cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15493/dffe.ccis.75102024
title: Future Extreme heat index: Ensemble 10,50 and 90th percentiles of Annual minimum of daily man temperature (tnn)  for 3.0 degree global temperature scenario relative to the period 1961-1991

description: National Climate Change Information System
description: The climate extremes projections over the Free State Province were conducted using the Coupled Global Climate Models (CGCMs) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets as part of the Assessment Report (AR) 6 of the Intergovernmental Panel on Climate Change (IPCC). The focus was on climate extreme events including heat, drought, heatwaves, and flooding. Calculations of climate extreme indices that speak to the identified extreme events were conducted using 10 CMIP6 climate models from the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) community. The ISIMIP models were statistically downscaled using the CMIP6 climate model scenario 4, Shared Socioeconomic Pathways 3-70 (SSP3-7.0), also known as the regional rivalry scenario, in the context of the Paris Agreement temperature goals. Under this scenario, a resurgence of nationalism and regional conflicts overshadow global issues. Governments increasingly prioritize national and regional security, leading to reduced investments in education and technological development. Inequality grows, and some regions experience severe environmental damage. These extreme indices were selected from the 27 core indices developed by the World Meteorological Organization (WMO) Expert Team on Climate Change Detection and Indices (ETCCDI) widely used for analysing extreme events in a changing climate. The calculations were conducted for the baseline period (1961-1990). The level of model uncertainty was represented by ensemble percentiles (10th, 50th and 90th percentiles) from the 10 models in which agreement between the models on the projected spatial pattern of the monthly maximum value of daily maximum temperature (Txx) for the baseline period is illustrated.
description: All datasets were downloaded from ISIMIP as netcdf and processed using Python to extreme climate indices of interest.
DOI: 10.15493/dffe.ccis.59102024
title: Future Extreme heat index: Ensemble 10th,50th and 90th percentiles of Annual percentage of days when TN < 10th percentile (tn10p) for 2.0 degree global temperature scenario relative to the period 1961-1991

description: National Climate Change Information System
description: The climate extremes projections over the Free State Province were conducted using the Coupled Global Climate Models (CGCMs) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets as part of the Assessment Report (AR) 6 of the Intergovernmental Panel on Climate Change (IPCC). The focus was on climate extreme events including heat, drought, heatwaves, and flooding. Calculations of climate extreme indices that speak to the identified extreme events were conducted using 10 CMIP6 climate models from the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) community. The ISIMIP models were statistically downscaled using the CMIP6 climate model scenario 4, Shared Socioeconomic Pathways 3-70 (SSP3-7.0), also known as the regional rivalry scenario, in the context of the Paris Agreement temperature goals. Under this scenario, a resurgence of nationalism and regional conflicts overshadow global issues. Governments increasingly prioritize national and regional security, leading to reduced investments in education and technological development. Inequality grows, and some regions experience severe environmental damage. These extreme indices were selected from the 27 core indices developed by the World Meteorological Organization (WMO) Expert Team on Climate Change Detection and Indices (ETCCDI) widely used for analysing extreme events in a changing climate. The calculations were conducted for the baseline period (1961-1990). The level of model uncertainty was represented by ensemble percentiles (10th, 50th and 90th percentiles) from the 10 models in which agreement between the models on the projected spatial pattern of the monthly maximum value of daily maximum temperature (Txx) for the baseline period is illustrated.
description: All datasets were downloaded from ISIMIP as netcdf and processed using Python to extreme climate indices of interest.
DOI: 10.15493/dffe.ccis.78102024
title: Future Extreme heat index: Ensemble 10th,50th and 90th percentiles of Annual percentage of days when TX < 10th percentile (tx10p) for 1.5 degree global temperature scenario relative to the period 1961-1991

