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Research data keyboard_double_arrow_right Dataset 2023Publisher:World Data Center for Climate (WDCC) at DKRZ Authors: Lovato, Tomas; Peano, Daniele; Butenschön, Momme;Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.ScenarioMIP.CMCC.CMCC-ESM2.ssp126' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The CMCC-ESM2 climate model, released in 2017, includes the following components: aerosol: MAM3, atmos: CAM5.3 (1deg; 288 x 192 longitude/latitude; 30 levels; top at ~2 hPa), land: CLM4.5 (BGC mode), ocean: NEMO3.6 (ORCA1 tripolar primarly 1 deg lat/lon with meridional refinement down to 1/3 degree in the tropics; 362 x 292 longitude/latitude; 50 vertical levels; top grid cell 0-1 m), ocnBgchem: BFM5.2, seaIce: CICE4.0. The model was run by the Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici, Lecce 73100, Italy (CMCC) in native nominal resolutions: aerosol: 100 km, atmos: 100 km, land: 100 km, ocean: 100 km, ocnBgchem: 100 km, seaIce: 100 km.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2021Publisher:figshare Tran, Fanny; Holland, Jonathan E.; Quesada, Nora; Young, Mark; Bienkowski, Damian; Savvas, Dimitrios; Schubert, Andrea; Ntatsi, Georgia; White, Philip J.; Begg, Graham S.; Iannetta, Pietro P. M.;Additional file 3: Relevant reviews (excel file).
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2023Publisher:World Data Center for Climate (WDCC) at DKRZ Authors: Lovato, Tomas; Peano, Daniele;Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.CMIP.CMCC.CMCC-CM2-SR5.piControl' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The CMCC-CM2-SR5 climate model, released in 2016, includes the following components: aerosol: MAM3, atmos: CAM5.3 (1deg; 288 x 192 longitude/latitude; 30 levels; top at ~2 hPa), land: CLM4.5 (BGC mode), ocean: NEMO3.6 (ORCA1 tripolar primarly 1 deg lat/lon with meridional refinement down to 1/3 degree in the tropics; 362 x 292 longitude/latitude; 50 vertical levels; top grid cell 0-1 m), seaIce: CICE4.0. The model was run by the Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici, Lecce 73100, Italy (CMCC) in native nominal resolutions: aerosol: 100 km, atmos: 100 km, land: 100 km, ocean: 100 km, seaIce: 100 km.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2023Publisher:World Data Center for Climate (WDCC) at DKRZ Authors: Scoccimarro, Enrico; Bellucci, Alessio; Peano, Daniele;Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.HighResMIP.CMCC.CMCC-CM2-VHR4' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The CMCC-CM2-VHR4 climate model, released in 2017, includes the following components: aerosol: prescribed MACv2-SP, atmos: CAM4 (1/4deg; 1152 x 768 longitude/latitude; 26 levels; top at ~2 hPa), land: CLM4.5 (SP mode), ocean: NEMO3.6 (ORCA0.25 1/4 deg from the Equator degrading at the poles; 1442 x 1051 longitude/latitude; 50 vertical levels; top grid cell 0-1 m), seaIce: CICE4.0. The model was run by the Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici, Lecce 73100, Italy (CMCC) in native nominal resolutions: aerosol: 25 km, atmos: 25 km, land: 25 km, ocean: 25 km, seaIce: 25 km.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2023Publisher:World Data Center for Climate (WDCC) at DKRZ Authors: Lovato, Tomas; Peano, Daniele;Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.ScenarioMIP.CMCC.CMCC-CM2-SR5.ssp370' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The CMCC-CM2-SR5 climate model, released in 2016, includes the following components: aerosol: MAM3, atmos: CAM5.3 (1deg; 288 x 192 longitude/latitude; 30 levels; top at ~2 hPa), land: CLM4.5 (BGC mode), ocean: NEMO3.6 (ORCA1 tripolar primarly 1 deg lat/lon with meridional refinement down to 1/3 degree in the tropics; 362 x 292 longitude/latitude; 50 vertical levels; top grid cell 0-1 m), seaIce: CICE4.0. The model was run by the Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici, Lecce 73100, Italy (CMCC) in native nominal resolutions: aerosol: 100 km, atmos: 100 km, land: 100 km, ocean: 100 km, seaIce: 100 km.