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Research data keyboard_double_arrow_right Dataset 2023Publisher:World Data Center for Climate (WDCC) at DKRZ Ridley, Jeff; Menary, Matthew; Kuhlbrodt, Till; Andrews, Martin; Andrews, Tim;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.MOHC.HadGEM3-GC31-MM.historical' 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 HadGEM3-GC3.1-N216ORCA025 climate model, released in 2016, includes the following components: aerosol: UKCA-GLOMAP-mode, atmos: MetUM-HadGEM3-GA7.1 (N216; 432 x 324 longitude/latitude; 85 levels; top level 85 km), land: JULES-HadGEM3-GL7.1, ocean: NEMO-HadGEM3-GO6.0 (eORCA025 tripolar primarily 0.25 deg; 1440 x 1205 longitude/latitude; 75 levels; top grid cell 0-1 m), seaIce: CICE-HadGEM3-GSI8 (eORCA025 tripolar primarily 0.25 deg; 1440 x 1205 longitude/latitude). The model was run by the Met Office Hadley Centre, Fitzroy Road, Exeter, Devon, EX1 3PB, UK (MOHC) in native nominal resolutions: aerosol: 100 km, atmos: 100 km, land: 100 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:GitLab Vasconcelos, Miguel; Vasconcelos, Miguel; Cordeiro, Daniel; Da Costa, Georges; Dufossé, Fanny; Nicod, Jean-Marc; Rehn-Sonigo, Veronika;L'empreinte carbone des technologies numériques est une préoccupation depuis plusieurs années. Cela concerne principalement la consommation électrique des datacenters; beaucoup de fournisseurs dans le domaine du cloud s'engagent à n'utiliser que des sources d'énergie renouvelables. Cependant, cette approche néglige la phase de fabrication des composants des infrastructures numériques. Nous considérons dans ce travail de recherche la question du dimensionnement des énergies renouvelables pour une infrastructure de type cloud géographiquement distribuée autour de la planète, considérant l'impact carbone à la fois de l'électricité issue du réseau électrique local en fonction de la location de sa production, et de la fabrication des panneaux photovoltaïques et des batteries pour la part renouvelable de l'alimentation des ressources. Nous avons modélisé ce problème de minimisation de l'impact carbone d'une telle infrastructure cloud sous la forme d'un programme linéaire. La solution est le dimensionnement optimal d'une fédération de cloud sur une année complète en fonction des localisations des datacenters, des traces réelles des travaux à exécuter et valeurs d'irradiation solaire heure par heure. Nos résultats montrent une réduction de l'impact carbone de 30% comparés à la même architecture cloud totalement alimentée par des énergies renouvelables et 85% comparés à un modèle qui n'utiliserait qu'une alimentation via le réseau local d'électricité. The carbon footprint of IT technologies has been a significant concern in recent years. This concern mainly focuses on the electricity consumption of data centers; many cloud suppliers commit to using 100% of renewable energy sources. However, this approach neglects the impact of device manufacturing. We consider in this work the question of dimensioning the renewable energy sources of a geographically distributed cloud with considering the carbon impact of both the grid electricity consumption in the considered locations and the manufacturing of solar panels and batteries. We design a linear program to optimize cloud dimensioning over one year, considering worldwide locations for data centers, real-life workload traces, and solar irradiation values. Our results show a carbon footprint reduction of about 30% compared to a cloud fully supplied by solar energy and of 85% compared to the 100% grid electricity model. Données computationnelles ou de simulation: En tenant compte des données en entrée (description de la fédération de centres de données, fichiers de configuration appropriés, conditions météorologiques, etc.), le logiciel est capable de proposer un dimensionnement optimal pour la fédération des datacenters à faible émission de carbone distribuée à l'échelle mondiale : surface des panneaux photovoltaïques et capacité des batteries pour chaque datacenter de la fédération. Des scripts sont disponibles pour mettre en forme les solutions proposées. Simulation or computational data: Considering given inputs (datacenter federation, appropriate configuration files, weather conditions, etc.), the software is able to propose an optimal sizing for the globally distributed low carbon cloud federation: surface area of solar panels, battery capacity for each data center location. . Scripts are available to shape the optimal configuration. Audience: Research, Policy maker UpdatePeriodicity: as needed
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2023Publisher:4TU.ResearchData Kavun, Vitalii; van der Linden, Bart; Canossa, Stefano; Goryachev, Andrey; Bos , Emma E.; Santaclara, Jara Garcia; Smolentsev, Grigory; Repo, Eveliina; van der Veen, Monique A.;Dataset for the manuscript "Promoting photocatalytic activity of NH2-MIL-125(Ti) for H2 evolution reaction through creation of TiIII and CoI based proton reduction sites".Dataset includes raw N2 sorption data (.aif format), PXRD data of (Co@)NH2-MIL-125(Ti), Co K-edge XANES spectrum of Co foil and transitional XAS (70-1140 usec) and EXAFS data for Co@NH2-MIL-125(Ti), and raw TEM images of the photocatalysts. These data was used for analysis and plotting the figures for the manuscript.
