocean is to attempt to initialize the nowcast or forecast with the best possible estimate of the synoptic state of the system. The development of an efficient prediction system for a region thus involves the development of a forecast oriented, historical, synoptical, statistical data base. The observational network of the regional forecast system must provide real time input to nowcasts and forecasts. A mix of platforms and sensors with nested sampling is desirable to provide efficient information over a range of scales. Several data assimilation schemes are now available.The present version of HOPS has assimilated a wide variety of in-situ and remotely sensed data types. The potential for its portability is demonstrated by twenty regions of HOPS applications over more than a decade.