description: National Climate Change Information System
description: The climate extremes projections over the Free State Province were conducted using the Coupled Global Climate Models (CGCMs) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets as part of the Assessment Report (AR) 6 of the Intergovernmental Panel on Climate Change (IPCC). The focus was on climate extreme events including heat, drought, heatwaves, and flooding. Calculations of climate extreme indices that speak to the identified extreme events were conducted using 10 CMIP6 climate models from the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) community. The ISIMIP models were statistically downscaled using the CMIP6 climate model scenario 4, Shared Socioeconomic Pathways 3-70 (SSP3-7.0), also known as the regional rivalry scenario, in the context of the Paris Agreement temperature goals. Under this scenario, a resurgence of nationalism and regional conflicts overshadow global issues. Governments increasingly prioritize national and regional security, leading to reduced investments in education and technological development. Inequality grows, and some regions experience severe environmental damage. These extreme indices were selected from the 27 core indices developed by the World Meteorological Organization (WMO) Expert Team on Climate Change Detection and Indices (ETCCDI) widely used for analysing extreme events in a changing climate. The calculations were conducted for the baseline period (1961-1990). The level of model uncertainty was represented by ensemble percentiles (10th, 50th and 90th percentiles) from the 10 models in which agreement between the models on the projected spatial pattern of the monthly maximum value of daily maximum temperature (Txx) for the baseline period is illustrated.
description: All datasets were downloaded from ISIMIP as netcdf and processed using Python to extreme climate indices of interest.
DOI: 10.15493/dffe.ccis.77102024
title: Future Extreme heat index: Ensemble 10th,50th and 90th percentiles of Annual percentage of days when TX < 10th percentile (tx10p) for baseline period of 1961-1991

description: National Climate Change Information System
description: The climate extremes projections over the Free State Province were conducted using the Coupled Global Climate Models (CGCMs) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets as part of the Assessment Report (AR) 6 of the Intergovernmental Panel on Climate Change (IPCC). The focus was on climate extreme events including heat, drought, heatwaves, and flooding. Calculations of climate extreme indices that speak to the identified extreme events were conducted using 10 CMIP6 climate models from the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) community. The ISIMIP models were statistically downscaled using the CMIP6 climate model scenario 4, Shared Socioeconomic Pathways 3-70 (SSP3-7.0), also known as the regional rivalry scenario, in the context of the Paris Agreement temperature goals. Under this scenario, a resurgence of nationalism and regional conflicts overshadow global issues. Governments increasingly prioritize national and regional security, leading to reduced investments in education and technological development. Inequality grows, and some regions experience severe environmental damage. These extreme indices were selected from the 27 core indices developed by the World Meteorological Organization (WMO) Expert Team on Climate Change Detection and Indices (ETCCDI) widely used for analysing extreme events in a changing climate. The calculations were conducted for the baseline period (1961-1990). The level of model uncertainty was represented by ensemble percentiles (10th, 50th and 90th percentiles) from the 10 models in which agreement between the models on the projected spatial pattern of the monthly maximum value of daily maximum temperature (Txx) for the baseline period is illustrated.
description: All datasets were downloaded from ISIMIP as netcdf and processed using Python to extreme climate indices of interest.
DOI: 10.15493/dffe.ccis.84102024
title: Future Extreme heat index: Ensemble 10th,50th and 90th percentiles of Annual percentage of days when TX > 90th percentile (tx90p) for 2.0 degree global temperature scenario relative to the period 1961-1991

description: National Climate Change Information System
description: The climate extremes projections over the Free State Province were conducted using the Coupled Global Climate Models (CGCMs) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets as part of the Assessment Report (AR) 6 of the Intergovernmental Panel on Climate Change (IPCC). The focus was on climate extreme events including heat, drought, heatwaves, and flooding. Calculations of climate extreme indices that speak to the identified extreme events were conducted using 10 CMIP6 climate models from the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) community. The ISIMIP models were statistically downscaled using the CMIP6 climate model scenario 4, Shared Socioeconomic Pathways 3-70 (SSP3-7.0), also known as the regional rivalry scenario, in the context of the Paris Agreement temperature goals. Under this scenario, a resurgence of nationalism and regional conflicts overshadow global issues. Governments increasingly prioritize national and regional security, leading to reduced investments in education and technological development. Inequality grows, and some regions experience severe environmental damage. These extreme indices were selected from the 27 core indices developed by the World Meteorological Organization (WMO) Expert Team on Climate Change Detection and Indices (ETCCDI) widely used for analysing extreme events in a changing climate. The calculations were conducted for the baseline period (1961-1990). The level of model uncertainty was represented by ensemble percentiles (10th, 50th and 90th percentiles) from the 10 models in which agreement between the models on the projected spatial pattern of the monthly maximum value of daily maximum temperature (Txx) for the baseline period is illustrated.
description: All datasets were downloaded from ISIMIP as netcdf and processed using Python to extreme climate indices of interest.
DOI: 10.15493/dffe.ccis.73102024
title: Future Extreme heat index: Ensemble 10th,50th and 90th percentiles of Annual minimum of daily man temperature (tnn)  for 1.5 degree global temperature scenario relative to the period 1961-1991