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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: Stouffer, Ronald;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.UA.MCM-UA-1-0' 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 Manabe Climate Model v1.0 - University of Arizona climate model, released in 1991, includes the following components: aerosol: Modifies surface albedoes (Haywood et al. 1997, doi: 10.1175/1520-0442(1997)010<1562:GCMCOT>2.0.CO;2), atmos: R30L14 (3.75 X 2.5 degree (long-lat) configuration; 96 x 80 longitude/latitude; 14 levels; top level 0.015 sigma, 15 mb), land: Standard Manabe bucket hydrology scheme (Manabe 1969, doi: 10.1175/1520-0493(1969)097<0739:CATOC>2.3.CO;2), landIce: Specified location - invariant in time, has high albedo and latent heat capacity, ocean: MOM1.0 (MOM1, 1.875 X 2.5 deg; 192 x 80 longitude/latitude; 18 levels; top grid cell 0-40 m), seaIce: Thermodynamic ice model (free drift dynamics). The model was run by the Department of Geosciences, University of Arizona, Tucson, AZ 85721, USA (UA) in native nominal resolutions: aerosol: 250 km, atmos: 250 km, land: 250 km, landIce: 250 km, ocean: 250 km, seaIce: 250 km.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2023Embargo end date: 09 Mar 2023Publisher:Dryad Authors: Wolfe, Kennedy David; Desbiens, Amelia; Mumby, Peter;Patterns of movement of marine species can reflect strategies of reproduction and dispersal, species’ interactions, trophodynamics, and susceptibility to change, and thus critically inform how we manage populations and ecosystems. On coral reefs, the density and diversity of metazoan taxa is greatest in dead coral and rubble, which is suggested to fuel food webs from the bottom-up. Yet, biomass and secondary productivity in rubble is predominantly available in some of the smallest individuals, limiting how accessible this energy is to higher trophic levels. We address the bioavailability of motile coral reef cryptofauna based on small-scale patterns of emigration in rubble. We deployed modified RUbble Biodiversity Samplers (RUBS) and emergence traps in a shallow rubble patch at Heron Island, Great Barrier Reef, to detect community-level differences in the directional influx of motile cryptofauna under five habitat accessibility regimes. The mean density (0.13–4.5 ind.cm-3) and biomass (0.14–5.2 mg.cm-3) of cryptofauna were high and varied depending on microhabitat accessibility. Emergent zooplankton represented a distinct community (dominated by the Appendicularia and Calanoida) with the lowest density and biomass, indicating constraints on nocturnal resource availability. Mean cryptofauna density and biomass were greatest when interstitial access within rubble was blocked, driven by the rapid proliferation of small harpacticoid copepods from the rubble surface, leading to trophic simplification. Individuals with high biomass (e.g., decapods, gobies, and echinoderms) were greatest when interstitial access within rubble was unrestricted. Treatments with a closed rubble surface did not differ from those completely open, suggesting that top-down predation does not diminish rubble-derived resources. Our results show that conspecific cues and species’ interactions (e.g., competition and predation) within rubble are most critical in shaping ecological outcomes within the cryptobiome. These findings have implications for prey accessibility through trophic and community size structuring in rubble, which may become increasingly relevant as benthic reef complexity shifts in the Anthropocene. We address the bioavailability of coral reef cryptofauna in rubble based on small-scale patterns of emigration. We adapted the accessibility of Rubble Biodiversity Samplers (RUBS), models used to standardise biodiversity sampling in rubble (Wolfe and Mumby 2020), to explore the local movement patterns of rubble-dwelling fauna, with inference to predation processes within and beyond the cryptobenthos. Five treatments were developed to detect community-level