cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.1065400
title: Fire Weather Index - ERA-Interim

description: The Fire Weather Index (FWI) is a numeric rating of fire intensity, dependent on weather conditions. This is a good indicator of fire danger because it contains both a component of fuel availability (drought conditions) and a measure of ease of spread. This is part of a larger dataset providing gridded field calculations from the Canadian Fire Weather Index System using weather forcings from the European Centre for Medium-range Weather Forecast (ECMWF) ERA-Interim reanalysis dataset (Vitolo et al., 2019; Di Giuseppe et al., 2016). The dataset has been developed through a collaboration between the Joint Research Centre and ECMWF under the umbrella of the Global Wildfires Information System (GWIS), a joint initiative of the GEO and the Copernicus Work Programs. The whole dataset consists of seven indices, each of which describes a different aspect of the effect that fuel moisture and wind have on fire ignition probability and its behavior, if started. The indices are called: Fine Fuel Moisture Code (FFMC), Duff Moisture Code (DMC), Drought Code (DC), Initial Spread Index (ISI), Build Up Index (BUI), Fire Weather Index (FWI) and Daily Severity Rating (DSR). For convenience, each index is archived separately. Data are generated using the open source software GEFF v3.0 (https://git.ecmwf.int/projects/CEMSF/repos/geff), which now uses settings and parameters provided by the JRC (more info here https://git.ecmwf.int/projects/CEMSF/repos/geff/browse/NEWS.md). This dataset can be manipulated using the caliver R package (Vitolo et al. 2017, 2018). Details: File format: netcdf4 Coordinate system: World Geodetic System 1984 (also known as WGS 1984, EPSG:4326). Longitude range: [-180, +180] Latitude range: [-90, +90] Temporal resolution: 1 day Spatial resolution: 0.7 degrees (~80 Km) Spatial coverage: Global Time span: from 1980-01-01 to 2018-12-31
description: Contract 933710 between JRC and ECMWF (Copernicus - Fire Danger Forecast Computation)
description: {"references": ["Di Giuseppe, F., Pappenberger, F., Wetterhall, F., Krzeminski, B., Camia, A., Libert\u00e1, G. and San Miguel, J., 2016. The potential predictability of fire danger provided by numerical weather prediction. Journal of Applied Meteorology and Climatology, 55(11), pp.2469-2491. DOI: https://doi.org/10.1175/JAMC-D-15-0297.1", "Vitolo C., Di Giuseppe F., D'Andrea M., 2018. Caliver: An R package for CALIbration and VERification of forest fire gridded model outputs. PLoS ONE 13(1): e0189419. https://doi.org/10.1371/journal.pone.0189419", "Vitolo C., Di Giuseppe F., D'Andrea M., 2017. caliver R package version 1.0. URL: https://github.com/ecmwf/caliver, DOI: https://doi.org/10.5281/zenodo.582416.", "Vitolo C., Di Giuseppe F., Krzeminski B., San-Miguel-Ayanz J., 2019. A 1980\u20132018 global fire danger re-analysis dataset for the Canadian Fire Weather Indices, Scientific Data. https://doi.org/10.1038/sdata.2019.32"]}
DOI: 10.5281/zenodo.4400914
title: Socio world

description: Socio World-Social Research & Behavioral Sciences
DOI: 10.5281/zenodo.4400913
title: Socio world

description: Socio World-Social Research & Behavioral Sciences
DOI: 10.5281/zenodo.3250992
title: Fine Fuel Moisture Code - ERA-Interim