description: National Climate Change Information System
description: The climate extremes projections over the Free State Province were conducted using the Coupled Global Climate Models (CGCMs) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets as part of the Assessment Report (AR) 6 of the Intergovernmental Panel on Climate Change (IPCC). The focus was on climate extreme events including heat, drought, heatwaves, and flooding. Calculations of climate extreme indices that speak to the identified extreme events were conducted using 10 CMIP6 climate models from the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) community. The ISIMIP models were statistically downscaled using the CMIP6 climate model scenario 4, Shared Socioeconomic Pathways 3-70 (SSP3-7.0), also known as the regional rivalry scenario, in the context of the Paris Agreement temperature goals. Under this scenario, a resurgence of nationalism and regional conflicts overshadow global issues. Governments increasingly prioritize national and regional security, leading to reduced investments in education and technological development. Inequality grows, and some regions experience severe environmental damage. These extreme indices were selected from the 27 core indices developed by the World Meteorological Organization (WMO) Expert Team on Climate Change Detection and Indices (ETCCDI) widely used for analysing extreme events in a changing climate. The calculations were conducted for the baseline period (1961-1990). The level of model uncertainty was represented by ensemble percentiles (10th, 50th and 90th percentiles) from the 10 models in which agreement between the models on the projected spatial pattern of the monthly maximum value of daily maximum temperature (Txx) for the baseline period is illustrated.
description: All datasets were downloaded from ISIMIP as netcdf and processed using Python to extreme climate indices of interest.
DOI: 10.15493/dffe.ccis.94102024
title: Future Extreme heat index: Ensemble 10th,50th and 90th percentiles of Annual universal thermal climate index (utci) for 2.0 degree global temperature scenario relative to the period 1961-1991

description: National Climate Change Information System
description: The climate extremes projections over the Free State Province were conducted using the Coupled Global Climate Models (CGCMs) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets as part of the Assessment Report (AR) 6 of the Intergovernmental Panel on Climate Change (IPCC). The focus was on climate extreme events including heat, drought, heatwaves, and flooding. Calculations of climate extreme indices that speak to the identified extreme events were conducted using 10 CMIP6 climate models from the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) community. The ISIMIP models were statistically downscaled using the CMIP6 climate model scenario 4, Shared Socioeconomic Pathways 3-70 (SSP3-7.0), also known as the regional rivalry scenario, in the context of the Paris Agreement temperature goals. Under this scenario, a resurgence of nationalism and regional conflicts overshadow global issues. Governments increasingly prioritize national and regional security, leading to reduced investments in education and technological development. Inequality grows, and some regions experience severe environmental damage. These extreme indices were selected from the 27 core indices developed by the World Meteorological Organization (WMO) Expert Team on Climate Change Detection and Indices (ETCCDI) widely used for analysing extreme events in a changing climate. The calculations were conducted for the baseline period (1961-1990). The level of model uncertainty was represented by ensemble percentiles (10th, 50th and 90th percentiles) from the 10 models in which agreement between the models on the projected spatial pattern of the monthly maximum value of daily maximum temperature (Txx) for the baseline period is illustrated.
description: All datasets were downloaded from ISIMIP as netcdf and processed using Python to extreme climate indices of interest.
DOI: 10.15493/dffe.ccis.79102024
title: Future Extreme heat index: Ensemble 10th,50th and 90th percentiles of Annual percentage of days when TX < 10th percentile (tx10p) for 2.0 degree global temperature scenario relative to the period 1961-1991

description: National Climate Change Information System
description: The climate extremes projections over the Free State Province were conducted using the Coupled Global Climate Models (CGCMs) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets as part of the Assessment Report (AR) 6 of the Intergovernmental Panel on Climate Change (IPCC). The focus was on climate extreme events including heat, drought, heatwaves, and flooding. Calculations of climate extreme indices that speak to the identified extreme events were conducted using 10 CMIP6 climate models from the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) community. The ISIMIP models were statistically downscaled using the CMIP6 climate model scenario 4, Shared Socioeconomic Pathways 3-70 (SSP3-7.0), also known as the regional rivalry scenario, in the context of the Paris Agreement temperature goals. Under this scenario, a resurgence of nationalism and regional conflicts overshadow global issues. Governments increasingly prioritize national and regional security, leading to reduced investments in education and technological development. Inequality grows, and some regions experience severe environmental damage. These extreme indices were selected from the 27 core indices developed by the World Meteorological Organization (WMO) Expert Team on Climate Change Detection and Indices (ETCCDI) widely used for analysing extreme events in a changing climate. The calculations were conducted for the baseline period (1961-1990). The level of model uncertainty was represented by ensemble percentiles (10th, 50th and 90th percentiles) from the 10 models in which agreement between the models on the projected spatial pattern of the monthly maximum value of daily maximum temperature (Txx) for the baseline period is illustrated.
description: All datasets were downloaded from ISIMIP as netcdf and processed using Python to extreme climate indices of interest.
DOI: 10.15493/dffe.ccis.66102024
title: Future Extreme heat index: Ensemble 10th,50th and 90th percentiles of Annual percentage of days when TN > 90th percentile (tn90p) for 1.5, 2.0 and 3.0 degree global temperature scenario relative to the period 1961-1991