differences in the directional influx of motile cryptofauna under various habitat accessibility regimes. Four of these treatments were developed by modifying accessibility into RUBS (https://www.thingiverse.com/thing:4176644/files) to understand limitations on the directional influx and movement of cryptofauna within coral rubble patches using four treatments; (1) open (completely accessible), (2) interstitial access (top closed), (3) surficial access (sides and bottom closed), and (4) raised (above rubble substratum). The fifth treatment involved a series of emergence plankton traps, designed to target demersal cryptofauna that vertically migrate from within the rubble benthos at night, given emergent zooplankton biomass and diversity are greatest at night. Fieldwork was conducted over several weeks (11th September to 5th October 2021) in a shallow (~3–5 m depth) reef slope site on the southern margin of Heron Island (-23˚26.845’ S, 151˚54.732’ E), Great Barrier Reef, Australia (Fig. 1). All collections were conducted under the Great Barrier Reef Marine Park Authority permit G20/44613.1.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2021Publisher:figshare Authors: Lucas Moreau (11607577); Evelyne Thiffault (10700505); Dominic Cyr (4836624); Yan Boulanger (2909306);Dataset for the article: How can the forest sector maintain its mitigation potential in a changing climate ? Case studies of boreal and northern temperate forests in eastern Canada.
figshare arrow_drop_down Smithsonian figshareDataset . 2021License: CC BYData 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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more_vert figshare arrow_drop_down Smithsonian figshareDataset . 2021License: CC BYData 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.euResearch data keyboard_double_arrow_right Dataset 2023Publisher:NERC EDS Environmental Information Data Centre Mercer, C.; Jump, A.; Morley, P.; O’Sullivan, K.; Van Der Maaten-Theunissen, M.; Zang, C.;Tree cores were sampled using increment borers. At each site three trees were chosen for coring, with two or three cores taken per tree. Cores were sanded and ring widths measured based on high-resolution images of the sanded cores. Cores were cross-dated and summary statistics used to compare cross-dating accuracy. The dataset contains the resulting dated ring width series. This dataset includes tree ring width data, derived from tree cores, that were sampled from sites across the Rhön Biosphere Reserve (Germany). At each chosen site three trees were cored, with two or three cores taken per cored tree. Data was collected in August 2021.
https://dx.doi.org/1... 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.euResearch data keyboard_double_arrow_right Dataset 2021Publisher:PANGAEA Authors: Hysa, Artan;The data shared in this package delivers the wildfire ignition probability and spreading capacity of vegetated surfaces in Romania following the method developed by Hysa and Baskaya (2019, https://doi.org/10.1007/s40808-018-0519-9). The model relies on remotely sensed free data that covers the time-lapse between 2015-2020. Geospatial information about sixteen criteria about anthropogenic, hydro-meteorological, geophysical, and fuel properties of Romanian territory are considered here. Raw data regarding each criterion is acquired for free from different online databases. The attribute table of the shared shapefile includes all inventory measurements per each criterion. It consist of 70410 point geometries in total representing 1km2 each, covering all vegetated surfaces of Romania. This data consist of a geospatial points layer (shp file), which deliver both the multi-criteria inventory records and the calculated wildfire ignition probability and wildfire spreading capacity (WIPI/WSCI) of the Romanian vegetated surfaces. The distance between points is 1km. The file consists of 70410 points in total, that overlap with the vegetated surfaces as derived from CORINE Land Cover data of 2018.