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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: Narayanasetti, Sandeep; Panickal, Swapna; Gopinathan, Prajeesh A.; Choudhury, Ayantika Dey; +2 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.ScenarioMIP.CCCR-IITM.IITM-ESM.ssp126' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The IITM-ESM climate model, released in 2015, includes the following components: aerosol: prescribed MAC-v2, atmos: IITM-GFSv1 (T62L64, Linearly Reduced Gaussian Grid; 192 x 94 longitude/latitude; 64 levels; top level 0.2 mb), land: NOAH LSMv2.7.1, ocean: MOM4p1 (tripolar, primarily 1deg; 360 x 200 longitude/latitude; 50 levels; top grid cell 0-10 m), ocnBgchem: TOPAZv2.0, seaIce: SISv1.0. The model was run by the Centre for Climate Change Research, Indian Institute of Tropical Meteorology Pune, Maharashtra 411 008, India (CCCR-IITM) in native nominal resolutions: aerosol: 250 km, atmos: 250 km, land: 250 km, ocean: 100 km, ocnBgchem: 100 km, seaIce: 100 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
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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/ World Data Center fo...arrow_drop_down
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      World Data Center for Climate
      Dataset . 2023
      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: Mitchell, Rachel; Natarajan, Sukumar;

    This dataset consists of hourly internal and daily external temperature data from 82 certified Passivhaus dwellings in the UK. The data can be used for calculating overheating risk and guaging how comfortable a home would be in the summer. This data come from 16 different sites and includes houses and flats. Some of the data is from the living room only, for other dwellings there were sensors in muitple rooms and these are indicated. As this data was compared to CIBSE TM59 "Design methodology for the assessment of overheating risk in homes", there is a calculation of the running mean temperature and maximum temperature. The variables are Timestamp = time and date SiteID = Site number (1-16) DWType = dwelling type (House or Flat) HouseID = unique reference number for each dwelling in dataset Room = room type LR = living room , BR= bedroom, KI= Kitchen, BT= bathroom T.int = internal temperature (mean hourly) T.ext.daily = external temperature (mean daily) T.rm = running mean temperature calculated using the method described in CIBSE TM59 T.max = maximum daily intenral temperature calculated using the method described in CIBSE TM59 This data was provided by the Technology Stratergy Board Building Performance Evaluation Program, and is available from the digital catapault. Other data was provided by WARM low energy Consultancy and indidiual home owners. All data has been anonymised

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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: Gebruk, Anna; Dgebuadze, Polina; Rogozhin, Vladimir; Ermilova, Yulia; +2 Authors

    The dataset comprises full list of species of macrozoobenthos collected from the Pechora Sea (SE Barents Sea). Grab samples were collected from 10 stations in the Pechora Bay from aboard RV Kartesh in 2020-2021. Macrobenthic invertebrates were identified with the maximum level of certainty through optical microscopy using regional taxonomic keys. All taxonomic names were standardised using the World Register of Marine Species (WoRMS). All specimens have been counted and weighted (wet biomass) on Ohaus Adventurer scales with reported accuracy to 0.01 g. Bivalve molluscs and gastropods were weighed in shells. Biomass (g. m-2) and abundance (ind m-2) are used to characterise macrozoobenthos. The sampling and identification work was carried out in collaboration with specialists from Lomonosov Moscow State University Marine Research Center and P.P. Shirshov Institute of Oceanology.

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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: Neubauer, David; Ferrachat, Sylvaine; Siegenthaler-Le Drian, Colombe; Stoll, Jens; +18 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.AerChemMIP.HAMMOZ-Consortium.MPI-ESM-1-2-HAM' 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 MPI-ESM1.2-HAM climate model, released in 2017, includes the following components: aerosol: HAM2.3, atmos: ECHAM6.3 (spectral T63; 192 x 96 longitude/latitude; 47 levels; top level 0.01 hPa), atmosChem: sulfur chemistry (unnamed), land: JSBACH 3.20, ocean: MPIOM1.63 (bipolar GR1.5, approximately 1.5deg; 256 x 220 longitude/latitude; 40 levels; top grid cell 0-12 m), ocnBgchem: HAMOCC6, seaIce: unnamed (thermodynamic (Semtner zero-layer) dynamic (Hibler 79) sea ice model). The model was run by the ETH Zurich, Switzerland; Max Planck Institut fur Meteorologie, Germany; Forschungszentrum Julich, Germany; University of Oxford, UK; Finnish Meteorological Institute, Finland; Leibniz Institute for Tropospheric Research, Germany; Center for Climate Systems Modeling (C2SM) at ETH Zurich, Switzerland (HAMMOZ-Consortium) in native nominal resolutions: aerosol: 250 km, atmos: 250 km, atmosChem: 250 km, land: 250 km, ocean: 250 km, ocnBgchem: 250 km, seaIce: 250 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
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      World Data Center for Climate
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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    Authors: Chen, Bingzhang; Montagnes, David; Wang, Qing; Liu, Hongbin; +1 Authors

