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Found 10 records similar to Statistically downscaled scenarios of projected minimum temperature change

Federal

Statistically downscaled multi-model ensembles of projected change (also known as anomalies) in mean temperature (°C) are available at a 10km spatial resolution for 1951-2100. Statistically downscaled ensembles are based on output from twenty-four Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models (GCM). Downscaled daily mean temperature was calculated by averaging downscaled daily minimum and maximum temperature. Daily minimum and maximum temperature from GCM outputs were downscaled using the Bias Correction/Constructed Analogues with Quantile mapping version 2 (BCCAQv2).

Last Updated: Feb. 22, 2022
Date Published: Sep. 6, 2018
Organization: Environment and Climate Change Canada
Formats: WMS PDF HTML NetCDF GeoTIF
Keywords:  Weather and Climate, Provide Climate Information Products and Services, Expand Scientific Knowledge for Climate Monitoring and Prediction, National (CA), Climate, Climate change
Federal

Statistically downscaled multi-model ensembles of minimum temperature are available at a 10km spatial resolution for 1951-2100. Statistically downscaled ensembles are based on output from twenty-four Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models (GCM). Daily minimum temperature from GCM outputs were downscaled using the Bias Correction/Constructed Analogues with Quantile mapping version 2 (BCCAQv2). A historical gridded minimum temperature dataset of Canada (ANUSPLIN) was used as the downscaling target.

Last Updated: Feb. 22, 2022
Date Published: Sep. 6, 2018
Organization: Environment and Climate Change Canada
Formats: WMS PDF HTML NetCDF GeoTIF
Keywords:  Weather and Climate, Provide Climate Information Products and Services, Expand Scientific Knowledge for Climate Monitoring and Prediction, National (CA), Climate, Climate change
Federal

Statistically downscaled multi-model ensembles of mean temperature are available at a 10km spatial resolution for 1951-2100. Statistically downscaled ensembles are based on output from twenty-four Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models (GCM). Downscaled daily mean temperature was calculated by averaging downscaled daily minimum and maximum temperature. Daily minimum and maximum temperature from GCM outputs were downscaled using the Bias Correction/Constructed Analogues with Quantile mapping version 2 (BCCAQv2).

Last Updated: Feb. 22, 2022
Date Published: Sep. 6, 2018
Organization: Environment and Climate Change Canada
Formats: WMS PDF HTML NetCDF GeoTIF
Keywords:  Weather and Climate, Provide Climate Information Products and Services, Expand Scientific Knowledge for Climate Monitoring and Prediction, National (CA), Climate, Climate change
Federal

Statistically downscaled multi-model ensembles of projected change (also known as anomalies) in maximum temperature (°C) are available at a 10km spatial resolution for 1951-2100. Statistically downscaled ensembles are based on output from twenty-four Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models (GCM). Daily maximum temperature from GCM outputs were downscaled using the Bias Correction/Constructed Analogues with Quantile mapping version 2 (BCCAQv2). A historical gridded maximum temperature dataset of Canada (ANUSPLIN) was used as the downscaling target.

Last Updated: Feb. 22, 2022
Date Published: Sep. 6, 2018
Organization: Environment and Climate Change Canada
Formats: WMS PDF HTML NetCDF GeoTIF
Keywords:  Weather and Climate, Provide Climate Information Products and Services, Expand Scientific Knowledge for Climate Monitoring and Prediction, National (CA), Climate, Climate change
Federal

Statistically downscaled multi-model ensembles of maximum temperature are available at a 10km spatial resolution for 1951-2100. Statistically downscaled ensembles are based on output from twenty-four Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models (GCM). Daily maximum temperature from GCM outputs were downscaled using the Bias Correction/Constructed Analogues with Quantile mapping version 2 (BCCAQv2). A historical gridded maximum temperature dataset of Canada (ANUSPLIN) was used as the downscaling target.

Last Updated: Feb. 22, 2022
Date Published: Sep. 6, 2018
Organization: Environment and Climate Change Canada
Formats: WMS PDF HTML NetCDF GeoTIF
Keywords:  Weather and Climate, Provide Climate Information Products and Services, Expand Scientific Knowledge for Climate Monitoring and Prediction, National (CA), Climate, Climate change
Federal

Statistically downscaled multi-model ensembles of projected change (also known as anomalies) in total precipitation are available at a 10km spatial resolution for 1951-2100. Statistically downscaled ensembles are based on output from twenty-four Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models (GCM). Daily precipitation (mm/day) from GCM outputs were downscaled using the Bias Correction/Constructed Analogues with Quantile mapping version 2 (BCCAQv2). A historical gridded precipitation dataset of Canada (ANUSPLIN) was used as the downscaling target.