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2021Publisher:Technical University of Denmark Authors: Vazquez Pombo, Daniel;Author: Daniel Vázquez Pombo (dvapo@elektro.dtu.dk) ------------------------------------------------------------------------------- This dataset corresponds to the results of the paper titled: "Multi-Horizon Data-Driven Wind Power Forecast: From Nowcast to 2 Days-Ahead" 4th International Conference on Smart Energy Systems and Technologies (SEST) - 2021 -> https://sites.univaasa.fi/sest2021/ Submmited: Dec 2020 Accepted: Feb 2021 Published: Sep 2021 ------------------------------------------------------------------------------- The folder contains all the results presented in the paper, for clarity. Additional resources might be supplied under request. -------------------------------------------------------------------------------
Smithsonian figshare arrow_drop_down Smithsonian figshareDataset . 2021License: CC BY SAData 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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more_vert Smithsonian figshare arrow_drop_down Smithsonian figshareDataset . 2021License: CC BY SAData 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.euResearch data keyboard_double_arrow_right Dataset 2023Publisher:World Data Center for Climate (WDCC) at DKRZ John, Jasmin G; Blanton, Chris; McHugh, Colleen; Radhakrishnan, Aparna; Rand, Kristopher; Vahlenkamp, Hans; Wilson, Chandin; Zadeh, Niki T.; Dunne, John P.; Dussin, Raphael; Horowitz, Larry W.; Krasting, John P.; Lin, Pu; Malyshev, Sergey; Naik, Vaishali; Ploshay, Jeffrey; Shevliakova, Elena; Silvers, Levi; Stock, Charles; Winton, Michael; Zeng, Yujin;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.NOAA-GFDL.GFDL-ESM4.ssp245' 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 GFDL-ESM4 climate model, released in 2018, includes the following components: aerosol: interactive, atmos: GFDL-AM4.1 (Cubed-sphere (c96) - 1 degree nominal horizontal resolution; 360 x 180 longitude/latitude; 49 levels; top level 1 Pa), atmosChem: GFDL-ATMCHEM4.1 (full atmospheric chemistry), land: GFDL-LM4.1, landIce: GFDL-LM4.1, ocean: GFDL-OM4p5 (GFDL-MOM6, tripolar - nominal 0.5 deg; 720 x 576 longitude/latitude; 75 levels; top grid cell 0-2 m), ocnBgchem: GFDL-COBALTv2, seaIce: GFDL-SIM4p5 (GFDL-SIS2.0, tripolar - nominal 0.5 deg; 720 x 576 longitude/latitude; 5 layers; 5 thickness categories). The model was run by the National Oceanic and Atmospheric Administration, Geophysical Fluid Dynamics Laboratory, Princeton, NJ 08540, USA (NOAA-GFDL) in native nominal resolutions: aerosol: 100 km, atmos: 100 km, atmosChem: 100 km, land: 100 km, landIce: 100 km, ocean: 50 km, ocnBgchem: 50 km, seaIce: 50 km.
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Research data keyboard_double_arrow_right Dataset 2023Publisher:World Data Center for Climate (WDCC) at DKRZ Ridley, Jeff; Menary, Matthew; Kuhlbrodt, Till; Andrews, Martin; Andrews, Tim;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.MOHC.HadGEM3-GC31-MM.historical' 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 HadGEM3-GC3.1-N216ORCA025 climate model, released in 2016, includes the following components: aerosol: UKCA-GLOMAP-mode, atmos: MetUM-HadGEM3-GA7.1 (N216; 432 x 324 longitude/latitude; 85 levels; top level 85 km), land: JULES-HadGEM3-GL7.1, ocean: NEMO-HadGEM3-GO6.0 (eORCA025 tripolar primarily 0.25 deg; 1440 x 1205 longitude/latitude; 75 levels; top grid cell 0-1 m), seaIce: CICE-HadGEM3-GSI8 (eORCA025 tripolar primarily 0.25 deg; 1440 x 1205 longitude/latitude). The model was run by the Met Office Hadley Centre, Fitzroy Road, Exeter, Devon, EX1 3PB, UK (MOHC) in native nominal resolutions: aerosol: 100 km, atmos: 100 km, land: 100 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:GitLab Vasconcelos, Miguel; Vasconcelos, Miguel; Cordeiro, Daniel; Da Costa, Georges; Dufossé, Fanny; Nicod, Jean-Marc; Rehn-Sonigo, Veronika;L'empreinte carbone des technologies numériques est une préoccupation depuis plusieurs années. Cela