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2020Publisher:IEEE DataPort Leva, Sonia; Nespoli, Alfredo ; Pretto, Silvia; Mussetta, Marco; Ogliari, Emanuele;This dataset includes PV power production measured on the SolarTech Lab, Politecnico di Milano, Italy. Data are freely available for scientific research purpose and further data validation.In particular, the dataset is composed of the following variables and specifics, with a time resolution of 1 minute:Timestamp: column with time recordings; the data format is “dd-MM-yyyy hh:mm:ss”, with the time always expressed in Central European Time (CET).Pm: power recordings from the PV module (W); module tilt: 30°.Tair: ambient temperature (°C) measured by the weather station described in SolarTech Lab website (http://www.solartech.polimi.it/instrumentation/).GHI: measured Global Horizontal Irradiance (W/m2).GPOA: global irradiance measured on the plane of array (30°).Ws: measured wind speed (m/s).Wd: measured wind direction (°), assuming 0° east, positive south.It is worth noticing that this dataset includes original measurements, i.e. these raw data can be used for any additional post-processing, validation and further research. When a value is missing in the original measurements recording, a “NaN” is reported.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2022Embargo end date: 11 Apr 2022Publisher:Harvard Dataverse Cammarano, Davide; Jamshidi, Sajad; Hoogenboom, Gerrit; C. Ruane, Alex; Niyogi, Dev; Ronga, Domenico;doi: 10.7910/dvn/sndp5w
The bulk of global tomato production is concentrated in a small number of regions where climate change will have an outsized influence on future supplies for tomato products. We simulated the tomato production in the three main producing countries (the United States, Italy, and China) under future climate scenarios. The Decision Support System for Agrotechnology Transfer (DSSAT) was used for the simulations under three CIMIP6 climate scenarios (SSP1-2.6, SSP3-7.0, and SSP5-8.5) based on five global circulation models. The DSSAT outputs were post-processed in a python environment to visualize the impact of climate change on future production. In this repository, we share the outcome of the DSSAT simulations, as well as the scripts and tables used to analyze the outputs and generate the Figures.
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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2012 Ireland, ItalyPublisher:Inter-Research Science Center Publicly fundedDonnelly, A.; Kelleher, C. T.; O'Neill, B. F.; Diskin, E.; Pletsers, A.; Proctor, H.; Stirnemann, R.; O'Halloran, J.; Penuelas, J.; Hodkinson, T. R.; Sparks, T. H.; Caffarra, Amelia;doi: 10.3354/cr01102
handle: 10449/21343 , 2262/73272
There are numerous reports in the literature of advancing trends in phenophases of plants, insects and birds attributed to rising temperature resulting from human-driven climate warming. One mechanism that enables a population to respond rapidly to changes in the environ- ment is termed phenotypic plasticity. This plasticity grants a degree of flexibility to enable the tim- ing of developmental stages to coincide with resource availability. If, however, environmental con- ditions exceed the plastic limits of an organism, evolutionary change may be necessary in order to ensure continued survival of their populations. We review evidence for phenotypic plasticity and genetic adaptation in phenological characteristics associated with climatic warming. We focus this review on examples from trees, insects and birds. We found many reports of direct observations of phenotypic plasticity but fewer studies providing conclusive evidence of genetic adaptation. Evi- dence for changes in genes linked with adaptive traits associated with a warming climate was stronger in insects, that have a relatively short life-cycle, than in longer-lived birds and trees. Fur- ther research is required to identify both appropriate long-term data sets for a range of species and traits and suitable analytical methods, which will permit the study of the complex interaction between phenotypic plasticity and genetic adaptation of organisms and their populations in response to climatic change.
