Preface "Operational oceanography in the Mediterranean Sea: the second stage of development"

The papers of this special issue overview some of the scientific results of the second phase of development of the Mediterranean Forecasting System (MFS) realised during the EU project "Mediterranean ocean Forecasting System: Toward Environmental Predictions-MFSTEP" that started 1 March 2003 and ended in June 2006. The MFS oceanographic service that is now operational in the Mediterranean Sea was developed, implemented and quality assessed during MFSTEP. MFS is composed of: a) a near real time observing system with satellite and in situ elements; b) a numerical ocean forecasting system at basin scale, assimilating all data available in real time, and a set of limited area forecasting models in different sub-regional and shelf areas; c) biochemical models for algal biomass forecasting; d) a product dissemination system. Moreover, the products of MFS are used to develop downstream services, such as oil spill drift and dispersion, sediment transport in the coastal areas and fish stock assessment that demonstrate the value of the operational service for end-users. MFSTEP contained several phases of development and realised a demonstration exercise, the so-called Targeted Operational Period-TOP that started in September 2004 and ended in March 2005. During TOP all possible observing platforms were active, the numerical models were capable to assimilate the observations and the all models were running in forecast mode, from the basin scale to the shelf areas. The deployed observing and modelling components of MFS are now part of a sustained operational oceanographic service for the Mediterranean Sea, so-called Mediterranean Operational Oceanography Network (MOON, http: //www.moon-oceanforecasting.eu)

Mediterranean ocean Forecasting System: Toward Environmental Predictions-MFSTEP Executive Summary

Objectives: The Project aims at the further development of an operational forecasting system for the Mediterranean Sea based upon three main components: a) a Real Time-RT Observing system; b) a numerical forecasting system at the basin scale and for the sub-regional/shelf areas; c) the forecast products dissemination/exploitation system. The Observing system component consists of: • a SOOP-VOS system with RT data dissemination and test of new sensors that collect multidisciplinary data; • a moored buoy network (M3A) designed to serve the RT validation of the basin scale models and the calibration of the ecosystem models; • a satellite RT data analysis system using several satellites for sea surface elevation, sea surface temperature and sea surface winds; • a high space-time resolution network of autonomous subsurface profiling floats (Array for Real-Time Geostrophic Oceanography-ARGO); • a basin scale glider autonomous vehicle experiment; The sampling strategy is continuously assessed by the Observing System Simulation Experiment (OSSE) activities and a RT data management and delayed mode archiving system has been organized

Oil spill forecasting in the Mediterranean Sea

In this work sensitivity experiments to the coupled MFS (currents) and MEDSLIK (oil spill) input parameters will be shown and results will be compared with observations. In these experiments the drift angle, the drift factor, the currents depth, the type of oil, horizontal diffusivity and the horizontal and temporal current resolution were changed

Parallel implementation of the SHYFEM (System of HydrodYnamic Finite Element Modules) model

This paper presents the message passing interface (MPI)-based parallelization of the three-dimensional hydrodynamic model SHYFEM (System of HydrodYnamic Finite Element Modules). The original sequential version of the code was parallelized in order to reduce the execution time of high-resolution configurations using state-of-the-art high-performance computing (HPC) systems. A distributed memory approach was used, based on the MPI. Optimized numerical libraries were used to partition the unstructured grid (with a focus on load balancing) and to solve the sparse linear system of equations in parallel in the case of semi-to-fully implicit time stepping. The parallel implementation of the model was validated by comparing the outputs with those obtained from the sequential version. The performance assessment demonstrates a good level of scalability with a realistic configuration used as benchmark

Real-time optical manipulation of cardiac conduction in intact hearts

Optogenetics has provided new insights in cardiovascular research, leading to new methods for cardiac pacing, resynchronization therapy and cardioversion. Although these interventions have clearly demonstrated the feasibility of cardiac manipulation, current optical stimulation strategies do not take into account cardiac wave dynamics in real time. Here, we developed an all‐optical platform complemented by integrated, newly developed software to monitor and control electrical activity in intact mouse hearts. The system combined a wide‐field mesoscope with a digital projector for optogenetic activation. Cardiac functionality could be manipulated either in free‐run mode with submillisecond temporal resolution or in a closed‐loop fashion: a tailored hardware and software platform allowed real‐time intervention capable of reacting within 2 ms. The methodology was applied to restore normal electrical activity after atrioventricular block, by triggering the ventricle in response to optically mapped atrial activity with appropriate timing. Real‐time intraventricular manipulation of the propagating electrical wavefront was also demonstrated, opening the prospect for real‐time resynchronization therapy and cardiac defibrillation. Furthermore, the closed‐loop approach was applied to simulate a re‐entrant circuit across the ventricle demonstrating the capability of our system to manipulate heart conduction with high versatility even in arrhythmogenic conditions. The development of this innovative optical methodology provides the first proof‐of‐concept that a real‐time optically based stimulation can control cardiac rhythm in normal and abnormal conditions, promising a new approach for the investigation of the (patho)physiology of the heart