description: The Fine Fuel Moisture Code (FFMC) is a numeric rating of the moisture content of litter and other cured fine fuels. This code is an indicator of the relative ease of ignition and the flammability of fine fuel. This is part of a larger dataset providing gridded field calculations from the Canadian Fire Weather Index System using weather forcings from the European Centre for Medium-range Weather Forecast (ECMWF) ERA-Interim reanalysis dataset (Vitolo et al., 2019; Di Giuseppe et al., 2016). The dataset has been developed through a collaboration between the Joint Research Centre and ECMWF under the umbrella of the Global Wildfires Information System (GWIS), a joint initiative of the GEO and the Copernicus Work Programs. The whole dataset consists of seven indices, each of which describes a different aspect of the effect that fuel moisture and wind have on fire ignition probability and its behavior, if started. The indices are called: Fine Fuel Moisture Code (FFMC), Duff Moisture Code (DMC), Drought Code (DC), Initial Spread Index (ISI), Build Up Index (BUI), Fire Weather Index (FWI) and Daily Severity Rating (DSR). For convenience, each index is archived separately. Data are generated using the open source software GEFF v3.0 (https://git.ecmwf.int/projects/CEMSF/repos/geff), which now uses settings and parameters provided by the JRC (more info here https://git.ecmwf.int/projects/CEMSF/repos/geff/browse/NEWS.md). This dataset can be manipulated using the caliver R package (Vitolo et al. 2017, 2018). Details: File format: netcdf4 Coordinate system: World Geodetic System 1984 (also known as WGS 1984, EPSG:4326). Longitude range: [-180, +180] Latitude range: [-90, +90] Temporal resolution: 1 day Spatial resolution: 0.7 degrees (~80 Km) Spatial coverage: Global Time span: from 1980-01-01 to 2018-12-31
description: Contract 933710 between JRC and ECMWF (Copernicus - Fire Danger Forecast Computation)
description: {"references": ["Di Giuseppe, F., Pappenberger, F., Wetterhall, F., Krzeminski, B., Camia, A., Libert\u00e1, G. and San Miguel, J., 2016. The potential predictability of fire danger provided by numerical weather prediction. Journal of Applied Meteorology and Climatology, 55(11), pp.2469-2491. DOI: https://doi.org/10.1175/JAMC-D-15-0297.1", "Vitolo C., Di Giuseppe F., D'Andrea M., 2018. Caliver: An R package for CALIbration and VERification of forest fire gridded model outputs. PLoS ONE 13(1): e0189419. https://doi.org/10.1371/journal.pone.0189419", "Vitolo C., Di Giuseppe F., D'Andrea M., 2017. caliver R package version 1.0. URL: https://github.com/ecmwf/caliver, DOI: https://doi.org/10.5281/zenodo.582416.", "Vitolo C., Di Giuseppe F., Krzeminski B., San-Miguel-Ayanz J., 2019. A 1980\u20132018 global fire danger re-analysis dataset for the Canadian Fire Weather Indices, Scientific Data. https://doi.org/10.1038/sdata.2019.32"]}
DOI: 10.5281/zenodo.1068893
title: Fine Fuel Moisture Code - ERA-Interim

