**5. Process studies and simulations**

In this section we present an example from some of our recent and ongoing Mediterranean modeling research. It is a one dimensional (vertical) coupled hydrodynamics-ecosystem model for a typical point located in the Eastern Mediterranean Sea. The goal of this model is to investigate the fundamental biogeochemical processes and the influence of the annual cycle of vertical mixing upon them. The hydrodynamic part of the model is a one dimensional version of the Princeton Ocean Model (POM) originally described by (Blumberg & Mellor, 1987). POM is a three dimensional, time dependent model based on the primitive equations with the Boussinesq and hydrostatic approximations as described above in Section 2. It also included a free surface, which turns the continuity equation, Eq. (4), into a time dependent equation for the height of the free surface. POM contains full thermodynamics as well as the turbulence closure sub-model of (Mellor & Yamada, 1982). It is forced at the surface through the boundary conditions which specify the wind stress, heat flux components, and fresh water flux. In the vertical column version all horizontal

years scientific interest in the oceanography of the Mediterranean Sea was renewed for various reasons. As a result of intensive field campaigns, it became clear that the circulation is far more complex than originally envisioned. It is now known that the Mediterranean Sea functions as a mini-ocean with dynamical processes occurring over a broad spectrum of spatial and temporal scales ranging from the basin wide thermohaline cell, driven by deep water formation, with a time scale of tens of years to energetic mesoscale eddies varying over a period of several weeks to months (e.g., Millot, 1999; Robinson & Golnaraghi, 1994). Following the new description of the circulation that emerged from these programs, various numerical models were applied to the Mediterranean to further investigate the processes that drive the circulation. Initially, low resolution, basin wide models were used to study the climatological mean circulation of the entire Mediterranean (e.g., Roussenov et al., 1995; Zavatarelli & Mellor, 1995). Other models focused on particular process studies such as deep water formation (e.g., Wu et al., 2000) and/or the sub-basin circulation, and were used to study the response of the general circulation to interannual atmospheric variability (e.g., Korres et al., 2000). Most recently, a rather unique and fascinating phenomenon that occurred in the Eastern Mediterranean involved an abrupt shift in the source region of deep water formation from the Adriatic Sea to the Aegean Sea during the 1990's. This has been called the Eastern Mediterranean Transient (Roether et al., 2007). Several models have been used to simulate the evolution of this process (e.g., Lascaratos et al., 1999; Samuel et al., 1999) in response to changes in atmospheric forcing. As the data and research models provided new understanding of the circulation, and as observational systems and computer technology advanced, by the late 1990's it was decided to apply this new knowledge to the problem of operational ocean forecasting. An up to date review of the present

understanding of the Mediterranean circulation can be found in Brenner (2011).

experience of research in the Mediterranean.

**5. Process studies and simulations** 

In the next two sections we will present some examples of both process studies and ocean forecasting taken from some of our most recent research efforts. This represents only a small fraction of many of the ongoing investigations being conducted by many scientists around the Mediterranean. In no way is this intended to be an exhaustive survey. It is simply a small sample meant to demonstrate the state-of-the-art of applications of numerical ocean models. It is mainly out of convenience that we take examples from our own personal