    Conventional analyses suggest the metabolism of heterotrophs is thermally more sensitive than that of autotrophs, implying that warming leads to pronounced trophodynamic imbalances. However, these analyses inappropriately combine within- and across-taxa trends. We present a novel mathematic framework to separate these, revealing that the higher temperature sensitivity of heterotrophs is mainly caused by within-taxa responses which account for 92% of the difference between autotrophic and heterotrophic protists. This dataset contains both the datasets and R codes of per capita growth rates of autotrophic and heterotrophic protists as well as heterotrophic bacteria and insects. The datasets of per capita growth rates against temperature were compiled from the literature. Experimental data were included if they met the following criteria: at least 3 data points with positive growth rate (µ) and at least 2 unique temperatures at which positive µ were measured. To calculate apparent activation energy, we also removed data points with nonpositive µ and those with temperatures above the optimal growth temperature (defined as the temperature corresponding to the maximal µ). We use the free software R (version 4.2.0) with R packages (foreach, nlme, plyr, dplyr) to analyse these datasets. R codes are also provided.

    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 . 2022
    License: CC 0
    Data sources: ZENODO
    DRYAD
    Dataset . 2022
    License: CC 0
    Data sources: Datacite
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      ZENODO
      Dataset . 2022
      License: CC 0
      Data sources: ZENODO
      DRYAD
      Dataset . 2022
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      Data sources: Datacite
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    Authors: Lewis-Brown, Emily; Mills, Morena; Ewers, Robert M; Jennings, Neil; +1 Authors

    Survey used and data gathered for research into adoption of carbon management strategies amongst universities 2022, which forms part of a PhD thesis and will be submitted for publication in a journal.

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    ZENODO
    Dataset . 2022
    License: CC BY
    Data sources: ZENODO
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    ZENODO
    Dataset . 2022
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    Data sources: Datacite
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    ZENODO
    Dataset . 2022
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    Data sources: Datacite
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      ZENODO
      Dataset . 2022
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      ZENODO
      Dataset . 2022
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      ZENODO
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    Authors: Garner, Gregory; Hermans, Tim H.J.; Kopp, Robert; Slangen, Aimée; +22 Authors

    Project: IPCC Data Distribution Centre : Supplementary data sets for the Sixth Assessment Report - For the Sixth Assessment Report of the IPCC (AR6) input/source and intermediate datasets underlying the AR6 were collected and long-term archived. This project compliments CMIP6 data subset and snapshot analyzed for the WGI AR6. Summary: This data set contains detailed elements the sea level projections associated with the Intergovernmental Panel on Climate Change Sixth Assessment Report. In particular, it contains relative sea level projections that exclude the background term (representing primarily land subsidence or uplift). It includes probability distributions for all the workflows described in AR6 WGI 9.6.3.2. P-boxes derived from these distributions are available in the sister entry 'IPCC-DDC_AR6_Sup_PBox'. These data may be of use for users who want to substitute their own estimates of the background term. Regional projections can also be accessed through the NASA/IPCC Sea Level Projections Tool at https://sealevel.nasa.gov/ipcc-ar6-sea-level-projection-tool. See https://zenodo.org/communities/ipcc-ar6-sea-level-projections for additional related data sets.

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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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    Authors: McAuliffe, Thomas P; Foden, Alexander; Bilsland, Chris; Daskalaki-Mountanou, Dafni; +2 Authors

    Prepared by Tom McAuliffe (t.mcauliffe17@imperial.ac.uk) This repository is a release of the raw data and analysis results for: 'Advancing characterisation with statistics from correlative electron diffraction and X-ray spectroscopy, in the scanning electron microscope' https://doi.org/10.1016/j.ultramic.2020.112944 The raw data is given as 'RawData.h5' - this contains patterns, spectra, and metadata in the Bruker-exported format. Outputs of our analysis code (which will be made available via AstroEBSD) are contained in 'PCA_Outputs' subfolders. Exported plots and .mat results files are contained within. These are organised by Figure number in the paper. The provided results are divided into two major sections: (1) Variation in the variance tolerance limit (and corresponding numbers of retained components), and the weighting of the PCA in favour of EBSD or EDS information. RCCs are validated by cross-correlation with the corresponding raw data point pattern and/or spectrum. (2) Full outputs of PCA analysis having varied the weighting parameter. This contains IPF maps, quantified chemical maps, PC scores, and label maps.

