A5050596440- Scientific Computing and Data Management
- Distributed and Parallel Computing Systems
- Research Data Management Practices
- Climate variability and models
- Meteorological Phenomena and Simulations
- Atmospheric and Environmental Gas Dynamics
- Tropical and Extratropical Cyclones Research
- solar cell performance optimization
- Advanced Data Storage Technologies
- Innovative Approaches in Technology and Social Development
- Data Analysis with R
- Oceanographic and Atmospheric Processes
- Marine and coastal ecosystems
- Air Quality Monitoring and Forecasting
- Immigration and Intercultural Education
- Data Stream Mining Techniques
- Advanced Computational Techniques and Applications
- Data Quality and Management
- Scientific Research and Discoveries
- Time Series Analysis and Forecasting
- Methane Hydrates and Related Phenomena
CMCC Foundation - Euro-Mediterranean Center on Climate Change
2018-2024
University of Salento
2023
Cambia
2018-2023
Abstract. The distribution of data contributed to the Coupled Model Intercomparison Project Phase 6 (CMIP6) is via Earth System Grid Federation (ESGF). ESGF a network internationally distributed sites that together work as federated archive. Data records from climate modelling institutes are published and then shared around world. It anticipated CMIP6 will produce approximately 20 PB be ESGF. In addition this large volume number value-added services required interact with ESGF; for example...
Abstract. The CMIP6 project was the most expansive and ambitious Model Intercomparison Project (MIP), latest in a long history, extending back four decades. CMIP has captivated engaged broad, growing community focused on improving our climate understanding. It anchored ability to quantify attribute drivers responses of observed changes we are experiencing today. project's profound impact been achieved by combining science technology. This enabled production latest-generation simulations...
Scientific workflows and provenance are two faces of the same medal. While former addresses coordinated execution multiple tasks over a set computational resources, latter relates to historical record data from its original sources. As experiments rapidly evolve towards complex end-to-end workflows, handling at different levels granularity during entire analytics workflow lifecycle is key for managing lineage information related large-scale in flexible way as well enabling reproducibility...
The increasing volume of data in many scientific fields demands a transformative approach to management and analysis. space concept, i.e., digital ecosystem promoting sustainable FAIR use, has emerged address key challenges. This paper introduces the ENES Data Space, domain-specific implementation for climate scientists within European Open Science Cloud. integrated environment offers datasets, tools, services science applications. We present motivations, architecture, application example,...
Open Science is key to future scientific research and promotes a deep transformation in the whole process encouraging adoption of transparent collaborative approaches aimed at knowledge sharing. increasingly gaining attention current agenda worldwide. To effectively address goals, besides Access results data, it also paramount provide tools or environments support process, particular design, execution sharing reproducible experiments, including data provenance (or lineage) tracking. This...
Open Science is a vital part in the current and future research agenda worldwide. In order to meet goals, it of paramount importance fully support process, which includes also properly addressing provenance reproducibility scientific experiments. Indeed, are two key requirements for analytics workflows contexts. Handling at different levels granularity during entire experiment lifecycle becomes flexibly managing lineage information related large-scale experiments as well enabling scenarios....
Provenance and reproducibility are two key requirements for analytics workflows in Open Science contexts. Handling provenance at different levels of granularity during the entire experiment lifecycle becomes to properly flexibly managing lineage information related large-scale experiments as well enabling scenarios, which turn foster re-usability, one FAIR guiding data principles. This contribution focuses on a multi-level approach applied climate way manage more structured multifaceted way,...
The increasing volume and complexity of Earth environmental data requires an efficient, interdisciplinary collaboration between scientists providers. This can be achieved by utilising research infrastructures providing advanced e-services exploiting integration interoperability, seamless machine-to-machine exchange HPC/ cloud facilities.   In this contribution we will present a case study geodata import, analysis visualization, carried out on the ENES Data Space...
Several scientific fields, including climate science, have undergone radical changes in the last years due to increase data volumes and emergence of science Machine Learning (ML) approaches. In this context, providing fast access analytics has become paramount importance. The space concept emerged address some key challenges support communities  towards a more sustainable FAIR use data. ENES Data Space (EDS) represents domain-specific example for community developed under umbrella...
<ns3:p>This paper presents the approach adopted by EGI-ACE project for setup and delivery of Data Spaces various scientific domains. The work was implemented members EGI e-infrastructure several European Research Infrastructures in context Open Science Cloud programme. Our results are Space services that enable reuse exploitation open, big data compute intensive use cases. illustrates through two examples: (1) EMSO ERIC Portal seafloor water column research (2) ENES climate research.</ns3:p>
Abstract. The Baseline Climate Variables for Earth System Modelling (ESM-BCVs) are defined as a list of 132 variables which have high utility the evaluation and exploitation climate simulations. reflects most heavily used elements Coupled Model Intercomparison Project phase 6 (CMIP6) archive. Successive phases CMIP supported strong results in science substantial influence international policy formulation. This paper responds both to interest exploiting data standards broader range modelling...
Abstract. The distribution of data contributed to the Coupled Model Intercomparison Project Phase 6 (CMIP6) is via Earth System Grid Federation (ESGF). ESGF a network internationally distributed sites that together work as federated archive. Data records from climate modelling institutes are published on and then shared around world. It anticipated CMIP6 will produce O(20PB) be ESGF. In addition this large volume number value-added services required interact with ESGF, for example Citation...
The exponential increase in data volumes and complexities is causing a radical change the scientific discovery process several domains, including climate science. This affects different stages of lifecycle, thus posing significant management challenges terms archiving, access, analysis, visualization, sharing. space concept can support scientists' workflow simplify towards more FAIR use data.In context European Open Science Cloud (EOSC) initiative launched by Commission, ENES Data Space...
The Earth System Grid Federation (ESGF) is an international collaboration powering most global climate change research and managing the first-ever decentralized repository for handling science data, with multiple petabytes of data at dozens federated sites worldwide. It recognized as leading infrastructure management access large distributed volumes supports Coupled Model Intercomparison Project (CMIP) Coordinated Regional Climate Downscaling Experiment (CORDEX), whose protocols enable...
&lt;p&gt;Tropical cyclones (TCs) transport energy and moisture along their pathways interacting with the climate system TCs activities are expected to extend further poleward during 21&lt;sup&gt;st&lt;/sup&gt; century.&lt;/p&gt;&lt;p&gt;For this reason, it is important assess ability of state-of-the-art models in reproducing an accurate meridional distribution as well a reasonable portrait associated TCs.&lt;/p&gt;&lt;p&gt;Since high...