316 research outputs found
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
Computer-aided diagnosis of emphysema in COPD patients: neural-network-based analysis of lung shape in digital chest radiographs.
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
Drift simulation of MH370 debris using superensemble techniques
On 7 March 2014 (UTC), Malaysia Airlines flight 370 vanished without a trace.
The aircraft is believed to have crashed in the southern Indian Ocean, but
despite extensive search operations the location of the wreckage is still
unknown. The first tangible evidence of the accident was discovered almost
17 months after the disappearance. On 29 July 2015, a small piece of the right
wing of the aircraft was found washed up on the island of RĂŠunion,
approximately 4000âŻkm from the assumed crash site. Since then a number of
other parts have been found in Mozambique, South Africa and on Rodrigues Island.
This paper presents a numerical simulation using high-resolution
oceanographic and meteorological data to predict the movement of floating
debris from the accident. Multiple model realisations are used with different
starting locations and wind drag parameters. The model realisations are
combined into a superensemble, adjusting the model weights to best represent
the discovered debris. The superensemble is then used to predict the
distribution of marine debris at various moments in time. This approach can
be easily generalised to other drift simulations where observations are
available to constrain unknown input parameters.
The distribution at the time of the accident shows that the discovered debris
most likely originated from the wide search area between 28Â and
35° S. This partially overlaps with the current underwater search
area, but extends further towards the north. Results at later times show that
the most probable locations to discover washed-up debris are along the
African east coast, especially in the area around Madagascar. The debris
remaining at sea in 2016 is spread out over a wide area and its distribution
changes only slowly
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 allâoptical platform complemented by integrated, newly developed software to monitor and control electrical activity in intact mouse hearts. The system combined a wideâfield mesoscope with a digital projector for optogenetic activation. Cardiac functionality could be manipulated either in freeârun mode with submillisecond temporal resolution or in a closedâloop fashion: a tailored hardware and software platform allowed realâtime 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. Realâtime intraventricular manipulation of the propagating electrical wavefront was also demonstrated, opening the prospect for realâtime resynchronization therapy and cardiac defibrillation. Furthermore, the closedâloop approach was applied to simulate a reâentrant 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 proofâofâconcept that a realâtime 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
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