concerne principalement la consommation électrique des datacenters; beaucoup de fournisseurs dans le domaine du cloud s'engagent à n'utiliser que des sources d'énergie renouvelables. Cependant, cette approche néglige la phase de fabrication des composants des infrastructures numériques. Nous considérons dans ce travail de recherche la question du dimensionnement des énergies renouvelables pour une infrastructure de type cloud géographiquement distribuée autour de la planète, considérant l'impact carbone à la fois de l'électricité issue du réseau électrique local en fonction de la location de sa production, et de la fabrication des panneaux photovoltaïques et des batteries pour la part renouvelable de l'alimentation des ressources. Nous avons modélisé ce problème de minimisation de l'impact carbone d'une telle infrastructure cloud sous la forme d'un programme linéaire. La solution est le dimensionnement optimal d'une fédération de cloud sur une année complète en fonction des localisations des datacenters, des traces réelles des travaux à exécuter et valeurs d'irradiation solaire heure par heure. Nos résultats montrent une réduction de l'impact carbone de 30% comparés à la même architecture cloud totalement alimentée par des énergies renouvelables et 85% comparés à un modèle qui n'utiliserait qu'une alimentation via le réseau local d'électricité. The carbon footprint of IT technologies has been a significant concern in recent years. This concern mainly focuses on the electricity consumption of data centers; many cloud suppliers commit to using 100% of renewable energy sources. However, this approach neglects the impact of device manufacturing. We consider in this work the question of dimensioning the renewable energy sources of a geographically distributed cloud with considering the carbon impact of both the grid electricity consumption in the considered locations and the manufacturing of solar panels and batteries. We design a linear program to optimize cloud dimensioning over one year, considering worldwide locations for data centers, real-life workload traces, and solar irradiation values. Our results show a carbon footprint reduction of about 30% compared to a cloud fully supplied by solar energy and of 85% compared to the 100% grid electricity model. Données computationnelles ou de simulation: En tenant compte des données en entrée (description de la fédération de centres de données, fichiers de configuration appropriés, conditions météorologiques, etc.), le logiciel est capable de proposer un dimensionnement optimal pour la fédération des datacenters à faible émission de carbone distribuée à l'échelle mondiale : surface des panneaux photovoltaïques et capacité des batteries pour chaque datacenter de la fédération. Des scripts sont disponibles pour mettre en forme les solutions proposées. Simulation or computational data: Considering given inputs (datacenter federation, appropriate configuration files, weather conditions, etc.), the software is able to propose an optimal sizing for the globally distributed low carbon cloud federation: surface area of solar panels, battery capacity for each data center location. . Scripts are available to shape the optimal configuration. Audience: Research, Policy maker UpdatePeriodicity: as needed
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2023Publisher:4TU.ResearchData Kavun, Vitalii; van der Linden, Bart; Canossa, Stefano; Goryachev, Andrey; Bos , Emma E.; Santaclara, Jara Garcia; Smolentsev, Grigory; Repo, Eveliina; van der Veen, Monique A.;Dataset for the manuscript "Promoting photocatalytic activity of NH2-MIL-125(Ti) for H2 evolution reaction through creation of TiIII and CoI based proton reduction sites".Dataset includes raw N2 sorption data (.aif format), PXRD data of (Co@)NH2-MIL-125(Ti), Co K-edge XANES spectrum of Co foil and transitional XAS (70-1140 usec) and EXAFS data for Co@NH2-MIL-125(Ti), and raw TEM images of the photocatalysts. These data was used for analysis and plotting the figures for the manuscript.
