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  • 11. Sustainability

  • 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: Paula Castesana (11024216); Melisa Diaz Resquin (11024219); Sabine Darras (11024222); Darío Gómez (11024225); +6 Authors

    PAPILA dataset is a collection of annual emission inventories of reactive gases (CO, NOx, NMVOCs, NH3 and SO2) from anthropogenic sources in South America, for the period 2014–2016. The dataset was developed on the basis of the existing data on the global dataset CAMS-GLOB-ANT v4.1 (developed by joining CEDS trends and EDGARv4.3.2 historical data), enriching it with derived data from locally available emission inventories for Argentina, Chile and Colombia. The inventories are presented as NetCDF4 files, one for each species and year, gridded with a spatial resolution of 0.1° x 0.1° covering the domain 32° W–120° W and 34° N–58° S. Each file contains 12 variables corresponding to the emissions in Tg/y from the following categories, which are organized and denominated using the nomenclature given by CAMS: thermal power plants (ENE); residential and commercial combustion (RES); road transportation (TRO); non-road transportation (TNR); fugitive emissions (FEF); industries (including fuel consumption in manufacturing industries and construction, refineries, industrial processes and solvent and other products use) (IND); agricultural soils (AGS); agriculture livestock (AGL); inland navigation (SHP); international navigation (SHP-INT); waste (including solid waste, wastewater and incineration) (SWD); and the sum of all sectors (SUM).

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    Mendeley Data
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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    Mendeley Data
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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    Mendeley Data
    Dataset . 2021
    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/
    Mendeley Data
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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    B2FIND
    Dataset . 2021
    Data sources: B2FIND
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    B2FIND
    Dataset . 2021
    Data sources: B2FIND
    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/
    B2FIND
    Dataset . 2021
    Data sources: B2FIND
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    Smithsonian figshare
    Dataset . 2021
    License: CC BY
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    Smithsonian figshare
    Dataset . 2021
    License: CC BY
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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/ Mendeley Dataarrow_drop_down
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      Mendeley Data
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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      Mendeley Data
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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      Mendeley Data
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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      Mendeley Data
      Dataset . 2021
      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/
      B2FIND
      Dataset . 2021
      Data sources: B2FIND
      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/
      B2FIND
      Dataset . 2021
      Data sources: B2FIND
      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/
      B2FIND
      Dataset . 2021
      Data sources: B2FIND
      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/
      Smithsonian figshare
      Dataset . 2021
      License: CC BY
      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/
      Smithsonian figshare
      Dataset . 2021
      License: CC BY
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    Authors: Reidy, Jennifer; Sinnott, Emily; Thompson, Frank; O'Donnell, Lisa;

    We monitored golden-cheeked warbler territories in 10 plots within an urban preserve to determine abundance, delineate territories, and document breeding success. We determined environmental conditions across the study period to examine temporal and landscape effects. We then used these data to estimate adult survival and productivity and relate these vital rates to environmental conditions experienced during our study period. We used supported covariates to predict potential effects on this population 25 years into the future. These data and code are associated with the publication in Ecosphere entitled "Urban land cover and El Nino events negatively impact population viability of an endangered North American songbird." We performed an integrated population model to evaluate the effect of climate patterns and urban land cover on the viability of an endangered wood-warbler breeding in central Texas. We used territory monitroing data from 2011–2019 to predict viability of the population 25 years into the future. We assembled and conducted the analysis in R.

    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 . 2023
    License: CC 0
    Data sources: ZENODO
    DRYAD
    Dataset . 2023
    License: CC 0
    Data sources: Datacite
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      ZENODO
      Dataset . 2023
      License: CC 0
      Data sources: ZENODO
      DRYAD
      Dataset . 2023
      License: CC 0
      Data sources: Datacite
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    Authors: Pflüger, Mika; Gütschow, Johannes;

    Dataset containing all greenhouse gas emissions data submitted by countries under climate change convention (including CRF data) as published by the UNFCCC secretariat at 2024-07-05. Changes in this version compared to version 2024-07-04: No data changes. Provide the full dataset as a single parquet file instead of a collection of parquet files in a zip file. The dataset is also available via datalad. To obtain the dataset with datalad, see the instructions at https://github.com/mikapfl/unfccc_di_data .