Environmental variables and machine learning models to predict cetacean abundance in the Central-eastern Mediterranean Sea

: Although the Mediterranean Sea is a crucial hotspot in marine biodiversity, it has been threatened by numerous anthropogenic pressures. As flagship species, Cetaceans are exposed to those anthropogenic impacts and global changes. Assessing their conservation status becomes strategic to set effective management plans. The aim of this paper is to understand the habitat requirements of cetaceans, exploiting the advantages of a machine-learning framework. To this end, 28 physical and biogeochemical variables were identified as environmental predictors related to the abundance of three odontocete species in the Northern Ionian Sea (Central-eastern Mediterranean Sea). In fact, habitat models were built using sighting data collected for striped dolphins Stenella coeruleoalba, common bottlenose dolphins Tursiops truncatus, and Risso's dolphins Grampus griseus between July 2009 and October 2021. Random Forest was a suitable machine learning algorithm for the cetacean abundance estimation. Nitrate, phytoplankton carbon biomass, temperature, and salinity were the most common influential predictors, followed by latitude, 3D-chlorophyll and density. The habitat models proposed here were validated using sighting data acquired during 2022 in the study area, confirming the good performance of the strategy. This study provides valuable information to support management decisions and conservation measures in the EU marine spatial planning context

Operational oceanography in support to indicator reporting

Operational Oceanography (OO) has now emerged to a stage that allows the design, development and execution of marine core services tailored to user requirements. As such it is also feasible to provide routine production of environmental and climate indicators. Indicators are synthetic indices of environmental changes at various temporal and spatial scales. In this paper we outline the possible contribution and strengthening of existing indicator reporting based on OO products followed by a discussion of the relevance of such improved reporting for marine environmental policy implementation and regulation. In particular, it capitalizes on the main achievements of the Marine Environment and Security of the European Area (MERSEA) project, the outcome of a European Marine Monitoring and Assessment (EMMA) workshop on the connection between operational oceanography and the European Marine Strategy (EMS) Directive and the regular European Environmental Agency (EEA) assessment reports

Hindcast of oil-spill pollution during the Lebanon crisis in the Eastern Mediterranean, July–August 2006

MOON (Mediterranean Operational Oceanography Network http://www.moon-oceanforecasting.eu) pro- vides near-real-time information on oil-spill detection (ocean color and SAR) and predictions [ocean fore- casts (MFS and CYCOFOS) and oil-spill predictions (MEDSLIK)]. We employ this system to study the Lebanese oil-pollution crisis in summer 2006 and thus to assist regional and local decision makers in Europe, regionally and locally. The MEDSLIK oil-spill predictions obtained using CYCOFOS high-resolution ocean fields are compared with those obtained using lower-resolution MFS hydrodynamics, and both are validated against satellite observations. The predicted beached oil distributions along the Lebanese and Syrian coasts are compared with in situ observations. The oil-spill predictions are able to simulate the northward movement of the oil spill, with the CYCO- FOS predictions being in better agreement with satellite observations. Among the free MEDSLIK param- eters tested in the sensitivity experiments, the drift factor appears to be the most relevant to improve the quality of the results.The paper was produced using the INGV MFS forecasting-sys- tem product and the OC-UCY CYCOFOS forecasting-system prod- ucts. The MODIS satellite data products were processed at the GOS-CNR-ISAC Rome laboratory using the SeaDAS software devel- oped by NASA GSFC, Greenbelt, Maryland, the HDFLook software developed by The Laboratoire d’Optique Atmosphérique, Univer- sity of Lille, France, and the MS2GT tool box developed by the Uni- versity of Colorado. Procedures for oil-spill detection were developed in the ENVI environment. Processed ENVISAT-ASAR data were made available by Telespazio and JRC. Part of this work was carried out with the support of the PRIMI project (ASI Contract No. I/094/06/0) financed by the Italian Space Agency (ASI).In press4.6. Oceanografia operativa per la valutazione dei rischi in aree marineJCR Journalreserve