description: National Climate Change Information System
description: The climate extremes projections over the Free State Province were conducted using the Coupled Global Climate Models (CGCMs) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets as part of the Assessment Report (AR) 6 of the Intergovernmental Panel on Climate Change (IPCC). The focus was on climate extreme events including heat, drought, heatwaves, and flooding. Calculations of climate extreme indices that speak to the identified extreme events were conducted using 10 CMIP6 climate models from the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) community. The ISIMIP models were statistically downscaled using the CMIP6 climate model scenario 4, Shared Socioeconomic Pathways 3-70 (SSP3-7.0), also known as the regional rivalry scenario, in the context of the Paris Agreement temperature goals. Under this scenario, a resurgence of nationalism and regional conflicts overshadow global issues. Governments increasingly prioritize national and regional security, leading to reduced investments in education and technological development. Inequality grows, and some regions experience severe environmental damage. These extreme indices were selected from the 27 core indices developed by the World Meteorological Organization (WMO) Expert Team on Climate Change Detection and Indices (ETCCDI) widely used for analysing extreme events in a changing climate. The calculations were conducted for the baseline period (1961-1990). The level of model uncertainty was represented by ensemble percentiles (10th, 50th and 90th percentiles) from the 10 models in which agreement between the models on the projected spatial pattern of the monthly maximum value of daily maximum temperature (Txx) for the baseline period is illustrated.
description: All datasets were downloaded from ISIMIP as netcdf and processed using Python to extreme climate indices of interest.
DOI: 10.15468/dl.z4yjxv
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"equals","key":"TAXON_KEY","value":"5894340","matchCase":false},{"type":"equals","key":"OCCURRENCE_STATUS","value":"PRESENT","matchCase":false},{"type":"equals","key":"HAS_COORDINATE","value":"true","matchCase":false},{"type":"equals","key":"HAS_GEOSPATIAL_ISSUE","value":"false","matchCase":false},{"type":"lessThan","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"in","key":"YEAR","values":["2008","2009","2010","2011","2012","2013","2014","2015","2016","2017","2018","2019","2020","2021","2022","2023","2024"],"matchCase":false},{"type":"in","key":"BASIS_OF_RECORD","values":["LIVING_SPECIMEN","HUMAN OBSERVATION","OBSERVATION","OCCURRENCE","MACHINE_OBSERVATION"],"matchCase":false}]}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013042-241024112534372/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15493/dffe.ccis.95102024
title: Future Extreme heat index: Ensemble 10th,50th and 90th percentiles of Annual universal thermal climate index (utci) for 3.0 degree global temperature scenario relative to the period 1961-1991

description: National Climate Change Information System
description: The climate extremes projections over the Free State Province were conducted using the Coupled Global Climate Models (CGCMs) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets as part of the Assessment Report (AR) 6 of the Intergovernmental Panel on Climate Change (IPCC). The focus was on climate extreme events including heat, drought, heatwaves, and flooding. Calculations of climate extreme indices that speak to the identified extreme events were conducted using 10 CMIP6 climate models from the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) community. The ISIMIP models were statistically downscaled using the CMIP6 climate model scenario 4, Shared Socioeconomic Pathways 3-70 (SSP3-7.0), also known as the regional rivalry scenario, in the context of the Paris Agreement temperature goals. Under this scenario, a resurgence of nationalism and regional conflicts overshadow global issues. Governments increasingly prioritize national and regional security, leading to reduced investments in education and technological development. Inequality grows, and some regions experience severe environmental damage. These extreme indices were selected from the 27 core indices developed by the World Meteorological Organization (WMO) Expert Team on Climate Change Detection and Indices (ETCCDI) widely used for analysing extreme events in a changing climate. The calculations were conducted for the baseline period (1961-1990). The level of model uncertainty was represented by ensemble percentiles (10th, 50th and 90th percentiles) from the 10 models in which agreement between the models on the projected spatial pattern of the monthly maximum value of daily maximum temperature (Txx) for the baseline period is illustrated.
description: All datasets were downloaded from ISIMIP as netcdf and processed using Python to extreme climate indices of interest.