description: The Fine Fuel Moisture Code (FFMC) is a numeric rating of the moisture content of litter and other cured fine fuels. This code is an indicator of the relative ease of ignition and the flammability of fine fuel. This is part of a larger dataset providing gridded field calculations from the Canadian Fire Weather Index System using weather forcings from the European Centre for Medium-range Weather Forecast (ECMWF) ERA-Interim reanalysis dataset (Vitolo et al., 2019; Di Giuseppe et al., 2016). The dataset has been developed through a collaboration between the Joint Research Centre and ECMWF under the umbrella of the Global Wildfires Information System (GWIS), a joint initiative of the GEO and the Copernicus Work Programs. The whole dataset consists of seven indices, each of which describes a different aspect of the effect that fuel moisture and wind have on fire ignition probability and its behavior, if started. The indices are called: Fine Fuel Moisture Code (FFMC), Duff Moisture Code (DMC), Drought Code (DC), Initial Spread Index (ISI), Build Up Index (BUI), Fire Weather Index (FWI) and Daily Severity Rating (DSR). For convenience, each index is archived separately. Data are generated using the open source software GEFF v3.0 (https://git.ecmwf.int/projects/CEMSF/repos/geff), which now uses settings and parameters provided by the JRC (more info here https://git.ecmwf.int/projects/CEMSF/repos/geff/browse/NEWS.md). This dataset can be manipulated using the caliver R package (Vitolo et al. 2017, 2018). Details: File format: netcdf4 Coordinate system: World Geodetic System 1984 (also known as WGS 1984, EPSG:4326). Longitude range: [-180, +180] Latitude range: [-90, +90] Temporal resolution: 1 day Spatial resolution: 0.7 degrees (~80 Km) Spatial coverage: Global Time span: from 1980-01-01 to 2018-12-31
description: Contract 933710 between JRC and ECMWF (Copernicus - Fire Danger Forecast Computation)
description: {"references": ["Di Giuseppe, F., Pappenberger, F., Wetterhall, F., Krzeminski, B., Camia, A., Libert\u00e1, G. and San Miguel, J., 2016. The potential predictability of fire danger provided by numerical weather prediction. Journal of Applied Meteorology and Climatology, 55(11), pp.2469-2491. DOI: https://doi.org/10.1175/JAMC-D-15-0297.1", "Vitolo C., Di Giuseppe F., D'Andrea M., 2018. Caliver: An R package for CALIbration and VERification of forest fire gridded model outputs. PLoS ONE 13(1): e0189419. https://doi.org/10.1371/journal.pone.0189419", "Vitolo C., Di Giuseppe F., D'Andrea M., 2017. caliver R package version 1.0. URL: https://github.com/ecmwf/caliver, DOI: https://doi.org/10.5281/zenodo.582416.", "Vitolo C., Di Giuseppe F., Krzeminski B., San-Miguel-Ayanz J., 2019. A 1980\u20132018 global fire danger re-analysis dataset for the Canadian Fire Weather Indices, Scientific Data. https://doi.org/10.1038/sdata.2019.32"]}
DOI: 10.5281/zenodo.3250991
title: Duff Moisture Code - ERA-Interim

description: The Duff Moisture Code (DMC) is a numeric rating of the average moisture content of loosely compacted organic layers of moderate depth. This code gives an indication of fuel consumption in moderate duff layers and medium-size woody material. This is part of a larger dataset providing gridded field calculations from the Canadian Fire Weather Index System using weather forcings from the European Centre for Medium-range Weather Forecast (ECMWF) ERA-Interim reanalysis dataset (Vitolo et al., 2019; Di Giuseppe et al., 2016). The dataset has been developed through a collaboration between the Joint Research Centre and ECMWF under the umbrella of the Global Wildfires Information System (GWIS), a joint initiative of the GEO and the Copernicus Work Programs. The whole dataset consists of seven indices, each of which describes a different aspect of the effect that fuel moisture and wind have on fire ignition probability and its behavior, if started. The indices are called: Fine Fuel Moisture Code (FFMC), Duff Moisture Code (DMC), Drought Code (DC), Initial Spread Index (ISI), Build Up Index (BUI), Fire Weather Index (FWI) and Daily Severity Rating (DSR). For convenience, each index is archived separately. Data are generated using the open source software GEFF v3.0 (https://git.ecmwf.int/projects/CEMSF/repos/geff), which now uses settings and parameters provided by the JRC (more info here https://git.ecmwf.int/projects/CEMSF/repos/geff/browse/NEWS.md). This dataset can be manipulated using the caliver R package (Vitolo et al. 2017, 2018). Details: File format: netcdf4 Coordinate system: World Geodetic System 1984 (also known as WGS 1984, EPSG:4326). Longitude range: [-180, +180] Latitude range: [-90, +90] Temporal resolution: 1 day Spatial resolution: 0.7 degrees (~80 Km) Spatial coverage: Global Time span: from 1980-01-01 to 2018-12-31
description: Contract 933710 between JRC and ECMWF (Copernicus - Fire Danger Forecast Computation)
description: {"references": ["Di Giuseppe, F., Pappenberger, F., Wetterhall, F., Krzeminski, B., Camia, A., Libert\u00e1, G. and San Miguel, J., 2016. The potential predictability of fire danger provided by numerical weather prediction. Journal of Applied Meteorology and Climatology, 55(11), pp.2469-2491. DOI: https://doi.org/10.1175/JAMC-D-15-0297.1", "Vitolo C., Di Giuseppe F., D'Andrea M., 2018. Caliver: An R package for CALIbration and VERification of forest fire gridded model outputs. PLoS ONE 13(1): e0189419. https://doi.org/10.1371/journal.pone.0189419", "Vitolo C., Di Giuseppe F., D'Andrea M., 2017. caliver R package version 1.0. URL: https://github.com/ecmwf/caliver, DOI: https://doi.org/10.5281/zenodo.582416.", "Vitolo C., Di Giuseppe F., Krzeminski B., San-Miguel-Ayanz J., 2019. A 1980\u20132018 global fire danger re-analysis dataset for the Canadian Fire Weather Indices, Scientific Data. https://doi.org/10.1038/sdata.2019.32"]}
DOI: 10.5281/zenodo.1068891
title: Duff Moisture Code - ERA-Interim