Fondazione Edmund Ma... arrow_drop_down Fondazione Edmund Mach: IRIS-OpenPubArticle . 2012Full-Text: http://hdl.handle.net/10449/21343Data sources: Bielefeld Academic Search Engine (BASE)The University of Dublin, Trinity College: TARA (Trinity's Access to Research Archive)Article . 2012Full-Text: http://hdl.handle.net/2262/73272Data sources: Bielefeld Academic Search Engine (BASE)Trinity's Access to Research ArchiveArticle . 2012 . Peer-reviewedData sources: Trinity's Access to Research Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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more_vert Fondazione Edmund Ma... arrow_drop_down Fondazione Edmund Mach: IRIS-OpenPubArticle . 2012Full-Text: http://hdl.handle.net/10449/21343Data sources: Bielefeld Academic Search Engine (BASE)The University of Dublin, Trinity College: TARA (Trinity's Access to Research Archive)Article . 2012Full-Text: http://hdl.handle.net/2262/73272Data sources: Bielefeld Academic Search Engine (BASE)Trinity's Access to Research ArchiveArticle . 2012 . Peer-reviewedData sources: Trinity's Access to Research Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2017Publisher:Zenodo Authors: Garegnani, Giulia; Scaramuzzino, Chiara;Data show the total energy potential of wind in the eu28. raster data with the power density of wind at 50, 100 and 200 m are presented and then have been aggregated at nuts3 level in grass gis, through the corine land cover and by excluding urban areas, bird connectivity corridors, mountain peaks over 2500m and protected areas from the natura 2000 framework. in the dataset we report the median value at nuts3 level as indicator of the wind potential.
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visibility 38visibility views 38 download downloads 7 Powered bymore_vert ZENODO arrow_drop_down add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2022Embargo end date: 24 Dec 2021 United Kingdom, SwitzerlandPublisher:Elsevier BV Authors: Argyroudis, Sotirios A; Aristotels Mitoulis, Stergios; Chatzi, Eleni W; Baker, Jack W; +8 AuthorsArgyroudis, Sotirios A; Aristotels Mitoulis, Stergios; Chatzi, Eleni W; Baker, Jack W; Brilakis, Ioannis; Gkoumas, Konstantinos; Vousdoukas, Michalis; Hynes, William; Carluccio, Savina; Keou, Oceane; Frangopol, Dan M; Linkov, Igor;Delivering infrastructure, resilient to multiple natural hazards and climate change, is fundamental to continued economic prosperity and social coherence. This is a strategic priority of the United Nations Sustainable Development Goals (SDGs), the World Bank, the Organisation for Economic Co-operation and Development (OECD), public policies and global initiatives. The operability and functionality of critical infrastructure are continuously challenged by multiple stressors, increasing demands and ageing, whilst their interconnectedness and dependencies pose additional challenges. Emerging and disruptive digital technologies have the potential to enhance climate resilience of critical infrastructure, by providing rapid and accurate assessment of asset condition and support decision-making and adaptation. In this pursuit, it is imperative to adopt multidisciplinary roadmaps and deploy computational, communication and other digital technologies, tools and monitoring systems. Nevertheless, the potential of these emerging technologies remains largely unexploited, as there is a lack of consensus, integrated approaches and legislation in support of their use. In this perspective paper, we discuss the main challenges and enablers of climate-resilient infrastructure and we identify how available roadmaps, tools and emerging digital technologies, e.g. Internet of Things, digital twins, point clouds, Artificial Intelligence, Building Information Modelling, can be placed at the service of a safer world. We show how digital technologies will lead to infrastructure of enhanced resilience, by delivering efficient and reliable decision-making, in a proactive and/or reactive manner, prior, during and after hazard occurrences. In this respect, we discuss how emerging technologies significantly reduce the uncertainties in all phases of infrastructure resilience evaluations. Thus, building climate-resilient infrastructure, aided by digital technologies, will underpin critical activities globally, contribute to Net Zero target and hence safeguard our societies and economies. To achieve this we set an agenda, which is aligned with the relevant SDGs and highlights the urgent need to deliver holistic and inclusive standards and legislation, supported by coordinated alliances, to fully utilise emerging digital technologies.
Brunel University Lo... arrow_drop_down Brunel University London: Brunel University Research Archive (BURA)Article . 2021License: CC BYFull-Text: https://bura.brunel.ac.uk/handle/2438/23764Data sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 103 citations 103 popularity Top 1% influence Top 10% impulse Top 1% Powered by BIP!
