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  • 11
    Publication Date: 2019-12-23
    Description: A clean and healthy ocean can be achieved, restored and preserved through constant and systematic monitoring of the marine environment, which allows to understand its complex dynamics and exploit its natural recourses through a sustainable development approach. Marine monitoring is a complex and multidisciplinary activity that measures, evaluates and determines physical and biogeochemical parameters at multiple scales through a variety of sensors characterized by different accuracy. The management and long term preservation of the deriving marine data represents a societal priority which enables to assess the past and present ocean state, to predict its evolution and to understand/mitigate the impact of human activity and climate change on it.
    Description: Published
    Description: Rome
    Description: 4A. Oceanografia e clima
    Keywords: historical observations, marine data, open data, EMODnet, SeaDatNet ; marine environment monitoring
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: Extended abstract
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  • 12
    Publication Date: 2014-09-29
    Description: The EU-funded project SANGOMA - Stochastic Assimilation of the Next Generation Ocean Model Applications provides new developments in data assimilation to ensure that future operational systems can make use of state-of-the-art data-assimilation methods and related analysis tools. One task of SANGOMA is to develop a collection of common tools for data assimilation with a uniform interface so that the tools are usable from different data assimilation systems. The tool developments mainly aim at tools that support ensemble-based data assimilation applications like for the generation of perturbations, to perform transformations, to compute diagnostics, as well as further utilities. The tools are implemented in Fortran and as scripts for Matlab or Octave. The tools and their documentation are provided as free open-source programs via the project web site [http://www.data-assimilation.net]. This contribution provides an overview of the tools that are available in the latest release V1 of the SANGOMA tools as well as the plans for the next release.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Conference , notRev
    Format: application/pdf
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  • 13
    Publication Date: 2017-04-04
    Description: In the frame of the SeaDataNet project, several regional climatologies for the temperature and salinity are being developed by different groups. The data used for these climatologies are distributed by the 40 SeaDataNet data centers. Such climatologies have several uses: 1. the detection of outliers by comparison of the in situ data with the climatological fields, 2. the the optimization of locations of new observations, 3. the initialization of numerical hydrodynamic models. 4. definition of a reference state to identify anomalies and to detect long-term climatic trends Diva (Data Interpolating Variational Analysis) software is adapted to each region by taking into account the geometrical characteristics (coastlines, bathymetry) and the distribution of data (correlation length, signal-to-noise ratio, reference field). The regional climatologies treated in this work are: - JRA5: North Atlantic - JRA6: Mediterranean Sea - JRA7: Baltic Sea - JRA8: North Sea, Arctic Sea Several examples of gridded fields are presented in this work. The validation of the different products is carried out through a comparison with the last release of the widespread World Ocean Atlas 2005.
    Description: Published
    Description: Museum National d'Histoire Naturelle, Paris France
    Description: 4.6. Oceanografia operativa per la valutazione dei rischi in aree marine
    Description: open
    Keywords: Climatologies ; Seadatanet ; 03. Hydrosphere::03.01. General::03.01.05. Operational oceanography
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: Poster session
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  • 14
    Publication Date: 2021-09-06
    Description: A new global ocean temperature and salinity climatology is proposed for two time periods: a long time mean using multiple sensor data for the 1900–2017 period and a shorter time mean using only profiling float data for the 2003–2017 period. We use the historical database of World Ocean Database 2018. The estimation approach is novel as an additional quality control procedure is implemented, along with a new mapping algorithm based on Data Interpolating Variational Analysis. The new procedure, in addition to the traditional quality control approach, resulted in low sensitivity in terms of the first guess field choice. The roughness index and the root mean square of residuals are new indices applied to the selection of the free mapping parameters along with sensitivity experiments. Overall, the new estimates were consistent with previous climatologies, but several differences were found. The cause of these discrepancies is difficult to identify due to several differences in the procedures. To minimise these uncertainties, a multi-model ensemble mean is proposed as the least uncertain estimate of the global ocean temperature and salinity climatology.
    Description: SeaDataCloud Project and University of Bologna
    Description: Published
    Description: 711363
    Description: 4A. Oceanografia e clima
    Description: JCR Journal
    Keywords: global climatology ; temperature and salinity ; Hydrosphere ; Oceanography
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 15
    Publication Date: 2021-10-13
    Description: The needs of society and the emerging blue economy require access and integration of data and information for the construction of dedicated products. A “transparent and accessible ocean” is one of the key objectives of the Ocean Decade 2021–30. In this context, marine infrastructures become significant components of a global knowledge environment, enabling environmental assessment and providing the necessary data for scientifically valid actions to protect and restore ocean health, to use marine resources in a sustainable way. The data is collected, analyzed, organized, and used by people and their good use/reuse can be obtained with social practices, technological and physical agreements aimed at facilitating collaborative knowledge, decision-making, inference. The vision is a digital ocean data ecosystem made up of multiple, interoperable, and scalable components. The huge amount of data and the resulting products can drive the development of new knowledge as well as new applications and services. Predictive capabilities that derive from the digital ecosystem enable the implementation of services for real-time decision-making, multihazard warning systems, and advance marine space planning. The chapter develops following the progressive complexity and information content of products deriving from oceanic data: data cycle and data collections, data products, oceanic reanalysis. The chapter discusses the new challenges of data products and the complexity of deriving them.