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    ZENODO
    Dataset . 2020
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2020
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2020
    License: CC BY
    Data sources: ZENODO
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      ZENODO
      Dataset . 2020
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2020
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2020
      License: CC BY
      Data sources: ZENODO
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    Authors: Good, Peter; Sellar, Alistair; Tang, Yongming; Rumbold, Steve; +3 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.ScenarioMIP.MOHC.UKESM1-0-LL.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 UKESM1.0-N96ORCA1 climate model, released in 2018, includes the following components: aerosol: UKCA-GLOMAP-mode, atmos: MetUM-HadGEM3-GA7.1 (N96; 192 x 144 longitude/latitude; 85 levels; top level 85 km), atmosChem: UKCA-StratTrop, land: JULES-ES-1.0, ocean: NEMO-HadGEM3-GO6.0 (eORCA1 tripolar primarily 1 deg with meridional refinement down to 1/3 degree in the tropics; 360 x 330 longitude/latitude; 75 levels; top grid cell 0-1 m), ocnBgchem: MEDUSA2, seaIce: CICE-HadGEM3-GSI8 (eORCA1 tripolar primarily 1 deg; 360 x 330 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: 250 km, atmos: 250 km, atmosChem: 250 km, land: 250 km, ocean: 100 km, ocnBgchem: 100 km, seaIce: 100 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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    Authors: Niblett, Samuel; Biedermann, M; Wales, David; de Souza, Vanessa;

    Archive files containing the input files and (where relevant) source code to reproduce data on the dynamics and energy landscape of supercooled silica. The main components of the repository are as follows: source code and input files for producing MD trajectories for binary Lennard-Jones and BKS silica systems as used in the code, python scripts for analysing these trajectories, source code for identifying cage-breaking transitions in quenched trajectories, input files for the Cambridge Energy Landscape Software used to generate the landscape databases, and scripts for analysing those databases.

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    Apollo
    Dataset . 2017
    License: CC BY
    Data sources: Datacite
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    Apollo
    Dataset . 2017
    License: CC BY
    Data sources: Apollo
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      Apollo
      Dataset . 2017
      License: CC BY
      Data sources: Datacite
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      Apollo
      Dataset . 2017
      License: CC BY
      Data sources: Apollo
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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: Narayanasetti, Sandeep; Panickal, Swapna; Gopinathan, Prajeesh A.; Choudhury, Ayantika Dey; +2 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.ScenarioMIP.CCCR-IITM.IITM-ESM.ssp126' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The IITM-ESM climate model, released in 2015, includes the following components: aerosol: prescribed MAC-v2, atmos: IITM-GFSv1 (T62L64, Linearly Reduced Gaussian Grid; 192 x 94 longitude/latitude; 64 levels; top level 0.2 mb), land: NOAH LSMv2.7.1, ocean: MOM4p1 (tripolar, primarily 1deg; 360 x 200 longitude/latitude; 50 levels; top grid cell 0-10 m), ocnBgchem: TOPAZv2.0, seaIce: SISv1.0. The model was run by the Centre for Climate Change Research, Indian Institute of Tropical Meteorology Pune, Maharashtra 411 008, India (CCCR-IITM) in native nominal resolutions: aerosol: 250 km, atmos: 250 km, land: 250 km, ocean: 100 km, ocnBgchem: 100 km, seaIce: 100 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
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    Authors: Mitchell, Rachel; Natarajan, Sukumar;

    This dataset consists of hourly internal and daily external temperature data from 82 certified Passivhaus dwellings in the UK. The data can be used for calculating overheating risk and guaging how comfortable a home would be in the summer. This data come from 16 different sites and includes houses and flats. Some of the data is from the living room only, for other dwellings there were sensors in muitple rooms and these are indicated. As this data was compared to CIBSE TM59 "Design methodology for the assessment of overheating risk in homes", there is a calculation of the running mean temperature and maximum temperature. The variables are Timestamp = time and date SiteID = Site number (1-16) DWType = dwelling type (House or Flat) HouseID = unique reference number for each dwelling in dataset Room = room type LR = living room , BR= bedroom, KI= Kitchen, BT= bathroom T.int = internal temperature (mean hourly) T.ext.daily = external temperature (mean daily) T.rm = running mean temperature calculated using the method described in CIBSE TM59 T.max = maximum daily intenral temperature calculated using the method described in CIBSE TM59 This data was provided by the Technology Stratergy Board Building Performance Evaluation Program, and is available from the digital catapault. Other data was provided by WARM low energy Consultancy and indidiual home owners. All data has been anonymised