    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 . 2024
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2024
    License: CC BY
    Data sources: ZENODO
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    ZENODO
    Dataset . 2024
    License: CC BY
    Data sources: Datacite
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    BIP!Powered by BIP!
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    downloaddownloads156
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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
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      ZENODO
      Dataset . 2024
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2024
      License: CC BY
      Data sources: ZENODO
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      ZENODO
      Dataset . 2024
      License: CC BY
      Data sources: Datacite
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    Authors: Jackson, Laura;

    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.HadGEM3-GC31-MM.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 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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    Authors: Guo, Chuncheng; Bentsen, Mats; Bethke, Ingo; Ilicak, Mehmet; +4 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.PMIP.NCC.NorESM1-F' 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 NorESM1-F (a fast version of NorESM that is designed for paleo and multi-ensemble simulations) climate model, released in 2018, includes the following components: atmos: CAM4 (2 degree resolution; 144 x 96; 32 levels; top level 3 mb), land: CLM4, landIce: CISM, ocean: MICOM (1 degree resolution; 360 x 384; 70 levels; top grid cell minimum 0-2.5 m [native model uses hybrid density and generic upper-layer coordinate interpolated to z-level for contributed data]), ocnBgchem: HAMOCC5.1, seaIce: CICE4. The model was run by the NorESM Climate modeling Consortium consisting of CICERO (Center for International Climate and Environmental Research, Oslo 0349), MET-Norway (Norwegian Meteorological Institute, Oslo 0313), NERSC (Nansen Environmental and Remote Sensing Center, Bergen 5006), NILU (Norwegian Institute for Air Research, Kjeller 2027), UiB (University of Bergen, Bergen 5007), UiO (University of Oslo, Oslo 0313) and UNI (Uni Research, Bergen 5008), Norway. Mailing address: NCC, c/o MET-Norway, Henrik Mohns plass 1, Oslo 0313, Norway (NCC) in native nominal resolutions: atmos: 250 km, land: 250 km, landIce: 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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      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: Schupfner, Martin; Wieners, Karl-Hermann; Wachsmann, Fabian; Steger, Christian; +47 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.DKRZ.MPI-ESM1-2-HR.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 MPI-ESM1.2-HR climate model, released in 2017, includes the following components: aerosol: none, prescribed MACv2-SP, atmos: ECHAM6.3 (spectral T127; 384 x 192 longitude/latitude; 95 levels; top level 0.01 hPa), land: JSBACH3.20, landIce: none/prescribed, ocean: MPIOM1.63 (tripolar TP04, approximately 0.4deg; 802 x 404 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 Deutsches Klimarechenzentrum, Hamburg 20146, Germany (DKRZ) in native nominal resolutions: aerosol: 100 km, atmos: 100 km, land: 100 km, landIce: none, ocean: 50 km, ocnBgchem: 50 km, seaIce: 50 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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    This dataset contains the data displayed in the figures or the article "High-resolution projections of ambient heat for major European cities using different heat metrics". The different files contain: Data_Fig1_DeltaTXx_EURO-CORDEX_1981-2010_to_3K-European-warming_RCP85.nc: Change of yearly maximum temperature in Europe between 1981-2010 and 3 °C European warming relative to 1981-2010. Data_Fig2_timeseries-GSAT-ESAT_EURO-CORDEX_CMIP5_CMIP6_1971-2100_RCP85_SSP585.xlsx: Time series of global mean surface air temperature (GSAT) for CMIP5 and CMIP6 models, and for European mean surface air temperature (ESAT) for EURO-CORDEX, CMIP5, and CMIP6 models for the period 1971-2100. Data_Fig3_TX-distribution_distance-from-city-centre_E-OBS_1981-2010.xlsx: Distribution of average daily maximum temperature in summer (June, July, August) in 1981-2010 for E-OBS for all investigated cities. Temperature data are indicated as a function of the distance to the city centre. Data_Fig3_TX-distribution_distance-from-city-centre_ERA5-Land_1981-2010.xlsx: Distribution of average daily maximum temperature in summer (June, July, August) in 1981-2010 for ERA5-Land for all investigated cities. Temperature data are indicated as a function of the distance to the city centre. Data_Fig3_TX-distribution_distance-from-city-centre_EURO-CORDEX_1981-2010.xlsx: Distribution of average daily maximum temperature in summer (June, July, August) in 1981-2010 for the EURO-CORDEX models for all investigated cities. Temperature data are indicated as a function of the distance to the city centre. Data_Fig3_TX-distribution_distance-from-city-centre_weather-stations_1981-2010.xlsx: Distribution of average daily maximum temperature in summer (June, July, August) in 1981-2010 for GSOD and ECA&D stations for all investigated cities. Temperature data are indicated as a function of the distance to the city centre. Data_Fig4_TX-ambient-heat_EURO-CORDEX_3K-European-warming.xlsx: Daytime heat metrics for the investigated cities: HWMId-TX at 3 °C European warming relative to 1981-2010, TX exceedances above 30 °C at 3 °C European warming relative to 1981-2010, and TXx change between 1981-2010 and 3 °C European warming relative to 1981-2010 for EURO-CORDEX models. Data_Fig5_Contribution-of-explanatory-variables-to-total-explained-variance.xlsx: Contribution of different explanatory variables (climate and location factors) to the total explained variance of spatial patterns of heat metrics. Data_Fig6_TN-ambient-heat_EURO-CORDEX_3K-European-warming.xlsx: Nighttime heat metrics for the investigated cities: HWMId-TN at 3 °C European warming relative to 1981-2010, TN exceedances above 20 °C at 3 °C European warming relative to 1981-2010, and TNx change between 1981-2010 and 3 °C European warming relative to 1981-2010 for EURO-CORDEX models. Data_Fig7_TX-ambient-heat_CMIP5_3K-European-warming.xlsx: Daytime heat metrics for the investigated cities: HWMId-TX at 3 °C European warming relative to 1981-2010, TX exceedances above 30 °C at 3 °C European warming relative to 1981-2010, and TXx change between 1981-2010 and 3 °C European warming relative to 1981-2010 for CMIP5 models. Data_Fig7_TX-ambient-heat_CMIP6_3K-European-warming.xlsx: Daytime heat metrics for the investigated cities: HWMId-TX at 3 °C European warming relative to 1981-2010, TX exceedances above 30 °C at 3 °C European warming relative to 1981-2010, and TXx change between 1981-2010 and 3 °C European warming relative to 1981-2010 for CMIP6 models. Data_Fig8_GCM-RCM-matrix_ambient-heat_3K-European-warming.xlsx: GCM-RCM matrices for the three heat metrics.