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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: Stouffer, Ronald;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.UA.MCM-UA-1-0' 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 Manabe Climate Model v1.0 - University of Arizona climate model, released in 1991, includes the following components: aerosol: Modifies surface albedoes (Haywood et al. 1997, doi: 10.1175/1520-0442(1997)010<1562:GCMCOT>2.0.CO;2), atmos: R30L14 (3.75 X 2.5 degree (long-lat) configuration; 96 x 80 longitude/latitude; 14 levels; top level 0.015 sigma, 15 mb), land: Standard Manabe bucket hydrology scheme (Manabe 1969, doi: 10.1175/1520-0493(1969)097<0739:CATOC>2.3.CO;2), landIce: Specified location - invariant in time, has high albedo and latent heat capacity, ocean: MOM1.0 (MOM1, 1.875 X 2.5 deg; 192 x 80 longitude/latitude; 18 levels; top grid cell 0-40 m), seaIce: Thermodynamic ice model (free drift dynamics). The model was run by the Department of Geosciences, University of Arizona, Tucson, AZ 85721, USA (UA) in native nominal resolutions: aerosol: 250 km, atmos: 250 km, land: 250 km, landIce: 250 km, ocean: 250 km, seaIce: 250 km.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2023Embargo end date: 09 Mar 2023Publisher:Dryad Authors: Wolfe, Kennedy David; Desbiens, Amelia; Mumby, Peter;Patterns of movement of marine species can reflect strategies of reproduction and dispersal, species’ interactions, trophodynamics, and susceptibility to change, and thus critically inform how we manage populations and ecosystems. On coral reefs, the density and diversity of metazoan taxa is greatest in dead coral and rubble, which is suggested to fuel food webs from the bottom-up. Yet, biomass and secondary productivity in rubble is predominantly available in some of the smallest individuals, limiting how accessible this energy is to higher trophic levels. We address the bioavailability of motile coral reef cryptofauna based on small-scale patterns of emigration in rubble. We deployed modified RUbble Biodiversity Samplers (RUBS) and emergence traps in a shallow rubble patch at Heron Island, Great Barrier Reef, to detect community-level differences in the directional influx of motile cryptofauna under five habitat accessibility regimes. The mean density (0.13–4.5 ind.cm-3) and biomass (0.14–5.2 mg.cm-3) of cryptofauna were high and varied depending on microhabitat accessibility. Emergent zooplankton represented a distinct community (dominated by the Appendicularia and Calanoida) with the lowest density and biomass, indicating constraints on nocturnal resource availability. Mean cryptofauna density and biomass were greatest when interstitial access within rubble was blocked, driven by the rapid proliferation of small harpacticoid copepods from the rubble surface, leading to trophic simplification. Individuals with high biomass (e.g., decapods, gobies, and echinoderms) were greatest when interstitial access within rubble was unrestricted. Treatments with a closed rubble surface did not differ from those completely open, suggesting that top-down predation does not diminish rubble-derived resources. Our results show that conspecific cues and species’ interactions (e.g., competition and predation) within rubble are most critical in shaping ecological outcomes within the cryptobiome. These findings have implications for prey accessibility through trophic and community size structuring in rubble, which may become increasingly relevant as benthic reef complexity shifts in the Anthropocene. We address the bioavailability of coral reef cryptofauna in rubble based on small-scale patterns of emigration. We adapted the accessibility of Rubble Biodiversity Samplers (RUBS), models used to standardise biodiversity sampling in rubble (Wolfe and Mumby 2020), to explore the local movement patterns of rubble-dwelling fauna, with inference to predation processes within and beyond the cryptobenthos. Five treatments were developed to detect community-level differences in the directional influx of motile cryptofauna under various habitat accessibility regimes. Four of these treatments were developed by modifying accessibility into RUBS (https://www.thingiverse.com/thing:4176644/files) to understand limitations on the directional influx and movement of cryptofauna within coral rubble patches using four treatments; (1) open (completely accessible), (2) interstitial access (top closed), (3) surficial access (sides and bottom closed), and (4) raised (above rubble substratum). The fifth treatment involved a series of emergence plankton traps, designed to target demersal cryptofauna that vertically migrate from within the rubble benthos at night, given emergent zooplankton biomass and diversity are greatest at night. Fieldwork was conducted over several weeks (11th September to 5th October 2021) in a shallow (~3–5 m depth) reef slope site on the southern margin of Heron Island (-23˚26.845’ S, 151˚54.732’ E), Great Barrier Reef, Australia (Fig. 1). All collections were conducted under the Great Barrier Reef Marine Park Authority permit G20/44613.1.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2021Publisher:figshare Authors: Lucas Moreau (11607577); Evelyne Thiffault (10700505); Dominic Cyr (4836624); Yan Boulanger (2909306);Dataset for the article: How can the forest sector maintain its mitigation potential in a changing climate ? Case studies of boreal and northern temperate forests in eastern Canada.