description: The Duff Moisture Code (DMC) is a numeric rating of the average moisture content of loosely compacted organic layers of moderate depth. This code gives an indication of fuel consumption in moderate duff layers and medium-size woody material. This is part of a larger dataset providing gridded field calculations from the Canadian Fire Weather Index System using weather forcings from the European Centre for Medium-range Weather Forecast (ECMWF) ERA-Interim reanalysis dataset (Vitolo et al., 2019; Di Giuseppe et al., 2016). The dataset has been developed through a collaboration between the Joint Research Centre and ECMWF under the umbrella of the Global Wildfires Information System (GWIS), a joint initiative of the GEO and the Copernicus Work Programs. The whole dataset consists of seven indices, each of which describes a different aspect of the effect that fuel moisture and wind have on fire ignition probability and its behavior, if started. The indices are called: Fine Fuel Moisture Code (FFMC), Duff Moisture Code (DMC), Drought Code (DC), Initial Spread Index (ISI), Build Up Index (BUI), Fire Weather Index (FWI) and Daily Severity Rating (DSR). For convenience, each index is archived separately. Data are generated using the open source software GEFF v3.0 (https://git.ecmwf.int/projects/CEMSF/repos/geff), which now uses settings and parameters provided by the JRC (more info here https://git.ecmwf.int/projects/CEMSF/repos/geff/browse/NEWS.md). This dataset can be manipulated using the caliver R package (Vitolo et al. 2017, 2018). Details: File format: netcdf4 Coordinate system: World Geodetic System 1984 (also known as WGS 1984, EPSG:4326). Longitude range: [-180, +180] Latitude range: [-90, +90] Temporal resolution: 1 day Spatial resolution: 0.7 degrees (~80 Km) Spatial coverage: Global Time span: from 1980-01-01 to 2018-12-31
description: Contract 933710 between JRC and ECMWF (Copernicus - Fire Danger Forecast Computation)
description: {"references": ["Di Giuseppe, F., Pappenberger, F., Wetterhall, F., Krzeminski, B., Camia, A., Libert\u00e1, G. and San Miguel, J., 2016. The potential predictability of fire danger provided by numerical weather prediction. Journal of Applied Meteorology and Climatology, 55(11), pp.2469-2491. DOI: https://doi.org/10.1175/JAMC-D-15-0297.1", "Vitolo C., Di Giuseppe F., D'Andrea M., 2018. Caliver: An R package for CALIbration and VERification of forest fire gridded model outputs. PLoS ONE 13(1): e0189419. https://doi.org/10.1371/journal.pone.0189419", "Vitolo C., Di Giuseppe F., D'Andrea M., 2017. caliver R package version 1.0. URL: https://github.com/ecmwf/caliver, DOI: https://doi.org/10.5281/zenodo.582416.", "Vitolo C., Di Giuseppe F., Krzeminski B., San-Miguel-Ayanz J., 2019. A 1980\u20132018 global fire danger re-analysis dataset for the Canadian Fire Weather Indices, Scientific Data. https://doi.org/10.1038/sdata.2019.32"]}
DOI: 10.5281/zenodo.4486612
title: Genotyping of the Chinese Spring x Renan mapping population with the TaBW280K SNP array