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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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      ZENODO
      Dataset . 2023
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      Data sources: Datacite
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      ZENODO
      Dataset . 2023
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      Data sources: ZENODO
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    This file contains the data and the STATA estimation code to replicate the results in the article entitled: "Information Communication Technology development and energy demand in African countries".

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    Mendeley Data
    Dataset . 2019
    License: CC BY
    Data sources: Datacite
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    Mendeley Data
    Dataset . 2019
    License: CC BY
    Data sources: Datacite
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    Mendeley Data
    Dataset . 2019
    License: CC BY
    Data sources: Datacite
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    Mendeley Data
    Dataset . 2019
    License: CC BY
    Data sources: Datacite
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    B2FIND
    Dataset . 2019
    Data sources: B2FIND
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      Mendeley Data
      Dataset . 2019
      License: CC BY
      Data sources: Datacite
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      Mendeley Data
      Dataset . 2019
      License: CC BY
      Data sources: Datacite
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      Mendeley Data
      Dataset . 2019
      License: CC BY
      Data sources: Datacite
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      Mendeley Data
      Dataset . 2019
      License: CC BY
      Data sources: Datacite
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      B2FIND
      Dataset . 2019
      Data sources: B2FIND
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    Authors: María de la Paz Diulio (10410087); Gabriela Reus Netto (10410090); Roberto Berardi (75497); Jorge Daniel Czajkowski (10410093);

