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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Doukas, Haris; Spiliotis, Evangelos; Jafari, Mohsen A.; Giarola, Sara; +1 Authors

    This dataset contains the underlying data for the following publication: Doukas, H., Spiliotis, E., Jafari, M. A., Giarola, S. & Nikas, A. (2021). Low-cost emissions cuts in container shipping: Thinking inside the box. Transportation Research Part D: Transport and Environment, 94, 102815, https://doi.org/10.1016/j.trd.2021.102815.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: ZENODO
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: ZENODO
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    Authors: Ferreira, Igor José Malfetoni; Campanharo, Wesley Augusto; Fonseca, Marisa Gesteira; Escada, Maria Isabel Sobral; +7 Authors

    This file collection contains the estimated spatial distribution of the above-ground biomass density (AGB) by the end of the 21st century across the Brazilian Atlantic Forest domain and the respective uncertanty. To develop the models, we used the maximum entropy method with projected climate data to 2100, based on the Intergovernmental Panel on Climate Change (IPCC) Representative Concentration Pathway (RCP) 4.5 from the fifth Assessment Report (AR5). The dataset is composed of four files in GeoTIFF format: calibrated-AGB-distribution.tif: raster file representing the present spatial distribution of the above-ground biomass density in the Atlantic Forest from the calibrated model. Unit: Mg/ha estimated-uncertanty-for-calibrated-agb-distribution.tif: raster file representing the estimated spatial uncertanty distribution of the calibrated above-ground biomass density. Unit: percentage. projected-AGB-distribution-under-rcp45.tif: raster file representing the projected spatial distribution of the above-ground biomass density in the Atlantic Forest by the end of 2100 under RCP 4.5 scenario. Unit: Mg/ha estimated-uncertanty-for-projected-agb-distribution.tif: raster file representing the estimated spatial uncertanty distribution of the projected above-ground biomass density. Unit: percentage. Spatial resolution: 0.0083 degree (ca. 1 km) Coordinate reference system: Geographic Coordinate System - Datum WGS84

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    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: ZENODO
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: ZENODO
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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    Authors: Banu, Ioan Viorel; Istrate, Marcel;

    This dataset contains (1) the Simulink model of a three-phase photovoltaic power system with passive anti-islanding protections like over/under current (OUC), over/under voltage (OUV), over/under frequency (OUF), rate of change of frequency (ROCOF), and dc-link voltage and (2) the results in the voltage source converter and the point of common coupling of the photovoltaic system during islanding operation mode and detection times of analyzed anti-islanding methods. The dataset is related with the data used in the "DC-Link Voltage Anti-Islanding Method for Grid-Connected Photovoltaic Power Systems" manuscript submitted to IEEE Transactions on Smart Grid.

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    IEEE DataPort
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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      IEEE DataPort
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Ridley, Jeff; Menary, Matthew; Kuhlbrodt, Till; Andrews, Martin; +1 Authors

    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.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ World Data Center fo...arrow_drop_down
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    World Data Center for Climate
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    World Data Center for Climate
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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      World Data Center for Climate
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      World Data Center for Climate
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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    Authors: Horton, Tammy; Serpell-Stevens, Amanda; Domedel, Georgina Valls; Bett, Brian James;

    These data record the results of processing otter trawl catches (OTSB14; Merrett & Marshall, 1980) from the National Oceanography Centre (NOC, UK) long-term study of the Porcupine Abyssal Plain (PAP), including the PAP-Sustained Observatory time-series. The data concern catches recovered during the RRS Challenger cruise 135 in 1997. Billett, D.S.M. et al. (1998). RRS Challenger Cruise 135, 15 Oct-30 Oct 1997. BENGAL: High resolution temporal and spatial study of the BENthic biology and Geochemistry of a north-eastern Atlantic abyssal Locality. Southampton Oceanography Centre Cruise Report, No. 19, 49pp.| https://www.bodc.ac.uk/resources/inventories/cruise_inventory/reports/ch135_97.pdf

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    Global Biodiversity Information Facility
    Dataset . 2024
    License: CC BY
    Data sources: Datacite
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      Global Biodiversity Information Facility
      Dataset . 2024
      License: CC BY
      Data sources: Datacite
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    Authors: Hoffmann, Roman; Dimitrova, Anna; Muttarak, Raya; Crespo Cuaresma, Jesus; +1 Authors

    Complete replication data and code for article "A Meta-Analysis of Country Level Studies on Environmental Change and Migration". The rdata file contains both the meta and country level data. The data is also saved separately as xlsx files.