figshare arrow_drop_down Smithsonian figshareDataset . 2021License: CC BYData 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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more_vert figshare arrow_drop_down Smithsonian figshareDataset . 2021License: CC BYData 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.euResearch data keyboard_double_arrow_right Dataset 2023Publisher:NERC EDS Environmental Information Data Centre Mercer, C.; Jump, A.; Morley, P.; O’Sullivan, K.; Van Der Maaten-Theunissen, M.; Zang, C.;Tree cores were sampled using increment borers. At each site three trees were chosen for coring, with two or three cores taken per tree. Cores were sanded and ring widths measured based on high-resolution images of the sanded cores. Cores were cross-dated and summary statistics used to compare cross-dating accuracy. The dataset contains the resulting dated ring width series. This dataset includes tree ring width data, derived from tree cores, that were sampled from sites across the Rhön Biosphere Reserve (Germany). At each chosen site three trees were cored, with two or three cores taken per cored tree. Data was collected in August 2021.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2021Publisher:PANGAEA Authors: Hysa, Artan;The data shared in this package delivers the wildfire ignition probability and spreading capacity of vegetated surfaces in Romania following the method developed by Hysa and Baskaya (2019, https://doi.org/10.1007/s40808-018-0519-9). The model relies on remotely sensed free data that covers the time-lapse between 2015-2020. Geospatial information about sixteen criteria about anthropogenic, hydro-meteorological, geophysical, and fuel properties of Romanian territory are considered here. Raw data regarding each criterion is acquired for free from different online databases. The attribute table of the shared shapefile includes all inventory measurements per each criterion. It consist of 70410 point geometries in total representing 1km2 each, covering all vegetated surfaces of Romania. This data consist of a geospatial points layer (shp file), which deliver both the multi-criteria inventory records and the calculated wildfire ignition probability and wildfire spreading capacity (WIPI/WSCI) of the Romanian vegetated surfaces. The distance between points is 1km. The file consists of 70410 points in total, that overlap with the vegetated surfaces as derived from CORINE Land Cover data of 2018.
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For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!
more_vert 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.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2021Publisher:Technical University of Denmark Authors: Vazquez Pombo, Daniel;Author: Daniel Vázquez Pombo (dvapo@elektro.dtu.dk) ------------------------------------------------------------------------------- This dataset corresponds to the results of the paper titled: "Multi-Horizon Data-Driven Wind Power Forecast: From Nowcast to 2 Days-Ahead" 4th International Conference on Smart Energy Systems and Technologies (SEST) - 2021 -> https://sites.univaasa.fi/sest2021/ Submmited: Dec 2020 Accepted: Feb 2021 Published: Sep 2021 ------------------------------------------------------------------------------- The folder contains all the results presented in the paper, for clarity. Additional resources might be supplied under request. -------------------------------------------------------------------------------
Smithsonian figshare arrow_drop_down Smithsonian figshareDataset . 2021License: CC BY SAData 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.
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more_vert Smithsonian figshare arrow_drop_down Smithsonian figshareDataset . 2021License: CC BY SAData 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.
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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 John, Jasmin G; Blanton, Chris; McHugh, Colleen; Radhakrishnan, Aparna; Rand, Kristopher; Vahlenkamp, Hans; Wilson, Chandin; Zadeh, Niki T.; Dunne, John P.; Dussin, Raphael; Horowitz, Larry W.; Krasting, John P.; Lin, Pu; Malyshev, Sergey; Naik, Vaishali; Ploshay, Jeffrey; Shevliakova, Elena; Silvers, Levi; Stock, Charles; Winton, Michael; Zeng, Yujin;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.NOAA-GFDL.GFDL-ESM4.ssp245' 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 GFDL-ESM4 climate model, released in 2018, includes the following components: aerosol: interactive, atmos: GFDL-AM4.1 (Cubed-sphere (c96) - 1 degree nominal horizontal resolution; 360 x 180 longitude/latitude; 49 levels; top level 1 Pa), atmosChem: GFDL-ATMCHEM4.1 (full atmospheric chemistry), land: GFDL-LM4.1, landIce: GFDL-LM4.1, ocean: GFDL-OM4p5 (GFDL-MOM6, tripolar - nominal 0.5 deg; 720 x 576 longitude/latitude; 75 levels; top grid cell 0-2 m), ocnBgchem: GFDL-COBALTv2, seaIce: GFDL-SIM4p5 (GFDL-SIS2.0, tripolar - nominal 0.5 deg; 720 x 576 longitude/latitude; 5 layers; 5 thickness categories). The model was run by the National Oceanic and Atmospheric Administration, Geophysical Fluid Dynamics Laboratory, Princeton, NJ 08540, USA (NOAA-GFDL) in native nominal resolutions: aerosol: 100 km, atmos: 100 km, atmosChem: 100 km, land: 100 km, landIce: 100 km, ocean: 50 km, ocnBgchem: 50 km, seaIce: 50 km.
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For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!
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