    Abstract The metropolitan area of La Plata, Argentina, represents 1.6% of households in Argentina. Based on the analysis of the energy retrofit of a house, we provide indicators in order to propose a methodology that facilitates the extrapolation, at regional level, of the impact of a general energy retrofit in homes. The results obtained are presented from micro to macro level, in context of energy shortage and recurrent crisis in the supply of fuels and electricity in Argentina. The improved thermal resistance of walls and ceilings throughout the residential park of La Plata lead to a reduction of 12% of the energy consumed in heating, and a saving of 30,000 TEP / year. We conclude that the incidence of additional insulation on the cost of building justifies its use, partially solving the lack of fuel in our country, reducing fixed costs in housing, providing thermal comfort to users and generating economic reactivation of the construction sector.

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    figshare
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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    figshare
    Dataset . 2021
    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/
    Smithsonian figshare
    Dataset . 2016
    License: CC BY
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      figshare
      Dataset . 2021
      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/
      figshare
      Dataset . 2021
      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/
      Smithsonian figshare
      Dataset . 2016
      License: CC BY
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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/

    This data presents an experimental investigation carried out in a Boundary Layer Wind Tunnel located at Ruhr University Bochum, Germany. The flow field is measured above the rooftop of a high-rise building with a square cross-section considering two different roof shapes, flat roof and deck roof. The height-to-width ratio of the building was 1:3. The main purpose is to be used for estimation of urban wind energy potential, and besides for future validation of computational fluid dynamic simulations. Besides velocity field, measured at mainly three positions above the roof, the roof surface pressure was also measured. The flow above the roof was measured for different wind angles: 0°, 15°, 30°, and 45°.

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    Mendeley Data
    Dataset . 2020
    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/
    Mendeley Data
    Dataset . 2020
    License: CC BY
    Data sources: Datacite
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      Mendeley Data
      Dataset . 2020
      License: CC BY
      Data sources: Datacite
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      Mendeley Data
      Dataset . 2020
      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: Paula Castesana (11024216); Melisa Diaz Resquin (11024219); Sabine Darras (11024222); Darío Gómez (11024225); +6 Authors

    PAPILA dataset is a collection of annual emission inventories of reactive gases (CO, NOx, NMVOCs, NH3 and SO2) from anthropogenic sources in South America, for the period 2014–2016. The dataset was developed on the basis of the existing data on the global dataset CAMS-GLOB-ANT v4.1 (developed by joining CEDS trends and EDGARv4.3.2 historical data), enriching it with derived data from locally available emission inventories for Argentina, Chile and Colombia. The inventories are presented as NetCDF4 files, one for each species and year, gridded with a spatial resolution of 0.1° x 0.1° covering the domain 32° W–120° W and 34° N–58° S. Each file contains 12 variables corresponding to the emissions in Tg/y from the following categories, which are organized and denominated using the nomenclature given by CAMS: thermal power plants (ENE); residential and commercial combustion (RES); road transportation (TRO); non-road transportation (TNR); fugitive emissions (FEF); industries (including fuel consumption in manufacturing industries and construction, refineries, industrial processes and solvent and other products use) (IND); agricultural soils (AGS); agriculture livestock (AGL); inland navigation (SHP); international navigation (SHP-INT); waste (including solid waste, wastewater and incineration) (SWD); and the sum of all sectors (SUM).

