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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: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 2018Embargo end date: 14 Sep 2018Publisher:Harvard Dataverse Authors: Hap, Navy;doi: 10.7910/dvn/7qhibo
The database focused in both culture and capture, are susceptible to the impacts of climate change. The data collection to examine the vulnerability, as perceived by snakehead (Channa striata) fish farmers in Vietnam and fishers in Cambodia, to the impacts from climate change. Perceived impacts on various actors in the value chain are identified, as well as adaptation strategies currently being utilized and planned for the future and perception suggested to contribute to assisting snakehead farmers and fishers in adapting and preparing for the impacts of climate change.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2017Publisher:4TU.Centre for Research Data Authors: den Heijer, C. (Kees);Meteo measurements at the Sand Motor. Air temperature, humidity, pressure, solar radiation, precipitation, wind speed and wind direction are measured. Contributor: Verheijen, A.H. (Anne) [orcid:0000-0002-2131-7619]
4TU.ResearchData | s... arrow_drop_down DANS (Data Archiving and Networked Services)DatasetData sources: DANS (Data Archiving and Networked Services)DANS (Data Archiving and Networked Services)DatasetData sources: DANS (Data Archiving and Networked Services)DANS (Data Archiving and Networked Services)DatasetData sources: DANS (Data Archiving and Networked Services)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 4TU.ResearchData | s... arrow_drop_down DANS (Data Archiving and Networked Services)DatasetData sources: DANS (Data Archiving and Networked Services)DANS (Data Archiving and Networked Services)DatasetData sources: DANS (Data Archiving and Networked Services)DANS (Data Archiving and Networked Services)DatasetData sources: DANS (Data Archiving and Networked Services)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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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=10.4121/12713645.v2&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2018Publisher:PANGAEA Nardone, Jessica A; Patel, Shrey; Siegel, Kyle R; Tedesco, Dana; McNicholl, Conall G; O'Malley, Jessica; Herrick, Jack; Metzler, Rebecca A; Orihuela, Beatriz; Rittschof, Daniel; Dickinson, Gary H;Barnacles are dominant members of marine intertidal communities. Their success depends on firm attachment provided by their proteinaceous adhesive and protection imparted by their calcified shell plates. Little is known about how variations in the environment affect adhesion and shell formation processes in barnacles. Increased levels of atmospheric CO2 have led to a reduction in the pH of ocean waters (i.e., ocean acidification), a trend that is expected to continue into the future. Here, we assessed if a reduction in seawater pH, at levels predicted within the next 200 years, would alter physiology, adhesion, and shell formation in the cosmopolitan barnacle Amphibalanus (=Balanus) amphitrite. Juvenile barnacles, settled on silicone substrates, were exposed to one of three static levels of pHT, 8.01, 7.78, or 7.50, for 13 weeks. We found that barnacles were robust to reduced pH, with no effect of pH on physiological metrics (mortality, tissue mass, and presence of eggs). Likewise, adhesive properties (adhesion strength and adhesive plaque gross morphology) were not affected by reduced pH. Shell formation, however, was affected by seawater pH. Shell mass and base plate area were higher in barnacles exposed to reduced pH; barnacles grown at pHT 8.01 exhibited approximately 30% lower shell mass and 20% smaller base plate area as compared to those at pHT 7.50 or 7.78. Enhanced growth at reduced pH appears to be driven by the increased size of the calcite crystals that comprise the shell. Despite enhanced growth, mechanical properties of the base plate (but not the parietal plates) were compromised at the lowest pH level. Barnacle base plates at pHT 7.50 broke more easily and crack propagation, measured through microhardness testing, was significantly affected by seawater pH. Other shell metrics (plate thickness, relative crystallinity, and atomic disorder) were not affected by seawater pH. Hence, a reduction in pH resulted in larger barnacles but with base plates that would crack more readily. It is yet to be determined if such changes would alter the survival of A. amphitrite in the field, but changes in the abundance of this ecologically dominant species would undoubtedly affect the composition of biofouling communities. In order to allow full comparability with other ocean acidification data sets, the R package seacarb (Gattuso et al, 2019) was used to compute a complete and consistent set of carbonate system variables, as described by Nisumaa et al. (2010). In this dataset the original values were archived in addition with the recalculated parameters (see related PI). The date of carbonate chemistry calculation by seacarb is 2020-09-18.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2020Publisher:University of Bath Fosas, Daniel; Nikolaidou, Elli; Roberts, Matt; Allen, Stephen; Walker, Ian; Coley, David;doi: 10.15125/bath-00766
Dataset for the journal paper "Towards Active Buildings: rating grid-servicing buildings", which describes the simulations for the 20 case study buildings. The simulation inputs describe the intended characteristics as part of the early design stage process, and the outputs the performance metrics under the rating system introduced in the journal paper, called the ABCode1. Such outputs rate the relative merits of each case study in terms of embodied carbon, energy requirements, energy generation and energy flexibility. The simulation outputs have been generated using the inputs included in the dataset, which were then simulated in David Coley’s ZEBRA and then evaluated with the rating system proposed in the journal publication as part of ABCode1. The files are in the original Excel xlsx file (Microsoft Office 365), but it may be viewed by any other spread sheet tools such as LibreOffice's Calc.