visibility 37visibility views 37 download downloads 50 Powered bymore_vert Brunel University Lo... arrow_drop_down Brunel University London: Brunel University Research Archive (BURA)Article . 2021License: CC BYFull-Text: https://bura.brunel.ac.uk/handle/2438/23764Data sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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Research data keyboard_double_arrow_right Dataset 2023Publisher:World Data Center for Climate (WDCC) at DKRZ Authors: Lovato, Tomas; Peano, Daniele; Butenschön, Momme;Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.ScenarioMIP.CMCC.CMCC-ESM2.ssp126' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The CMCC-ESM2 climate model, released in 2017, includes the following components: aerosol: MAM3, atmos: CAM5.3 (1deg; 288 x 192 longitude/latitude; 30 levels; top at ~2 hPa), land: CLM4.5 (BGC mode), ocean: NEMO3.6 (ORCA1 tripolar primarly 1 deg lat/lon with meridional refinement down to 1/3 degree in the tropics; 362 x 292 longitude/latitude; 50 vertical levels; top grid cell 0-1 m), ocnBgchem: BFM5.2, seaIce: CICE4.0. The model was run by the Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici, Lecce 73100, Italy (CMCC) in native nominal resolutions: aerosol: 100 km, atmos: 100 km, land: 100 km, ocean: 100 km, ocnBgchem: 100 km, seaIce: 100 km.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2021Publisher:figshare Tran, Fanny; Holland, Jonathan E.; Quesada, Nora; Young, Mark; Bienkowski, Damian; Savvas, Dimitrios; Schubert, Andrea; Ntatsi, Georgia; White, Philip J.; Begg, Graham S.; Iannetta, Pietro P. M.;Additional file 3: Relevant reviews (excel file).
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2023Publisher:World Data Center for Climate (WDCC) at DKRZ Authors: Lovato, Tomas; Peano, Daniele;Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.CMIP.CMCC.CMCC-CM2-SR5.piControl' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The CMCC-CM2-SR5 climate model, released in 2016, includes the following components: aerosol: MAM3, atmos: CAM5.3 (1deg; 288 x 192 longitude/latitude; 30 levels; top at ~2 hPa), land: CLM4.5 (BGC mode), ocean: NEMO3.6 (ORCA1 tripolar primarly 1 deg lat/lon with meridional refinement down to 1/3 degree in the tropics; 362 x 292 longitude/latitude; 50 vertical levels; top grid cell 0-1 m), seaIce: CICE4.0. The model was run by the Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici, Lecce 73100, Italy (CMCC) in native nominal resolutions: aerosol: 100 km, atmos: 100 km, land: 100 km, ocean: 100 km, seaIce: 100 km.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2023Publisher:World Data Center for Climate (WDCC) at DKRZ Authors: Scoccimarro, Enrico; Bellucci, Alessio; Peano, Daniele;Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.HighResMIP.CMCC.CMCC-CM2-VHR4' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The CMCC-CM2-VHR4 climate model, released in 2017, includes the following components: aerosol: prescribed MACv2-SP, atmos: CAM4 (1/4deg; 1152 x 768 longitude/latitude; 26 levels; top at ~2 hPa), land: CLM4.5 (SP mode), ocean: NEMO3.6 (ORCA0.25 1/4 deg from the Equator degrading at the poles; 1442 x 1051 longitude/latitude; 50 vertical levels; top grid cell 0-1 m), seaIce: CICE4.0. The model was run by the Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici, Lecce 73100, Italy (CMCC) in native nominal resolutions: aerosol: 25 km, atmos: 25 km, land: 25 km, ocean: 25 km, seaIce: 25 km.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2023Publisher:World Data Center for Climate (WDCC) at DKRZ Authors: Lovato, Tomas; Peano, Daniele;Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.ScenarioMIP.CMCC.CMCC-CM2-SR5.ssp370' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The CMCC-CM2-SR5 climate model, released in 2016, includes the following components: aerosol: MAM3, atmos: CAM5.3 (1deg; 288 x 192 longitude/latitude; 30 levels; top at ~2 hPa), land: CLM4.5 (BGC mode), ocean: NEMO3.6 (ORCA1 tripolar primarly 1 deg lat/lon with meridional refinement down to 1/3 degree in the tropics; 362 x 292 longitude/latitude; 50 vertical levels; top grid cell 0-1 m), seaIce: CICE4.0. The model was run by the Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici, Lecce 73100, Italy (CMCC) in native nominal resolutions: aerosol: 100 km, atmos: 100 km, land: 100 km, ocean: 100 km, seaIce: 100 km.