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    Mendeley Data
    Dataset . 2021
    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/
    Mendeley Data
    Dataset . 2021
    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/
    Mendeley Data
    Dataset . 2021
    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/
    Mendeley Data
    Dataset . 2021
    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/
    B2FIND
    Dataset . 2021
    Data sources: B2FIND
    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/
    B2FIND
    Dataset . 2021
    Data sources: B2FIND
    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/
    B2FIND
    Dataset . 2021
    Data sources: B2FIND
    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/
    Smithsonian figshare
    Dataset . 2021
    License: CC BY
    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/
    Smithsonian figshare
    Dataset . 2021
    License: CC BY
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      Mendeley Data
      Dataset . 2021
      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/
      Mendeley Data
      Dataset . 2021
      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/
      Mendeley Data
      Dataset . 2021
      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/
      Mendeley Data
      Dataset . 2021
      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/
      B2FIND
      Dataset . 2021
      Data sources: B2FIND
      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/
      B2FIND
      Dataset . 2021
      Data sources: B2FIND
      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/
      B2FIND
      Dataset . 2021
      Data sources: B2FIND
      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/
      Smithsonian figshare
      Dataset . 2021
      License: CC BY
      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/
      Smithsonian figshare
      Dataset . 2021
      License: CC BY
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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: Reidy, Jennifer; Sinnott, Emily; Thompson, Frank; O'Donnell, Lisa;

    We monitored golden-cheeked warbler territories in 10 plots within an urban preserve to determine abundance, delineate territories, and document breeding success. We determined environmental conditions across the study period to examine temporal and landscape effects. We then used these data to estimate adult survival and productivity and relate these vital rates to environmental conditions experienced during our study period. We used supported covariates to predict potential effects on this population 25 years into the future. These data and code are associated with the publication in Ecosphere entitled "Urban land cover and El Nino events negatively impact population viability of an endangered North American songbird." We performed an integrated population model to evaluate the effect of climate patterns and urban land cover on the viability of an endangered wood-warbler breeding in central Texas. We used territory monitroing data from 2011–2019 to predict viability of the population 25 years into the future. We assembled and conducted the analysis in R.

    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 . 2023
    License: CC 0
    Data sources: ZENODO
    DRYAD
    Dataset . 2023
    License: CC 0
    Data sources: Datacite
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      ZENODO
      Dataset . 2023
      License: CC 0
      Data sources: ZENODO
      DRYAD
      Dataset . 2023
      License: CC 0
      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: Pflüger, Mika; Gütschow, Johannes;

    Dataset containing all greenhouse gas emissions data submitted by countries under climate change convention (including CRF data) as published by the UNFCCC secretariat at 2024-07-05. Changes in this version compared to version 2024-07-04: No data changes. Provide the full dataset as a single parquet file instead of a collection of parquet files in a zip file. The dataset is also available via datalad. To obtain the dataset with datalad, see the instructions at https://github.com/mikapfl/unfccc_di_data .

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    ZENODO
    Dataset . 2024
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2024
    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 . 2024
    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/ ZENODOarrow_drop_down
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      ZENODO
      Dataset . 2024
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2024
      License: CC BY
      Data sources: ZENODO
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      ZENODO
      Dataset . 2024
      License: CC BY
      Data sources: Datacite
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    Authors: Jackson, Laura;