description: The TaBW280K SNP array (Rimbert et al., PLoS ONE 2018) was used to genotype 430 Single Seed Descent (SSD) individuals<br> derived from a cross between Chinese Spring and Renan (CsRe; Choulet et al., Science 2014). Out of the 280,226 probesets, 85,276 were found to be polymorphic between the two parental lines and PHR on the population. Eventually, 83,721 (98.2%) SNPs were genetically mapped in 21 linkage groups corresponding to the 21 chromosomes of bread wheat, with no unlinked markers. This file contains the genotyping data of the 430 SSD lines.<br>
description: {"references": ["Rimbert et al. (2018) High throughput SNP discovery and genotyping in hexaploid wheat. PLoS ONE 13(1): e0186329."]}
DOI: 10.5281/zenodo.4486611
title: Genotyping of the Chinese Spring x Renan mapping population with the TaBW280K SNP array

description: The TaBW280K SNP array (Rimbert et al., PLoS ONE 2018) was used to genotype 430 Single Seed Descent (SSD) individuals<br> derived from a cross between Chinese Spring and Renan (CsRe; Choulet et al., Science 2014). Out of the 280,226 probesets, 85,276 were found to be polymorphic between the two parental lines and PHR on the population. Eventually, 83,721 (98.2%) SNPs were genetically mapped in 21 linkage groups corresponding to the 21 chromosomes of bread wheat, with no unlinked markers. This file contains the genotyping data of the 430 SSD lines.<br>
description: {"references": ["Rimbert et al. (2018) High throughput SNP discovery and genotyping in hexaploid wheat. PLoS ONE 13(1): e0186329."]}
DOI: 10.5281/zenodo.3250960
title: Drought Code - ERA-Interim

description: The Drought Code (DC) is a numeric rating of the average moisture content of deep, compact organic layers. This code is a useful indicator of seasonal drought effects on forest fuels and the amount of smoldering in deep duff layers and large logs. This is part of a larger dataset providing gridded field calculations from the Canadian Fire Weather Index System using weather forcings from the European Centre for Medium-range Weather Forecast (ECMWF) ERA-Interim reanalysis dataset (Vitolo et al., 2019; Di Giuseppe et al., 2016). The dataset has been developed through a collaboration between the Joint Research Centre and ECMWF under the umbrella of the Global Wildfires Information System (GWIS), a joint initiative of the GEO and the Copernicus Work Programs. The whole dataset consists of seven indices, each of which describes a different aspect of the effect that fuel moisture and wind have on fire ignition probability and its behavior, if started. The indices are called: Fine Fuel Moisture Code (FFMC), Duff Moisture Code (DMC), Drought Code (DC), Initial Spread Index (ISI), Build Up Index (BUI), Fire Weather Index (FWI) and Daily Severity Rating (DSR). For convenience, each index is archived separately. Data are generated using the open source software GEFF v3.0 (https://git.ecmwf.int/projects/CEMSF/repos/geff), which now uses settings and parameters provided by the JRC (more info here https://git.ecmwf.int/projects/CEMSF/repos/geff/browse/NEWS.md). This dataset can be manipulated using the caliver R package (Vitolo et al. 2017, 2018). Details: File format: netcdf4 Coordinate system: World Geodetic System 1984 (also known as WGS 1984, EPSG:4326). Longitude range: [-180, +180] Latitude range: [-90, +90] Temporal resolution: 1 day Spatial resolution: 0.7 degrees (~80 Km) Spatial coverage: Global Time span: from 1980-01-01 to 2018-12-31
description: Contract 933710 between JRC and ECMWF (Copernicus - Fire Danger Forecast Computation)
description: {"references": ["Di Giuseppe, F., Pappenberger, F., Wetterhall, F., Krzeminski, B., Camia, A., Libert\u00e1, G. and San Miguel, J., 2016. The potential predictability of fire danger provided by numerical weather prediction. Journal of Applied Meteorology and Climatology, 55(11), pp.2469-2491. DOI: https://doi.org/10.1175/JAMC-D-15-0297.1", "Vitolo C., Di Giuseppe F., D'Andrea M., 2018. Caliver: An R package for CALIbration and VERification of forest fire gridded model outputs. PLoS ONE 13(1): e0189419. https://doi.org/10.1371/journal.pone.0189419", "Vitolo C., Di Giuseppe F., D'Andrea M., 2017. caliver R package version 1.0. URL: https://github.com/ecmwf/caliver, DOI: https://doi.org/10.5281/zenodo.582416.", "Vitolo C., Di Giuseppe F., Krzeminski B., San-Miguel-Ayanz J., 2019. A 1980\u20132018 global fire danger re-analysis dataset for the Canadian Fire Weather Indices, Scientific Data. https://doi.org/10.1038/sdata.2019.32"]}
DOI: 10.5281/zenodo.1068896
title: Drought Code - ERA-Interim