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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 2016Publisher:International Institute of Refrigeration (IIR) Authors: GULLO, P.; CORTELLA, G.; POLZOT, A.;Carbon dioxide (CO2, R744) is an environmentally friendly refrigerant, which is widely used in supermarket refrigeration systems located in cold weather sites. Its use at high outdoor temperatures still requires some additional investigations to accomplish performance similar to the one obtained by employing the conventional working fluids. This paper deals with the theoretical comparison in terms of both annual energy consumption and Total Equivalent Warming Impact (TEWI) of different commercial R744 refrigeration cycles operating in five different warm climates. An innovative CO2 direct expansion (DX) configuration, which serves both the medium temperature (MT) load and the low temperature (LT) one, is also considered. Taking into account the running modes of a typical European supermarket and a R404A multiplex configuration as the baseline, the results showed that enhanced R744 refrigeration technologies are capable of dropping the energy consumption and the TEWI by at least 2.8% and 31.1%, respectively.
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For further information contact us at helpdesk@openaire.eu7 citations 7 popularity Average influence Average impulse Top 10% Powered by BIP!
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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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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: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 2018Embargo end date: 14 Sep 2018Publisher:Harvard Dataverse Authors: Hap, Navy;doi: 10.7910/dvn/7qhibo
The database focused in both culture and capture, are susceptible to the impacts of climate change. The data collection to examine the vulnerability, as perceived by snakehead (Channa striata) fish farmers in Vietnam and fishers in Cambodia, to the impacts from climate change. Perceived impacts on various actors in the value chain are identified, as well as adaptation strategies currently being utilized and planned for the future and perception suggested to contribute to assisting snakehead farmers and fishers in adapting and preparing for the impacts of climate change.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2017Publisher:4TU.Centre for Research Data Authors: den Heijer, C. (Kees);Meteo measurements at the Sand Motor. Air temperature, humidity, pressure, solar radiation, precipitation, wind speed and wind direction are measured. Contributor: Verheijen, A.H. (Anne) [orcid:0000-0002-2131-7619]
4TU.ResearchData | s... arrow_drop_down DANS (Data Archiving and Networked Services)DatasetData sources: DANS (Data Archiving and Networked Services)DANS (Data Archiving and Networked Services)DatasetData sources: DANS (Data Archiving and Networked Services)DANS (Data Archiving and Networked Services)DatasetData sources: DANS (Data Archiving and Networked Services)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 4TU.ResearchData | s... arrow_drop_down DANS (Data Archiving and Networked Services)DatasetData sources: DANS (Data Archiving and Networked Services)DANS (Data Archiving and Networked Services)DatasetData sources: DANS (Data Archiving and Networked Services)DANS (Data Archiving and Networked Services)DatasetData sources: DANS (Data Archiving and Networked Services)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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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=10.4121/12713645.v2&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2018Publisher:PANGAEA Nardone, Jessica A; Patel, Shrey; Siegel, Kyle R; Tedesco, Dana; McNicholl, Conall G; O'Malley, Jessica; Herrick, Jack; Metzler, Rebecca A; Orihuela, Beatriz; Rittschof, Daniel; Dickinson, Gary H;Barnacles are dominant members of marine intertidal communities. Their success depends on firm attachment provided by their proteinaceous adhesive and protection imparted by their calcified shell plates. Little is known about how variations in the environment affect adhesion and shell formation processes in barnacles. Increased levels of atmospheric CO2 have led to a reduction in the pH of ocean waters (i.e., ocean acidification), a trend that is expected to continue into the future. Here, we assessed if a reduction in seawater pH, at levels predicted within the next 200 years, would alter physiology, adhesion, and shell formation in the cosmopolitan barnacle Amphibalanus (=Balanus) amphitrite. Juvenile barnacles, settled on silicone substrates, were exposed to one of three static levels of pHT, 8.01, 7.78, or 7.50, for 13 weeks. We found that barnacles were robust to reduced pH, with no effect of pH on physiological