    Description: Published
    Description: 197-280
    Description: 4A. Oceanografia e clima
    Keywords: 03.02. Hydrology ; 05.02. Data dissemination
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: book chapter
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  • 16
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    Copernicus Publications
    In:  EPIC3Earth System Science Data, Copernicus Publications, 15(1), pp. 225-263, ISSN: 1866-3508
    Publication Date: 2024-05-29
    Description: Satellite altimetry missions flying over the ice-covered Arctic Ocean have opened the possibility of further understanding changes in the ocean beneath the sea ice. This requires complex processing of satellite signals emerging from the sea surface in leads within the sea ice, with efforts to generate consistent Arctic-wide datasets of sea surface height ongoing. The aim of this paper is to provide and assess a novel gridded dataset of sea surface height anomaly and geostrophic velocity, which incorporates both the ice-covered and open ocean areas of the Arctic. Data from the CryoSat-2 mission in the period 2011-2020 were gridded at monthly intervals, up to 88°N, using the Data-Interpolating Variational Analysis (DIVA) method. To examine the robustness of our results, we compare our dataset to independent satellite data, mooring time series and Arctic-wide hydrographic observations. We find that our dataset is well correlated with independent satellite data at monthly timescales. Comparisons to in situ ocean observations show that our dataset provides reliable information on the variability of sea surface height and surface geostrophic currents over geographically diverse regions of the Arctic Ocean and different dynamical regimes and sea ice states. At all comparison sites we find agreement with in situ observed variability at seasonal to interannual timescales. Furthermore, we find that our geostrophic velocity fields can resolve the variability of boundary currents wider than about 50km, a result relevant for studies of Arctic Ocean circulation. Additionally, large-scale seasonal features emerge. Sea surface height exhibits a wintertime Arctic-wide maximum, with the highest amplitude over the shelves. Also, we find a basin-wide seasonal acceleration of Arctic slope currents in winter. We suggest that this dataset can be used to study not only the large-scale sea surface height and circulation, but also the regionally confined boundary currents. The dataset is available in netCDF format from PANGAEA at 10.1594/PANGAEA.931869 .
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
    Format: application/pdf
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  • 17
    Publication Date: 2024-02-07
    Description: In this paper, we outline the need for a coordinated international effort toward the building of an open-access Global Ocean Oxygen Database and ATlas (GO2DAT) complying with the FAIR principles (Findable, Accessible, Interoperable, and Reusable). GO2DAT will combine data from the coastal and open ocean, as measured by the chemical Winkler titration method or by sensors (e.g., optodes, electrodes) from Eulerian and Lagrangian platforms (e.g., ships, moorings, profiling floats, gliders, ships of opportunities, marine mammals, cabled observatories). GO2DAT will further adopt a community-agreed, fully documented metadata format and a consistent quality control (QC) procedure and quality flagging (QF) system. GO2DAT will serve to support the development of advanced data analysis and biogeochemical models for improving our mapping, understanding and forecasting capabilities for ocean O2 changes and deoxygenation trends. It will offer the opportunity to develop quality-controlled data synthesis products with unprecedented spatial (vertical and horizontal) and temporal (sub-seasonal to multi-decadal) resolution. These products will support model assessment, improvement and evaluation as well as the development of climate and ocean health indicators. They will further support the decision-making processes associated with the emerging blue economy, the conservation of marine resources and their associated ecosystem services and the development of management tools required by a diverse community of users (e.g., environmental agencies, aquaculture, and fishing sectors). A better knowledge base of the spatial and temporal variations of marine O2 will improve our understanding of the ocean O2 budget, and allow better quantification of the Earth’s carbon and heat budgets. With the ever-increasing need to protect and sustainably manage ocean services, GO2DAT will allow scientists to fully harness the increasing volumes of O2 data already delivered by the expanding global ocean observing system and enable smooth incorporation of much higher quantities of data from autonomous platforms in the open ocean and coastal areas into comprehensive data products in the years to come. This paper aims at engaging the community (e.g., scientists, data managers, policy makers, service users) toward the development of GO2DAT within the framework of the UN Global Ocean Oxygen Decade (GOOD) program recently endorsed by IOC-UNESCO. A roadmap toward GO2DAT is proposed highlighting the efforts needed (e.g., in terms of human resources).
    Type: Article , PeerReviewed
    Format: text
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