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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
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    Authors: Gebruk, Anna; Dgebuadze, Polina; Rogozhin, Vladimir; Ermilova, Yulia; +2 Authors

    The dataset comprises full list of species of macrozoobenthos collected from the Pechora Sea (SE Barents Sea). Grab samples were collected from 10 stations in the Pechora Bay from aboard RV Kartesh in 2020-2021. Macrobenthic invertebrates were identified with the maximum level of certainty through optical microscopy using regional taxonomic keys. All taxonomic names were standardised using the World Register of Marine Species (WoRMS). All specimens have been counted and weighted (wet biomass) on Ohaus Adventurer scales with reported accuracy to 0.01 g. Bivalve molluscs and gastropods were weighed in shells. Biomass (g. m-2) and abundance (ind m-2) are used to characterise macrozoobenthos. The sampling and identification work was carried out in collaboration with specialists from Lomonosov Moscow State University Marine Research Center and P.P. Shirshov Institute of Oceanology.

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    Authors: Neubauer, David; Ferrachat, Sylvaine; Siegenthaler-Le Drian, Colombe; Stoll, Jens; +18 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.AerChemMIP.HAMMOZ-Consortium.MPI-ESM-1-2-HAM' 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 MPI-ESM1.2-HAM climate model, released in 2017, includes the following components: aerosol: HAM2.3, atmos: ECHAM6.3 (spectral T63; 192 x 96 longitude/latitude; 47 levels; top level 0.01 hPa), atmosChem: sulfur chemistry (unnamed), land: JSBACH 3.20, ocean: MPIOM1.63 (bipolar GR1.5, approximately 1.5deg; 256 x 220 longitude/latitude; 40 levels; top grid cell 0-12 m), ocnBgchem: HAMOCC6, seaIce: unnamed (thermodynamic (Semtner zero-layer) dynamic (Hibler 79) sea ice model). The model was run by the ETH Zurich, Switzerland; Max Planck Institut fur Meteorologie, Germany; Forschungszentrum Julich, Germany; University of Oxford, UK; Finnish Meteorological Institute, Finland; Leibniz Institute for Tropospheric Research, Germany; Center for Climate Systems Modeling (C2SM) at ETH Zurich, Switzerland (HAMMOZ-Consortium) in native nominal resolutions: aerosol: 250 km, atmos: 250 km, atmosChem: 250 km, land: 250 km, ocean: 250 km, ocnBgchem: 250 km, seaIce: 250 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
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    Authors: Chen, Bingzhang; Montagnes, David; Wang, Qing; Liu, Hongbin; +1 Authors

    Conventional analyses suggest the metabolism of heterotrophs is thermally more sensitive than that of autotrophs, implying that warming leads to pronounced trophodynamic imbalances. However, these analyses inappropriately combine within- and across-taxa trends. We present a novel mathematic framework to separate these, revealing that the higher temperature sensitivity of heterotrophs is mainly caused by within-taxa responses which account for 92% of the difference between autotrophic and heterotrophic protists. This dataset contains both the datasets and R codes of per capita growth rates of autotrophic and heterotrophic protists as well as heterotrophic bacteria and insects. The datasets of per capita growth rates against temperature were compiled from the literature. Experimental data were included if they met the following criteria: at least 3 data points with positive growth rate (µ) and at least 2 unique temperatures at which positive µ were measured. To calculate apparent activation energy, we also removed data points with nonpositive µ and those with temperatures above the optimal growth temperature (defined as the temperature corresponding to the maximal µ). We use the free software R (version 4.2.0) with R packages (foreach, nlme, plyr, dplyr) to analyse these datasets. R codes are also provided.

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    ZENODO
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    DRYAD
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      ZENODO
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      DRYAD
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    Authors: Lewis-Brown, Emily; Mills, Morena; Ewers, Robert M; Jennings, Neil; +1 Authors

    Survey used and data gathered for research into adoption of carbon management strategies amongst universities 2022, which forms part of a PhD thesis and will be submitted for publication in a journal.