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2020Publisher:IEEE DataPort Leva, Sonia; Nespoli, Alfredo ; Pretto, Silvia; Mussetta, Marco; Ogliari, Emanuele;This dataset includes PV power production measured on the SolarTech Lab, Politecnico di Milano, Italy. Data are freely available for scientific research purpose and further data validation.In particular, the dataset is composed of the following variables and specifics, with a time resolution of 1 minute:Timestamp: column with time recordings; the data format is “dd-MM-yyyy hh:mm:ss”, with the time always expressed in Central European Time (CET).Pm: power recordings from the PV module (W); module tilt: 30°.Tair: ambient temperature (°C) measured by the weather station described in SolarTech Lab website (http://www.solartech.polimi.it/instrumentation/).GHI: measured Global Horizontal Irradiance (W/m2).GPOA: global irradiance measured on the plane of array (30°).Ws: measured wind speed (m/s).Wd: measured wind direction (°), assuming 0° east, positive south.It is worth noticing that this dataset includes original measurements, i.e. these raw data can be used for any additional post-processing, validation and further research. When a value is missing in the original measurements recording, a “NaN” is reported.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2022Embargo end date: 11 Apr 2022Publisher:Harvard Dataverse Cammarano, Davide; Jamshidi, Sajad; Hoogenboom, Gerrit; C. Ruane, Alex; Niyogi, Dev; Ronga, Domenico;doi: 10.7910/dvn/sndp5w
The bulk of global tomato production is concentrated in a small number of regions where climate change will have an outsized influence on future supplies for tomato products. We simulated the tomato production in the three main producing countries (the United States, Italy, and China) under future climate scenarios. The Decision Support System for Agrotechnology Transfer (DSSAT) was used for the simulations under three CIMIP6 climate scenarios (SSP1-2.6, SSP3-7.0, and SSP5-8.5) based on five global circulation models. The DSSAT outputs were post-processed in a python environment to visualize the impact of climate change on future production. In this repository, we share the outcome of the DSSAT simulations, as well as the scripts and tables used to analyze the outputs and generate the Figures.
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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2012 Ireland, ItalyPublisher:Inter-Research Science Center Publicly fundedDonnelly, A.; Kelleher, C. T.; O'Neill, B. F.; Diskin, E.; Pletsers, A.; Proctor, H.; Stirnemann, R.; O'Halloran, J.; Penuelas, J.; Hodkinson, T. R.; Sparks, T. H.; Caffarra, Amelia;doi: 10.3354/cr01102
handle: 10449/21343 , 2262/73272
There are numerous reports in the literature of advancing trends in phenophases of plants, insects and birds attributed to rising temperature resulting from human-driven climate warming. One mechanism that enables a population to respond rapidly to changes in the environ- ment is termed phenotypic plasticity. This plasticity grants a degree of flexibility to enable the tim- ing of developmental stages to coincide with resource availability. If, however, environmental con- ditions exceed the plastic limits of an organism, evolutionary change may be necessary in order to ensure continued survival of their populations. We review evidence for phenotypic plasticity and genetic adaptation in phenological characteristics associated with climatic warming. We focus this review on examples from trees, insects and birds. We found many reports of direct observations of phenotypic plasticity but fewer studies providing conclusive evidence of genetic adaptation. Evi- dence for changes in genes linked with adaptive traits associated with a warming climate was stronger in insects, that have a relatively short life-cycle, than in longer-lived birds and trees. Fur- ther research is required to identify both appropriate long-term data sets for a range of species and traits and suitable analytical methods, which will permit the study of the complex interaction between phenotypic plasticity and genetic adaptation of organisms and their populations in response to climatic change.
Fondazione Edmund Ma... arrow_drop_down Fondazione Edmund Mach: IRIS-OpenPubArticle . 2012Full-Text: http://hdl.handle.net/10449/21343Data sources: Bielefeld Academic Search Engine (BASE)The University of Dublin, Trinity College: TARA (Trinity's Access to Research Archive)Article . 2012Full-Text: http://hdl.handle.net/2262/73272Data sources: Bielefeld Academic Search Engine (BASE)Trinity's Access to Research ArchiveArticle . 2012 . Peer-reviewedData sources: Trinity's Access to Research Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euAccess RoutesGreen bronze 47 citations 47 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!