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    Harvard Dataverse
    Dataset . 2020
    License: CC 0
    Data sources: Datacite
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      Harvard Dataverse
      Dataset . 2020
      License: CC 0
      Data sources: Datacite
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    Authors: Myrgiotis, Vasilis; Williams, Mathew;

    Model inputs, model code and aggregated model outputs (seasonal, annual) for every grassland field simulated (2017-2018) in "Myrgiotis et al. The carbon budget of the managed grasslands of Great Britain - informed by earth observations, Biogeosciences, 2022". Input files include (1) climate data (sitecode_M.npy) and (2) satellite based observations of Leaf Area Index (sitecode_O.pkl). Model code written in fortran. Model outputs (i.e. carbon pools, fluxes and balance for 2017 and 2018) aggregated annually (annual_outputs.csv) and monthly (annual_outputs.csv).

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    Edinburgh DataShare
    Dataset . 2022
    License: CC BY
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      Edinburgh DataShare
      Dataset . 2022
      License: CC BY
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    Authors: Fosas, Daniel; Nikolaidou, Elli; Roberts, Matt; Allen, Stephen; +2 Authors

    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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    University of Bath Research Data Archive
    Dataset . 2020
    License: CC BY
    Data sources: Datacite
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      University of Bath Research Data Archive
      Dataset . 2020
      License: CC BY
      Data sources: Datacite
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    Authors: Nuh, Mishael;

    3D scans of two prototypes digitally fabricated using automated robotic concrete spraying. Computed deviation of the thickness achieved compared to that which was designed is included.

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    Apollo
    Dataset . 2022
    License: CC BY
    Data sources: Datacite
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      Apollo
      Dataset . 2022
      License: CC BY
      Data sources: Datacite
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  • Authors: Mercer, C.; Jump, A.; Morley, P.; O’Sullivan, K.; +2 Authors

    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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    Authors: Doukas, Haris; Spiliotis, Evangelos; Jafari, Mohsen A.; Giarola, Sara; +1 Authors

    This dataset contains the underlying data for the following publication: Doukas, H., Spiliotis, E., Jafari, M. A., Giarola, S. & Nikas, A. (2021). Low-cost emissions cuts in container shipping: Thinking inside the box. Transportation Research Part D: Transport and Environment, 94, 102815, https://doi.org/10.1016/j.trd.2021.102815.

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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: ZENODO
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      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: ZENODO
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    Authors: Ferreira, Igor José Malfetoni; Campanharo, Wesley Augusto; Fonseca, Marisa Gesteira; Escada, Maria Isabel Sobral; +7 Authors

    This file collection contains the estimated spatial distribution of the above-ground biomass density (AGB) by the end of the 21st century across the Brazilian Atlantic Forest domain and the respective uncertanty. To develop the models, we used the maximum entropy method with projected climate data to 2100, based on the Intergovernmental Panel on Climate Change (IPCC) Representative Concentration Pathway (RCP) 4.5 from the fifth Assessment Report (AR5). The dataset is composed of four files in GeoTIFF format: calibrated-AGB-distribution.tif: raster file representing the present spatial distribution of the above-ground biomass density in the Atlantic Forest from the calibrated model. Unit: Mg/ha estimated-uncertanty-for-calibrated-agb-distribution.tif: raster file representing the estimated spatial uncertanty distribution of the calibrated above-ground biomass density. Unit: percentage. projected-AGB-distribution-under-rcp45.tif: raster file representing the projected spatial distribution of the above-ground biomass density in the Atlantic Forest by the end of 2100 under RCP 4.5 scenario. Unit: Mg/ha estimated-uncertanty-for-projected-agb-distribution.tif: raster file representing the estimated spatial uncertanty distribution of the projected above-ground biomass density. Unit: percentage. Spatial resolution: 0.0083 degree (ca. 1 km) Coordinate reference system: Geographic Coordinate System - Datum WGS84