    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.HadGEM3-GC31-MM.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 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
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    Authors: Guo, Chuncheng; Bentsen, Mats; Bethke, Ingo; Ilicak, Mehmet; +4 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.PMIP.NCC.NorESM1-F' 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 NorESM1-F (a fast version of NorESM that is designed for paleo and multi-ensemble simulations) climate model, released in 2018, includes the following components: atmos: CAM4 (2 degree resolution; 144 x 96; 32 levels; top level 3 mb), land: CLM4, landIce: CISM, ocean: MICOM (1 degree resolution; 360 x 384; 70 levels; top grid cell minimum 0-2.5 m [native model uses hybrid density and generic upper-layer coordinate interpolated to z-level for contributed data]), ocnBgchem: HAMOCC5.1, seaIce: CICE4. The model was run by the NorESM Climate modeling Consortium consisting of CICERO (Center for International Climate and Environmental Research, Oslo 0349), MET-Norway (Norwegian Meteorological Institute, Oslo 0313), NERSC (Nansen Environmental and Remote Sensing Center, Bergen 5006), NILU (Norwegian Institute for Air Research, Kjeller 2027), UiB (University of Bergen, Bergen 5007), UiO (University of Oslo, Oslo 0313) and UNI (Uni Research, Bergen 5008), Norway. Mailing address: NCC, c/o MET-Norway, Henrik Mohns plass 1, Oslo 0313, Norway (NCC) in native nominal resolutions: atmos: 250 km, land: 250 km, landIce: 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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      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: Schupfner, Martin; Wieners, Karl-Hermann; Wachsmann, Fabian; Steger, Christian; +47 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.DKRZ.MPI-ESM1-2-HR.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 MPI-ESM1.2-HR climate model, released in 2017, includes the following components: aerosol: none, prescribed MACv2-SP, atmos: ECHAM6.3 (spectral T127; 384 x 192 longitude/latitude; 95 levels; top level 0.01 hPa), land: JSBACH3.20, landIce: none/prescribed, ocean: MPIOM1.63 (tripolar TP04, approximately 0.4deg; 802 x 404 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 Deutsches Klimarechenzentrum, Hamburg 20146, Germany (DKRZ) in native nominal resolutions: aerosol: 100 km, atmos: 100 km, land: 100 km, landIce: none, ocean: 50 km, ocnBgchem: 50 km, seaIce: 50 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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    This dataset contains the data displayed in the figures or the article "High-resolution projections of ambient heat for major European cities using different heat metrics". The different files contain: Data_Fig1_DeltaTXx_EURO-CORDEX_1981-2010_to_3K-European-warming_RCP85.nc: Change of yearly maximum temperature in Europe between 1981-2010 and 3 °C European warming relative to 1981-2010. Data_Fig2_timeseries-GSAT-ESAT_EURO-CORDEX_CMIP5_CMIP6_1971-2100_RCP85_SSP585.xlsx: Time series of global mean surface air temperature (GSAT) for CMIP5 and CMIP6 models, and for European mean surface air temperature (ESAT) for EURO-CORDEX, CMIP5, and CMIP6 models for the period 1971-2100. Data_Fig3_TX-distribution_distance-from-city-centre_E-OBS_1981-2010.xlsx: Distribution of average daily maximum temperature in summer (June, July, August) in 1981-2010 for E-OBS for all investigated cities. Temperature data are indicated as a function of the distance to the city centre. Data_Fig3_TX-distribution_distance-from-city-centre_ERA5-Land_1981-2010.xlsx: Distribution of average daily maximum temperature in summer (June, July, August) in 1981-2010 for ERA5-Land for all investigated cities. Temperature data are indicated as a function of the distance to the city centre. Data_Fig3_TX-distribution_distance-from-city-centre_EURO-CORDEX_1981-2010.xlsx: Distribution of average daily maximum temperature in summer (June, July, August) in 1981-2010 for the EURO-CORDEX models for all investigated cities. Temperature data are indicated as a function of the distance to the city centre. Data_Fig3_TX-distribution_distance-from-city-centre_weather-stations_1981-2010.xlsx: Distribution of average daily maximum temperature in summer (June, July, August) in 1981-2010 for GSOD and ECA&D stations for all investigated cities. Temperature data are indicated as a function of the distance to the city centre. Data_Fig4_TX-ambient-heat_EURO-CORDEX_3K-European-warming.xlsx: Daytime heat metrics for the investigated cities: HWMId-TX at 3 °C European warming relative to 1981-2010, TX exceedances above 30 °C at 3 °C European warming relative to 1981-2010, and TXx change between 1981-2010 and 3 °C European warming relative to 1981-2010 for EURO-CORDEX models. Data_Fig5_Contribution-of-explanatory-variables-to-total-explained-variance.xlsx: Contribution of different explanatory variables (climate and location factors) to the total explained variance of spatial patterns of heat metrics. Data_Fig6_TN-ambient-heat_EURO-CORDEX_3K-European-warming.xlsx: Nighttime heat metrics for the investigated cities: HWMId-TN at 3 °C European warming relative to 1981-2010, TN exceedances above 20 °C at 3 °C European warming relative to 1981-2010, and TNx change between 1981-2010 and 3 °C European warming relative to 1981-2010 for EURO-CORDEX models. Data_Fig7_TX-ambient-heat_CMIP5_3K-European-warming.xlsx: Daytime heat metrics for the investigated cities: HWMId-TX at 3 °C European warming relative to 1981-2010, TX exceedances above 30 °C at 3 °C European warming relative to 1981-2010, and TXx change between 1981-2010 and 3 °C European warming relative to 1981-2010 for CMIP5 models. Data_Fig7_TX-ambient-heat_CMIP6_3K-European-warming.xlsx: Daytime heat metrics for the investigated cities: HWMId-TX at 3 °C European warming relative to 1981-2010, TX exceedances above 30 °C at 3 °C European warming relative to 1981-2010, and TXx change between 1981-2010 and 3 °C European warming relative to 1981-2010 for CMIP6 models. Data_Fig8_GCM-RCM-matrix_ambient-heat_3K-European-warming.xlsx: GCM-RCM matrices for the three heat metrics.