more_vert Fondazione Edmund Ma... arrow_drop_down Fondazione Edmund Mach: IRIS-OpenPubArticle . 2012Full-Text: http://hdl.handle.net/10449/21343Data sources: Bielefeld Academic Search Engine (BASE)The University of Dublin, Trinity College: TARA (Trinity's Access to Research Archive)Article . 2012Full-Text: http://hdl.handle.net/2262/73272Data sources: Bielefeld Academic Search Engine (BASE)Trinity's Access to Research ArchiveArticle . 2012 . Peer-reviewedData sources: Trinity's Access to Research Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3354/cr01102&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2017Publisher:Zenodo Authors: Garegnani, Giulia; Scaramuzzino, Chiara;Data show the total energy potential of wind in the eu28. raster data with the power density of wind at 50, 100 and 200 m are presented and then have been aggregated at nuts3 level in grass gis, through the corine land cover and by excluding urban areas, bird connectivity corridors, mountain peaks over 2500m and protected areas from the natura 2000 framework. in the dataset we report the median value at nuts3 level as indicator of the wind potential.
ZENODO arrow_drop_down add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.5281/zenodo.4687578&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!
visibility 38visibility views 38 download downloads 7 Powered bymore_vert ZENODO arrow_drop_down add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.5281/zenodo.4687578&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2022Embargo end date: 24 Dec 2021 United Kingdom, SwitzerlandPublisher:Elsevier BV Authors: Argyroudis, Sotirios A; Aristotels Mitoulis, Stergios; Chatzi, Eleni W; Baker, Jack W; +8 AuthorsArgyroudis, Sotirios A; Aristotels Mitoulis, Stergios; Chatzi, Eleni W; Baker, Jack W; Brilakis, Ioannis; Gkoumas, Konstantinos; Vousdoukas, Michalis; Hynes, William; Carluccio, Savina; Keou, Oceane; Frangopol, Dan M; Linkov, Igor;Delivering infrastructure, resilient to multiple natural hazards and climate change, is fundamental to continued economic prosperity and social coherence. This is a strategic priority of the United Nations Sustainable Development Goals (SDGs), the World Bank, the Organisation for Economic Co-operation and Development (OECD), public policies and global initiatives. The operability and functionality of critical infrastructure are continuously challenged by multiple stressors, increasing demands and ageing, whilst their interconnectedness and dependencies pose additional challenges. Emerging and disruptive digital technologies have the potential to enhance climate resilience of critical infrastructure, by providing rapid and accurate assessment of asset condition and support decision-making and adaptation. In this pursuit, it is imperative to adopt multidisciplinary roadmaps and deploy computational, communication and other digital technologies, tools and monitoring systems. Nevertheless, the potential of these emerging technologies remains largely unexploited, as there is a lack of consensus, integrated approaches and legislation in support of their use. In this perspective paper, we discuss the main challenges and enablers of climate-resilient infrastructure and we identify how available roadmaps, tools and emerging digital technologies, e.g. Internet of Things, digital twins, point clouds, Artificial Intelligence, Building Information Modelling, can be placed at the service of a safer world. We show how digital technologies will lead to infrastructure of enhanced resilience, by delivering efficient and reliable decision-making, in a proactive and/or reactive manner, prior, during and after hazard occurrences. In this respect, we discuss how emerging technologies significantly reduce the uncertainties in all phases of infrastructure resilience evaluations. Thus, building climate-resilient infrastructure, aided by digital technologies, will underpin critical activities globally, contribute to Net Zero target and hence safeguard our societies and economies. To achieve this we set an agenda, which is aligned with the relevant SDGs and highlights the urgent need to deliver holistic and inclusive standards and legislation, supported by coordinated alliances, to fully utilise emerging digital technologies.
Brunel University Lo... arrow_drop_down Brunel University London: Brunel University Research Archive (BURA)Article . 2021License: CC BYFull-Text: https://bura.brunel.ac.uk/handle/2438/23764Data sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.crm.2021.100387&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 103 citations 103 popularity Top 1% influence Top 10% impulse Top 1% Powered by BIP!
visibility 37visibility views 37 download downloads 50 Powered bymore_vert Brunel University Lo... arrow_drop_down Brunel University London: Brunel University Research Archive (BURA)Article . 2021License: CC BYFull-Text: https://bura.brunel.ac.uk/handle/2438/23764Data sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.crm.2021.100387&type=result"></script>'); --> </script>
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