In this section we present an example from some of our recent and ongoing Mediterranean modeling research. It is a one dimensional (vertical) coupled hydrodynamics-ecosystem model for a typical point located in the Eastern Mediterranean Sea. The goal of this model is to investigate the fundamental biogeochemical processes and the influence of the annual cycle of vertical mixing upon them. The hydrodynamic part of the model is a one dimensional version of the Princeton Ocean Model (POM) originally described by (Blumberg & Mellor, 1987). POM is a three dimensional, time dependent model based on the primitive equations with the Boussinesq and hydrostatic approximations as described above in Section 2. It also included a free surface, which turns the continuity equation, Eq. (4), into a time dependent equation for the height of the free surface. POM contains full thermodynamics as well as the turbulence closure sub-model of (Mellor & Yamada, 1982). It is forced at the surface through the boundary conditions which specify the wind stress, heat flux components, and fresh water flux. In the vertical column version all horizontal advection and diffusion are neglected and the focus is on the role of vertical mixing only. Complex ecosystem or biogeochemical models are young relative to hydrodynamic models and are therefore in a stage of rapid development. For this particular study we have used the Biogeochemical Flux Model (BFM) described by (Triantafyllou et al., 2003 and Vichi et al., 2003). The model simulates several classes of phytoplankton, zooplankton, the carbon cycle, and the nitrogen cycle. The specific coupling of the models and implementation for the southeastern Mediterranean Sea presented here is based on the work of Suari (2011). In terms of the hydrodynamics, the main challenge in running the one dimensional model for the eastern Mediterranean was to account for the inflow of relatively fresh Atlantic Water which prevents unrealistic increases in salinity, which would cause the model to eventually become unstable. This was solved by adding a relaxation term in which the simulated salinity profile was nudged towards monthly mean climatological profiles. The model was configured with 40 unevenly spaced layer from the surface to a depth of 600 m and was forced at the surface with a repeating annual cycle that consisted of daily mean winds and heat fluxes that were computed from the multiyear average of the data taken from the NCEP/NCAR reanalysis covering the period from 1950-2006 (Kalnay et al., 1996). The model was run for 50 years with this perpetual year forcing. The purpose of such experiments is to assess the long term behavior and stability of the system without regard to the high frequency or inter annual variability.

Fig. 1. Time series plot of: potential temperature (°C) in the upper panel and chlorophyll-a (μg L-1) in the lower panel from the last 10 years of a 50 year simulation of a one dimensional coupled hydrodynamic-ecosystem model for the eastern Mediterranean.

Numerical Modeling of the Ocean Circulation:

(Manca et al., 2004 and Yacobi et al., 1995).

**6. Ocean forecasting** 

numerical model itself.

scales and the ecosystem at the larger scales.

From Process Studies to Operational Forecasting – The Mediterranean Example 121

(e.g., Estrada et al., 1993; Yacobi et al., 1995). The simulated pattern and values of chlorophyll-a concentration are consistent with observed values for this region reported by

In this section we present another example of the powerful use and application of numerical ocean models as part of an operational forecasting system. In contrast to process studies or simulations which are designed to help us understand the particular dynamical process of interest, the goal of a forecasting system is to provide the most accurate prediction of the circulation at a particular instant in time, but within the constraint of producing the forecast in reasonably short period of time so that it considered to be useful. Clearly a 24 hour forecast that requires 24 hours of computer time has no value. A balance must therefore be reached between the acceptable level of forecast error and the time required to produce the forecast. Furthermore in a forecast system, in addition to the model itself, the specification of the initial conditions is a central consideration. Experience from numerical weather prediction has shown that during the first few days the forecast errors depend mainly on errors in the initial conditions, whereas at longer forecast lead times model errors and uncertainties have a larger impact on forecast errors. In addition to collecting data, accurate mathematical methods are necessary for interpolating the observations to the model grid while creating a minimal amount of numerical noise. This entire procedure, referred to as data assimilation (e.g., Kalnay, 2003), will not be discussed here. Our focus will be on the

The development of the Mediterranean Forecasting System, MFS, began in 1998 as a cooperative effort of nearly 30 institutions with the goal of producing a prototype operational forecasting system and to demonstrate its feasibility. The project included components of in situ and remotely sensed data collection, data assimilation and model development. The model development component was structured to include a hierarchy of nested models with increasing resolution. The overall system was driven by the coarse resolution, full Mediterranean model. At the next level, sub-basin scale models, which covered large sections of the western, central, and eastern Mediterranean with a threefold increase in resolution, were nested in the full basin model. Nesting is the procedure through which the initial conditions were interpolated to the higher resolution grid, and the time dependent lateral boundary conditions were extracted from the coarser grid model. Finally, very high resolution local models for specific regions were nested in the sub-basin models with an additional two to threefold increase in resolution. An overall description of the prototype system and its implementation can be found in (Pinardi et al., 2003). While the initial model development focused on mainly climatological simulations with the nested model, the next phase led to the pre-operational implementation of short term forecasting with all three levels of models. This system has evolved into Mediterranean Operational Ocean Network, which is perhaps one of the most advanced operational ocean forecasting systems today (MOON, 2011). It routinely provides daily forecasts for the circulation at all