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    ZENODO
    Dataset . 2022
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    ZENODO
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    ZENODO
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      ZENODO
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      ZENODO
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      ZENODO
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    Authors: Garner, Gregory; Hermans, Tim H.J.; Kopp, Robert; Slangen, Aimée; +22 Authors

    Project: IPCC Data Distribution Centre : Supplementary data sets for the Sixth Assessment Report - For the Sixth Assessment Report of the IPCC (AR6) input/source and intermediate datasets underlying the AR6 were collected and long-term archived. This project compliments CMIP6 data subset and snapshot analyzed for the WGI AR6. Summary: This data set contains detailed elements the sea level projections associated with the Intergovernmental Panel on Climate Change Sixth Assessment Report. In particular, it contains relative sea level projections that exclude the background term (representing primarily land subsidence or uplift). It includes probability distributions for all the workflows described in AR6 WGI 9.6.3.2. P-boxes derived from these distributions are available in the sister entry 'IPCC-DDC_AR6_Sup_PBox'. These data may be of use for users who want to substitute their own estimates of the background term. Regional projections can also be accessed through the NASA/IPCC Sea Level Projections Tool at https://sealevel.nasa.gov/ipcc-ar6-sea-level-projection-tool. See https://zenodo.org/communities/ipcc-ar6-sea-level-projections for additional related data sets.

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    World Data Center for Climate
    Dataset . 2023
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      World Data Center for Climate
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    Authors: McAuliffe, Thomas P; Foden, Alexander; Bilsland, Chris; Daskalaki-Mountanou, Dafni; +2 Authors

    Prepared by Tom McAuliffe (t.mcauliffe17@imperial.ac.uk) This repository is a release of the raw data and analysis results for: 'Advancing characterisation with statistics from correlative electron diffraction and X-ray spectroscopy, in the scanning electron microscope' https://doi.org/10.1016/j.ultramic.2020.112944 The raw data is given as 'RawData.h5' - this contains patterns, spectra, and metadata in the Bruker-exported format. Outputs of our analysis code (which will be made available via AstroEBSD) are contained in 'PCA_Outputs' subfolders. Exported plots and .mat results files are contained within. These are organised by Figure number in the paper. The provided results are divided into two major sections: (1) Variation in the variance tolerance limit (and corresponding numbers of retained components), and the weighting of the PCA in favour of EBSD or EDS information. RCCs are validated by cross-correlation with the corresponding raw data point pattern and/or spectrum. (2) Full outputs of PCA analysis having varied the weighting parameter. This contains IPF maps, quantified chemical maps, PC scores, and label maps.

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    ZENODO
    Dataset . 2020
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    ZENODO
    Dataset . 2020
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    ZENODO
    Dataset . 2020
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      Dataset . 2020
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      ZENODO
      Dataset . 2020
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      ZENODO
      Dataset . 2020
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    Authors: Good, Peter; Sellar, Alistair; Tang, Yongming; Rumbold, Steve; +3 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.ScenarioMIP.MOHC.UKESM1-0-LL.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 UKESM1.0-N96ORCA1 climate model, released in 2018, includes the following components: aerosol: UKCA-GLOMAP-mode, atmos: MetUM-HadGEM3-GA7.1 (N96; 192 x 144 longitude/latitude; 85 levels; top level 85 km), atmosChem: UKCA-StratTrop, land: JULES-ES-1.0, ocean: NEMO-HadGEM3-GO6.0 (eORCA1 tripolar primarily 1 deg with meridional refinement down to 1/3 degree in the tropics; 360 x 330 longitude/latitude; 75 levels; top grid cell 0-1 m), ocnBgchem: MEDUSA2, seaIce: CICE-HadGEM3-GSI8 (eORCA1 tripolar primarily 1 deg; 360 x 330 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: 250 km, atmos: 250 km, atmosChem: 250 km, land: 250 km, ocean: 100 km, ocnBgchem: 100 km, seaIce: 100 km.

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    World Data Center for Climate
    Dataset . 2023
    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/ World Data Center fo...arrow_drop_down
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      World Data Center for Climate
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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    Authors: Niblett, Samuel; Biedermann, M; Wales, David; de Souza, Vanessa;

    Archive files containing the input files and (where relevant) source code to reproduce data on the dynamics and energy landscape of supercooled silica. The main components of the repository are as follows: source code and input files for producing MD trajectories for binary Lennard-Jones and BKS silica systems as used in the code, python scripts for analysing these trajectories, source code for identifying cage-breaking transitions in quenched trajectories, input files for the Cambridge Energy Landscape Software used to generate the landscape databases, and scripts for analysing those databases.

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    Apollo
    Dataset . 2017
    License: CC BY
    Data sources: Datacite
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    Apollo
    Dataset . 2017
    License: CC BY
    Data sources: Apollo
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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/ Apolloarrow_drop_down
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      Apollo
      Dataset . 2017
      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/
      Apollo
      Dataset . 2017
      License: CC BY
      Data sources: Apollo
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