description: The Drought Code (DC) is a numeric rating of the average moisture content of deep, compact organic layers. This code is a useful indicator of seasonal drought effects on forest fuels and the amount of smoldering in deep duff layers and large logs. This is part of a larger dataset providing gridded field calculations from the Canadian Fire Weather Index System using weather forcings from the European Centre for Medium-range Weather Forecast (ECMWF) ERA-Interim reanalysis dataset (Vitolo et al., 2019; Di Giuseppe et al., 2016). The dataset has been developed through a collaboration between the Joint Research Centre and ECMWF under the umbrella of the Global Wildfires Information System (GWIS), a joint initiative of the GEO and the Copernicus Work Programs. The whole dataset consists of seven indices, each of which describes a different aspect of the effect that fuel moisture and wind have on fire ignition probability and its behavior, if started. The indices are called: Fine Fuel Moisture Code (FFMC), Duff Moisture Code (DMC), Drought Code (DC), Initial Spread Index (ISI), Build Up Index (BUI), Fire Weather Index (FWI) and Daily Severity Rating (DSR). For convenience, each index is archived separately. Data are generated using the open source software GEFF v3.0 (https://git.ecmwf.int/projects/CEMSF/repos/geff), which now uses settings and parameters provided by the JRC (more info here https://git.ecmwf.int/projects/CEMSF/repos/geff/browse/NEWS.md). This dataset can be manipulated using the caliver R package (Vitolo et al. 2017, 2018). Details: File format: netcdf4 Coordinate system: World Geodetic System 1984 (also known as WGS 1984, EPSG:4326). Longitude range: [-180, +180] Latitude range: [-90, +90] Temporal resolution: 1 day Spatial resolution: 0.7 degrees (~80 Km) Spatial coverage: Global Time span: from 1980-01-01 to 2018-12-31
description: Contract 933710 between JRC and ECMWF (Copernicus - Fire Danger Forecast Computation)
description: {"references": ["Di Giuseppe, F., Pappenberger, F., Wetterhall, F., Krzeminski, B., Camia, A., Libert\u00e1, G. and San Miguel, J., 2016. The potential predictability of fire danger provided by numerical weather prediction. Journal of Applied Meteorology and Climatology, 55(11), pp.2469-2491. DOI: https://doi.org/10.1175/JAMC-D-15-0297.1", "Vitolo C., Di Giuseppe F., D'Andrea M., 2018. Caliver: An R package for CALIbration and VERification of forest fire gridded model outputs. PLoS ONE 13(1): e0189419. https://doi.org/10.1371/journal.pone.0189419", "Vitolo C., Di Giuseppe F., D'Andrea M., 2017. caliver R package version 1.0. URL: https://github.com/ecmwf/caliver, DOI: https://doi.org/10.5281/zenodo.582416.", "Vitolo C., Di Giuseppe F., Krzeminski B., San-Miguel-Ayanz J., 2019. A 1980\u20132018 global fire danger re-analysis dataset for the Canadian Fire Weather Indices, Scientific Data. https://doi.org/10.1038/sdata.2019.32"]}