Last Updated: Feb. 22, 2022
Date Published: Sep. 6, 2018
Organization: Environment and Climate Change Canada
Formats: WMS PDF HTML NetCDF GeoTIF
Keywords:  Weather and Climate, Provide Climate Information Products and Services, Expand Scientific Knowledge for Climate Monitoring and Prediction, National (CA), Climate, Climate change
Federal

Statistically downscaled multi-model ensembles of total precipitation are available at a 10km spatial resolution for 1951-2100. Statistically downscaled ensembles are based on output from twenty-four Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models (GCM). Daily precipitation (mm/day) from GCM outputs were downscaled using the Bias Correction/Constructed Analogues with Quantile mapping version 2 (BCCAQv2). A historical gridded precipitation dataset of Canada (ANUSPLIN) was used as the downscaling target.

Last Updated: Feb. 22, 2022
Date Published: Sep. 6, 2018
Organization: Environment and Climate Change Canada
Formats: WMS PDF HTML NetCDF GeoTIF
Keywords:  Weather and Climate, Provide Climate Information Products and Services, Expand Scientific Knowledge for Climate Monitoring and Prediction, National (CA), Climate, Climate change
Federal

Seasonal and annual multi-model ensembles of projected change (also known as anomalies) in mean temperature (°C) based on an ensemble of twenty-nine Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models are available for 1901-2100. Projected change in mean temperature (°C) is with respect to the reference period of 1986-2005. The 5th, 25th, 50th, 75th and 95th percentiles of the ensembles of projected change in mean temperature change are available for the historical time period, 1901-2005, and for emission scenarios, RCP2.6, RCP4.5 and RCP8.5, for 2006-2100. Twenty-year average changes in mean temperature (°C) for four time periods (2021-2040; 2041-2060; 2061-2080; 2081-2100), with respect to the reference period of 1986-2005, for RCP2.6, RCP4.5 and RCP8.5 are also available in a range of formats.

Last Updated: Feb. 22, 2022
Date Published: Sep. 6, 2018
Organization: Environment and Climate Change Canada
Formats: WMS PDF HTML NetCDF GeoTIF
Keywords:  Projections; climate; climate change; percentiles; ensembles; climate model; temperature; cmip5; anomaly, Weather and Climate, Provide Climate Information Products and Services, Expand Scientific Knowledge for Climate Monitoring and Prediction, National (CA), Climate, Climate change
Federal

Multi-model ensembles of mean temperature based on projections from twenty-nine Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models are available for 1901-2100. Specifically, the 5th, 25th, 50th, 75th and 95th percentiles of the monthly, seasonal and annual ensembles of mean temperature (°C) are available for the historical time period, 1901-2005, and for emission scenarios, RCP2.6, RCP4.5 and RCP8.5, for 2006-2100.

Note: Projections among climate models can vary because of differences in their underlying representation of earth system processes. Thus, the use of a multi-model ensemble approach has been demonstrated in recent scientific literature to likely provide better projected climate change information.

Last Updated: Feb. 22, 2022
Date Published: Sep. 6, 2018
Organization: Environment and Climate Change Canada
Formats: WMS PDF HTML NetCDF GeoTIF
Keywords:  Projections; climate; climate change; percentiles; ensembles; climate model; temperature; cmip5, Weather and Climate, Provide Climate Information Products and Services, Expand Scientific Knowledge for Climate Monitoring and Prediction, International, Climate, Climate change
Federal

Seasonal and annual multi-model ensembles of projected change (also known as anomalies) in snow depth based on an ensemble of twenty-eight Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models are available for 1900-2100. Projected change in snow depth is with respect to the reference period of 1986-2005 and expressed as a percentage (%). The 5th, 25th, 50th, 75th and 95th percentiles of the ensemble of snow depth change are available for the historical time period, 1900-2005, and for emission scenarios, RCP2.6, RCP4.5 and RCP8.5, for 2006-2100. Twenty-year average changes in snow depth (%) for four time periods (2021-2040; 2041-2060; 2061-2080; 2081-2100), with respect to the reference period of 1986-2005, for RCP2.6, RCP4.5 and RCP8.5 are also available in a range of formats.

Last Updated: Feb. 22, 2022
Date Published: Sep. 6, 2018
Organization: Environment and Climate Change Canada
Formats: WMS PDF HTML NetCDF GeoTIF
Keywords:  Projections; climate; climate change; percentiles; ensembles; climate model; snow; cmip5; anomaly, Weather and Climate, Provide Climate Information Products and Services, Expand Scientific Knowledge for Climate Monitoring and Prediction, National (CA), Climate, Climate change
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