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    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: ZENODO
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    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: ZENODO
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      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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    Authors: Banu, Ioan Viorel; Istrate, Marcel;

    This dataset contains (1) the Simulink model of a three-phase photovoltaic power system with passive anti-islanding protections like over/under current (OUC), over/under voltage (OUV), over/under frequency (OUF), rate of change of frequency (ROCOF), and dc-link voltage and (2) the results in the voltage source converter and the point of common coupling of the photovoltaic system during islanding operation mode and detection times of analyzed anti-islanding methods. The dataset is related with the data used in the "DC-Link Voltage Anti-Islanding Method for Grid-Connected Photovoltaic Power Systems" manuscript submitted to IEEE Transactions on Smart Grid.

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    IEEE DataPort
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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      IEEE DataPort
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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    Authors: Ridley, Jeff; Menary, Matthew; Kuhlbrodt, Till; Andrews, Martin; +1 Authors

    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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    World Data Center for Climate
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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    World Data Center for Climate
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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      World Data Center for Climate
      Dataset . 2023
      License: CC BY
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      World Data Center for Climate
      Dataset . 2023
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    Authors: Horton, Tammy; Serpell-Stevens, Amanda; Domedel, Georgina Valls; Bett, Brian James;

    These data record the results of processing otter trawl catches (OTSB14; Merrett & Marshall, 1980) from the National Oceanography Centre (NOC, UK) long-term study of the Porcupine Abyssal Plain (PAP), including the PAP-Sustained Observatory time-series. The data concern catches recovered during the RRS Challenger cruise 135 in 1997. Billett, D.S.M. et al. (1998). RRS Challenger Cruise 135, 15 Oct-30 Oct 1997. BENGAL: High resolution temporal and spatial study of the BENthic biology and Geochemistry of a north-eastern Atlantic abyssal Locality. Southampton Oceanography Centre Cruise Report, No. 19, 49pp.| https://www.bodc.ac.uk/resources/inventories/cruise_inventory/reports/ch135_97.pdf

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    Global Biodiversity Information Facility
    Dataset . 2024
    License: CC BY
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      Global Biodiversity Information Facility
      Dataset . 2024
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    Authors: Hoffmann, Roman; Dimitrova, Anna; Muttarak, Raya; Crespo Cuaresma, Jesus; +1 Authors

    Complete replication data and code for article "A Meta-Analysis of Country Level Studies on Environmental Change and Migration". The rdata file contains both the meta and country level data. The data is also saved separately as xlsx files.

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    Harvard Dataverse
    Dataset . 2020
    License: CC 0
    Data sources: Datacite
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      Harvard Dataverse
      Dataset . 2020
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    Authors: Myrgiotis, Vasilis; Williams, Mathew;

    Model inputs, model code and aggregated model outputs (seasonal, annual) for every grassland field simulated (2017-2018) in "Myrgiotis et al. The carbon budget of the managed grasslands of Great Britain - informed by earth observations, Biogeosciences, 2022". Input files include (1) climate data (sitecode_M.npy) and (2) satellite based observations of Leaf Area Index (sitecode_O.pkl). Model code written in fortran. Model outputs (i.e. carbon pools, fluxes and balance for 2017 and 2018) aggregated annually (annual_outputs.csv) and monthly (annual_outputs.csv).

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    Edinburgh DataShare
    Dataset . 2022
    License: CC BY
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      Edinburgh DataShare
      Dataset . 2022
      License: CC BY
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    Authors: Fosas, Daniel; Nikolaidou, Elli; Roberts, Matt; Allen, Stephen; +2 Authors

    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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    University of Bath Research Data Archive
    Dataset . 2020
    License: CC BY
    Data sources: Datacite
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      University of Bath Research Data Archive
      Dataset . 2020
      License: CC BY
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    Authors: Nuh, Mishael;

    3D scans of two prototypes digitally fabricated using automated robotic concrete spraying. Computed deviation of the thickness achieved compared to that which was designed is included.

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    Apollo
    Dataset . 2022
    License: CC BY
    Data sources: Datacite
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      Apollo
      Dataset . 2022
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  • Authors: Mercer, C.; Jump, A.; Morley, P.; O’Sullivan, K.; +2 Authors

    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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