metrics (mortality, tissue mass, and presence of eggs). Likewise, adhesive properties (adhesion strength and adhesive plaque gross morphology) were not affected by reduced pH. Shell formation, however, was affected by seawater pH. Shell mass and base plate area were higher in barnacles exposed to reduced pH; barnacles grown at pHT 8.01 exhibited approximately 30% lower shell mass and 20% smaller base plate area as compared to those at pHT 7.50 or 7.78. Enhanced growth at reduced pH appears to be driven by the increased size of the calcite crystals that comprise the shell. Despite enhanced growth, mechanical properties of the base plate (but not the parietal plates) were compromised at the lowest pH level. Barnacle base plates at pHT 7.50 broke more easily and crack propagation, measured through microhardness testing, was significantly affected by seawater pH. Other shell metrics (plate thickness, relative crystallinity, and atomic disorder) were not affected by seawater pH. Hence, a reduction in pH resulted in larger barnacles but with base plates that would crack more readily. It is yet to be determined if such changes would alter the survival of A. amphitrite in the field, but changes in the abundance of this ecologically dominant species would undoubtedly affect the composition of biofouling communities. In order to allow full comparability with other ocean acidification data sets, the R package seacarb (Gattuso et al, 2019) was used to compute a complete and consistent set of carbonate system variables, as described by Nisumaa et al. (2010). In this dataset the original values were archived in addition with the recalculated parameters (see related PI). The date of carbonate chemistry calculation by seacarb is 2020-09-18.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2020Publisher:University of Bath Fosas, Daniel; Nikolaidou, Elli; Roberts, Matt; Allen, Stephen; Walker, Ian; Coley, David;doi: 10.15125/bath-00766
Dataset for the journal paper "Towards Active Buildings: rating grid-servicing buildings", which describes the simulations for the 20 case study buildings. The simulation inputs describe the intended characteristics as part of the early design stage process, and the outputs the performance metrics under the rating system introduced in the journal paper, called the ABCode1. Such outputs rate the relative merits of each case study in terms of embodied carbon, energy requirements, energy generation and energy flexibility. The simulation outputs have been generated using the inputs included in the dataset, which were then simulated in David Coley’s ZEBRA and then evaluated with the rating system proposed in the journal publication as part of ABCode1. The files are in the original Excel xlsx file (Microsoft Office 365), but it may be viewed by any other spread sheet tools such as LibreOffice's Calc.
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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.
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 2016Publisher:International Institute of Refrigeration (IIR) Authors: GULLO, P.; CORTELLA, G.; POLZOT, A.;Carbon dioxide (CO2, R744) is an environmentally friendly refrigerant, which is widely used in supermarket refrigeration systems located in cold weather sites. Its use at high outdoor temperatures still requires some additional investigations to accomplish performance similar to the one obtained by employing the conventional working fluids. This paper deals with the theoretical comparison in terms of both annual energy consumption and Total Equivalent Warming Impact (TEWI) of different commercial R744 refrigeration cycles operating in five different warm climates. An innovative CO2 direct expansion (DX) configuration, which serves both the medium temperature (MT) load and the low temperature (LT) one, is also considered. Taking into account the running modes of a typical European supermarket and a R404A multiplex configuration as the baseline, the results showed that enhanced R744 refrigeration technologies are capable of dropping the energy consumption and the TEWI by at least 2.8% and 31.1%, respectively.
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=10.18462/iir.iccc.2016.0041&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu7 citations 7 popularity Average influence Average impulse Top 10% 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.
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=10.18462/iir.iccc.2016.0041&type=result"></script>'); --> </script>
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.
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=10.1594/pangaea.931475&type=result"></script>'); --> </script>
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.
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=10.1594/pangaea.931475&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu