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This dataset provides the data applied in the case studies of the manuscript "Backcasting the Techno-economic Targets For Constructing Low-carbon Power Systems". Both the modified Garver’s 6-bus and realistic Northwest China power system are presented here, in two excel files respectively. The datasets include detailed information about buses, units, existing corridors, and candidate corridors.Average cost variations and load growth rate over the planning period are also provided.

Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.CMIP.CAS.FGOALS-f3-L' 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 FGOALS-f3-L climate model, released in 2017, includes the following components: atmos: FAMIL2.2 (Cubed-sphere, c96; 360 x 180 longitude/latitude; 32 levels; top level 2.16 hPa), land: CLM4.0, ocean: LICOM3.0 (LICOM3.0, tripolar primarily 1deg; 360 x 218 longitude/latitude; 30 levels; top grid cell 0-10 m), seaIce: CICE4.0. The model was run by the Chinese Academy of Sciences, Beijing 100029, China (CAS) in native nominal resolutions: atmos: 100 km, land: 100 km, ocean: 100 km, seaIce: 100 km.

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.C4MIP.E3SM-Project.E3SM-1-1' 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 E3SM 1.1 (Energy Exascale Earth System Model) climate model, released in 2019, includes the following components: aerosol: MAM4 with resuspension, marine organics, and secondary organics (same grid as atmos), atmos: EAM (v1.1, cubed sphere spectral-element grid; 5400 elements with p=3; 1 deg average grid spacing; 90 x 90 x 6 longitude/latitude/cubeface; 72 levels; top level 0.1 hPa), atmosChem: Troposphere specified oxidants for aerosols. Stratosphere linearized interactive ozone (LINOZ v2) (same grid as atmos), land: ELM (v1.1, same grid as atmos; active biogeochemistry using the Converging Trophic Cascade plant and soil carbon and nutrient mechanisms to represent carbon, nitrogen and phosphorus cycles), MOSART (v1.1, 0.5 degree latitude/longitude grid), ocean: MPAS-Ocean (v6.0, oEC60to30 unstructured SVTs mesh with 235160 cells and 714274 edges, variable resolution 60 km to 30 km; 60 levels; top grid cell 0-10 m), ocnBgchem: BEC (Biogeochemical Elemental Cycling model, NPZD-type with C/N/P/Fe/Si/O; same grid as ocean), seaIce: MPAS-Seaice (v6.0; same grid as ocean). The model was run by the LLNL (Lawrence Livermore National Laboratory, Livermore, CA 94550, USA); ANL (Argonne National Laboratory, Argonne, IL 60439, USA); BNL (Brookhaven National Laboratory, Upton, NY 11973, USA); LANL (Los Alamos National Laboratory, Los Alamos, NM 87545, USA); LBNL (Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA); ORNL (Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA); PNNL (Pacific Northwest National Laboratory, Richland, WA 99352, USA); SNL (Sandia National Laboratories, Albuquerque, NM 87185, USA). Mailing address: LLNL Climate Program, c/o David C. Bader, Principal Investigator, L-103, 7000 East Avenue, Livermore, CA 94550, USA (E3SM-Project) in native nominal resolutions: aerosol: 100 km, atmos: 100 km, atmosChem: 100 km, land: 100 km, ocean: 50 km, ocnBgchem: 50 km, seaIce: 50 km.

This is a set of aggregated data tables that underly the key figures in the SERL stats report "Smart Energy Research Lab: Energy use in GB domestic buildings 2021" (Volume 1). The report describes domestic gas and electricity energy use in Great Britain in 2021 based on data from the Smart Energy Research Lab (SERL) Observatory, which consists of smart meter and contextual data from approximately 13,000 homes that are broadly representative of the GB population in terms of region and Index of Multiple Deprivation (IMD) quintile. The report shows how residential energy use in GB varies over time (monthly over the year and half-hourly over the course of the day), with occupant characteristics (number of occupants, tenure), property characteristics (age, size, form, and Energy Performance Certificate (EPC)), by type of heating system, presence of solar panels and of electric vehicles, and by weather, region and IMD quintile.

This dataset contains two metrics for climate change exposure using downscaled climate projections with the SRES A2 emissions scenario (Tabor and Williams, 2007).The metrics represent dissimilarity measurements of the squared Euclidean distance between seasonal (June–August and December–February) temperature and precipitation variables in the 20th century climate and mid-21st century climate. (1) disappearing climate risk - measure of dissimilarity between a pixel’s late 20th century climate and its closest matching pixel in the global set of 21st-century climates (2) novel climate risk - measure of dissimilarity between a pixel’s future climate and its closest matching pixel in the global set of late 20th-century climates. The data are in arcASCII format. All data are in units of standard Euclidean distance and multiplied by 1000. This is the original data. To scale the data similar to Tabor et al. (2018), remove outliers above the 99th percentile distribution before rescaling from 0-1. Unprojected number of columns 2160 number of rows 857 Lower Left X Center -179.917 Lower Left Y Center -59.084 Cell size 0.166667 decimal degrees (10 minutes or ~17 km) {"references": ["Tabor, K. et al. (2018). Tropical Protected Areas Under Increasing Threats from Climate Change and Deforestation: https://doi.org/10.3390/land7030090", "Tabor and Williams (2010). Globally downscaled climate projections for assessing the conservation impacts of climate change. https://doi.org/10.1890/09-0173.1", "Williams, J.W. et al. (2007). Projected distributions of novel and disappearing climates by 20100 AD. https://doi.org/10.1073/pnas.0606292104"]} Support for this project was provided by Conservation International, the Land Tenure Center at the University of Wisconsin, the Center for Climatic Research at the University of Wisconsin, and the Environment Program at the University of Wisconsin–Madison. This research has been funded in part by the Walton Family Foundation, the Gordon and Betty Moore Foundation, and a gift from Betty and Gordon Moore.

We examine unequal outcomes in the implementation of India's national rural electrification program in Uttar Pradesh. We ask two questions: (1) to what extent did Dalits, the lowest group in India's caste hierarchy, receive less attention when the state electrified rural communities? (2) Was BSP, the state's Dalit party, able to reduce this inequality? Using data from a hundred thousand villages, we provide robust evidence for unequal outcomes. Villages inhabited solely by Dalits were 20 percentage points less likely to be covered by the program than villages without any Dalits. Moreover, a regression discontinuity analysis shows that the electoral success of BSP failed to reduce such differences. These results highlight the magnitude and persistence of caste inequality in the implementation of democratic public policy, despite political representation.

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

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.DAMIP.NOAA-GFDL.GFDL-ESM4' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The GFDL-ESM4 climate model, released in 2018, includes the following components: aerosol: interactive, atmos: GFDL-AM4.1 (Cubed-sphere (c96) - 1 degree nominal horizontal resolution; 360 x 180 longitude/latitude; 49 levels; top level 1 Pa), atmosChem: GFDL-ATMCHEM4.1 (full atmospheric chemistry), land: GFDL-LM4.1, landIce: GFDL-LM4.1, ocean: GFDL-OM4p5 (GFDL-MOM6, tripolar - nominal 0.5 deg; 720 x 576 longitude/latitude; 75 levels; top grid cell 0-2 m), ocnBgchem: GFDL-COBALTv2, seaIce: GFDL-SIM4p5 (GFDL-SIS2.0, tripolar - nominal 0.5 deg; 720 x 576 longitude/latitude; 5 layers; 5 thickness categories). The model was run by the National Oceanic and Atmospheric Administration, Geophysical Fluid Dynamics Laboratory, Princeton, NJ 08540, USA (NOAA-GFDL) in native nominal resolutions: aerosol: 100 km, atmos: 100 km, atmosChem: 100 km, land: 100 km, landIce: 100 km, ocean: 50 km, ocnBgchem: 50 km, seaIce: 50 km.

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.