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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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      ZENODO
      Dataset . 2023
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      ZENODO
      Dataset . 2023
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    This file contains the data and the STATA estimation code to replicate the results in the article entitled: "Information Communication Technology development and energy demand in African countries".

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    Mendeley Data
    Dataset . 2019
    License: CC BY
    Data sources: Datacite
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    Mendeley Data
    Dataset . 2019
    License: CC BY
    Data sources: Datacite
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    Mendeley Data
    Dataset . 2019
    License: CC BY
    Data sources: Datacite
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    Mendeley Data
    Dataset . 2019
    License: CC BY
    Data sources: Datacite
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    B2FIND
    Dataset . 2019
    Data sources: B2FIND
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      Mendeley Data
      Dataset . 2019
      License: CC BY
      Data sources: Datacite
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      Mendeley Data
      Dataset . 2019
      License: CC BY
      Data sources: Datacite
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      Mendeley Data
      Dataset . 2019
      License: CC BY
      Data sources: Datacite
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      Mendeley Data
      Dataset . 2019
      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/
      B2FIND
      Dataset . 2019
      Data sources: B2FIND
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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: María de la Paz Diulio (10410087); Gabriela Reus Netto (10410090); Roberto Berardi (75497); Jorge Daniel Czajkowski (10410093);

    Abstract The metropolitan area of La Plata, Argentina, represents 1.6% of households in Argentina. Based on the analysis of the energy retrofit of a house, we provide indicators in order to propose a methodology that facilitates the extrapolation, at regional level, of the impact of a general energy retrofit in homes. The results obtained are presented from micro to macro level, in context of energy shortage and recurrent crisis in the supply of fuels and electricity in Argentina. The improved thermal resistance of walls and ceilings throughout the residential park of La Plata lead to a reduction of 12% of the energy consumed in heating, and a saving of 30,000 TEP / year. We conclude that the incidence of additional insulation on the cost of building justifies its use, partially solving the lack of fuel in our country, reducing fixed costs in housing, providing thermal comfort to users and generating economic reactivation of the construction sector.

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    figshare
    Dataset . 2021
    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/
    figshare
    Dataset . 2021
    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/
    Smithsonian figshare
    Dataset . 2016
    License: CC BY
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      figshare
      Dataset . 2021
      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/
      figshare
      Dataset . 2021
      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/
      Smithsonian figshare
      Dataset . 2016
      License: CC BY
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    This data presents an experimental investigation carried out in a Boundary Layer Wind Tunnel located at Ruhr University Bochum, Germany. The flow field is measured above the rooftop of a high-rise building with a square cross-section considering two different roof shapes, flat roof and deck roof. The height-to-width ratio of the building was 1:3. The main purpose is to be used for estimation of urban wind energy potential, and besides for future validation of computational fluid dynamic simulations. Besides velocity field, measured at mainly three positions above the roof, the roof surface pressure was also measured. The flow above the roof was measured for different wind angles: 0°, 15°, 30°, and 45°.

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    Mendeley Data
    Dataset . 2020
    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/
    Mendeley Data
    Dataset . 2020
    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/
      Mendeley Data
      Dataset . 2020
      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/
      Mendeley Data
      Dataset . 2020
      License: CC BY
      Data sources: Datacite
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