One component of MOON is a high resolution local model for the southeastern continental shelf zone of the eastern Mediterranean. The model was developed initially within MFS (Brenner, 2003) and has subsequently gone through a number of improvements and refinements. The version presented here is described in detail by (Brenner et al., 2007). It is

The results presented in Fig. 1 show the potential temperature (upper panel) and the chlorophyll-a (lower panel) from the last ten years of the fifty year simulation. By this point the model has passed through the spin-up phase and produces a relatively stable repeating annual cycle. The surface temperature varies between a maximum of approximately 26°C in summer and a winter minimum of 16.6°C. The shallow surface mixed layer, in which the temperature is relatively high and uniform, is clearly visible in summer when it extends from the surface to a depth of 30 m. It is driven mainly by wind mixing, which generates enough turbulent kinetic energy to mix the water against the density gradient. By autumn the surface begins to cool and as a result the water column begins to mix vertically due to free convection, as indicated by the deepening of the green shaded contour. The free convection is driven by gravitational instability of the water column due to cooling from above. By late winter (early to mid March) the mixed layer has deepened to it maximum extent of 190 m as indicated by the uniform cyan contour extending from the surface from late February through mid March. This cycle and the values of the temperature and mixed layer depth are consistent with the observations from this region (e.g., Hecht, et al., 1988; Manca et al., 2004; Ozsoy et al., 1993).

The lower panel of Fig. 1 shows that chlorophyll-a (concentration in μM L-1), which is the proxy for phytoplankton biomass, is confined to the upper part of the water column where there is sufficient light for photosynthesis. Nutrients (mainly nitrate, phosphate, and silicate) are also necessary for the cells to function. The nutrients are injected into the upper layers from below the nutricline (begins at ~150-200 m and extends to ~ 600 m) during deep winter mixing or during wind induced upwelling events. They are rapidly depleted form the photic zone when photosynthesis commences. Chlorophyll-a in the figure exhibits a pattern that is typical for an oligotrophic sea such as the eastern Mediterranean. During spring and summer it is confined mainly to the upper 90-100 m. During the deep mixing in the latter part of winter, the phytoplankton are transported deeper by convective mixing. A combination of factors leads to reduced photosynthesis and biomass concentration during this period. Sun light is less intense and the phytoplankton spend less time in the photic zone. Also due to the deeper mixing they are distributed over a larger volume and therefore the concentration is lower as indicated by the cyan contour. The warmer colors indicate two important features on the marine ecosystem. In early spring the yellow contours show a layer of relatively high chlorophyll concentration extending from the surface to a depth of ~80 m and which lasts for 2-3 weeks. This phenomenon is referred to as the spring bloom. It occurs shortly after the end of the winter (i.e., end of net surface cooling) and the onset of net surface heating in the spring. As a result the free convective mixing ceases and the phytoplankton remain in the upper layers. At this time nutrients are abundant due to the import of high nutrient waters from the deeper layers during winter. These two factors combined with the increasing intensity of the sunlight lead to a rapid increase in photosynthesis and therefore a substantial increase in chlorophyll-a concentration. The nutrients are consumed by the photosynthetic activity of the cells. Since the nutrient source in deep water has been cut off by the cessation of free convection, the nutrients in the photic zone are rapidly depleted and the bloom ends within a few weeks. This is indicated by the transition to the green contours. Later in the summer a subsurface layer with high chlorophyll-a concentration appears at a depth of 70-90 m (yellow and orange contours). This phenomenon referred to as the deep chlorophyll maximum, DCM, is due to the complex interaction between light intensity, leakage of nutrients from the nutricline, and the density stratification. Its occurrence is quite common in the oligotrophic Mediterranean Sea (e.g., Estrada et al., 1993; Yacobi et al., 1995). The simulated pattern and values of chlorophyll-a concentration are consistent with observed values for this region reported by (Manca et al., 2004 and Yacobi et al., 1995).
