Retirement Notice: This beta item will be retired in December 2026. A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version.This layer represents CMIP6 future projections of mean annual temperature. This layer can be used to compare with recent climate histories to better understand the potential impacts of future climate change.WorldClim produced this projection as part of a series of 19 bioclimate variables identified by the USGS and provides this description:"Bioclimatic variables are derived from the monthly temperature and rainfall values in order to generate more biologically meaningful variables. These are often used in species distribution modeling and related ecological modeling techniques. The bioclimatic variables represent annual trends (e.g., mean annual temperature, annual precipitation) seasonality (e.g., annual range in temperature and precipitation) and extreme or limiting environmental factors (e.g., temperature of the coldest and warmest month, and precipitation of the wet and dry quarters). A quarter is a period of three months (1/4 of the year)."Time Extent: averages from 2021-2040, 2041-2060, 2061-2080, 2081-2100Units: deg CCell Size:  2.5 minutes (~5 km)Source Type:  StretchedPixel Type:  32 Bit FloatData Projection:  GCS WGS84Mosaic Projection:  GCS WGS84Extent:  GlobalSource:  WorldClim CMIP6 Bioclimate Climate ScenariosThe CMIP6 climate experiments use Shared Socioeconomic Pathways (SSPs) to model future climate scenarios. Each SSP pairs a human/community behavior component with the traditional RCP greenhouse gas forcing from the previous CMIP5. Three SSPs were chosen by Esri to be included in the service based on user requests: SSP2 4.5, SSP3 7.0 and SSP5 8.5.SSPScenarioEstimated warming(2041–2060)Estimated warming(2081–2100)Very likely range in °C(2081–2100)SSP2-4.5intermediate GHG emissions:CO2 emissions around current levels until 2050, then falling but not reaching net zero by 21002.0 °C2.7 °C2.1 – 3.5SSP3-7.0high GHG emissions:CO2 emissions double by 21002.1 °C3.6 °C2.8 – 4.6SSP5-8.5very high GHG emissions:CO2 emissions triple by 20752.4 °C4.4 °C3.3 – 5.7While the 8.5 scenario is no longer generally considered likely, SSP3 7.0 has been included and is considered the high end of possibilities. SSP5 8.5 has been retained since many organizations report to this threshold. The warming associated with SSP2 4.5 is equivalent to the global targets set at the 2021 United Nations COP26 meetings in Glasgow. Processing the Climate DataWorldClim provides 20-year averaged outputs for the various SSPs from 24 global climate models. A selection of 13 models were averaged for each variable and time based on Mahony et al 2022. These models included ACCESS-ESM1-5, BCC-CSM2-MR, CanESM5, CNRM-ESM2-1, EC-Earth3-Veg, GFDL-ESM4, GISS-E2-1-G, INM-CM5-0, IPSL-CM6A-LR, MIROC6, MPI-ESM1-2-HR, MRI-ESM2-0, UKESM1-0-LL. GFDL-ESM4 was not available for SSP2 4.5 or SSP5 8.5. Accessing the Multidimensional InformationThe time and SSP scenario are built into the layer using a multidimensional raster. Enable the time slider to move across the 20-year average periods. In ArcGIS Online and Pro, use the Multidimensional Filter to select the SSP (SSP2 4.5 is the default). What can you do with this layer?These multidimensional imagery tiles support analysis using ArcGIS Online or Pro. Use the Bioclimate Baseline layer to see the difference in pixels and calculate change from the historic period into the future. Use the Multidimensional tab in ArcGIS Pro to access a variety of useful tools. Each layer or variable can be styled using the Image Display options. Known Quality IssuesEach model is downscaled from ~100km resolution to ~5km resolution by WorldClim. Some artifacts are inevitable, especially at a global scale. Some variables have distinct transitions, especially in Greenland. Also, SSP2 4.5 has missing data for several variables in Antarctica. Related LayersBioclimate 1 Annual Mean TemperatureBioclimate 2 Mean Diurnal RangeBioclimate 3 IsothermalityBioclimate 4 Temperature SeasonalityBioclimate 5 Max Temperature of Warmest MonthBioclimate 6 Min Temperature Of Coldest MonthBioclimate 7 Temperature Annual RangeBioclimate 8 Mean Temperature Of Wettest QuarterBioclimate 9 Mean Temperature Of Driest QuarterBioclimate 10 Mean Temperature Of Warmest QuarterBioclimate 11 Mean Temperature Of Coldest QuarterBioclimate 12 Annual PrecipitationBioclimate 13 Precipitation Of Wettest MonthBioclimate 14 Precipitation Of Driest MonthBioclimate 15 Precipitation SeasonalityBioclimate 16 Precipitation Of Wettest QuarterBioclimate 17 Precipitation Of Driest QuarterBioclimate 18 Precipitation Of Warmest QuarterBioclimate 19 Precipitation Of Coldest QuarterBioclimate Baseline 1970-2000

Important Note: This beta item will be retired in December 2026. A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version.This layer represents CMIP6 future projections of mean annual temperature. This layer can be used to compare with recent climate histories to better understand the potential impacts of future climate change.WorldClim produced this projection as part of a series of 19 bioclimate variables identified by the USGS and provides this description:"Bioclimatic variables are derived from the monthly temperature and rainfall values in order to generate more biologically meaningful variables. These are often used in species distribution modeling and related ecological modeling techniques. The bioclimatic variables represent annual trends (e.g., mean annual temperature, annual precipitation) seasonality (e.g., annual range in temperature and precipitation) and extreme or limiting environmental factors (e.g., temperature of the coldest and warmest month, and precipitation of the wet and dry quarters). A quarter is a period of three months (1/4 of the year)."Time Extent: averages from 2021-2040, 2041-2060, 2061-2080, 2081-2100Units: deg CCell Size:  2.5 minutes (~5 km)Source Type:  StretchedPixel Type:  32 Bit FloatData Projection:  GCS WGS84Mosaic Projection:  GCS WGS84Extent:  GlobalSource:  WorldClim CMIP6 Bioclimate Climate ScenariosThe CMIP6 climate experiments use Shared Socioeconomic Pathways (SSPs) to model future climate scenarios. Each SSP pairs a human/community behavior component with the traditional RCP greenhouse gas forcing from the previous CMIP5. Three SSPs were chosen by Esri to be included in the service based on user requests: SSP2 4.5, SSP3 7.0 and SSP5 8.5.SSPScenarioEstimated warming(2041–2060)Estimated warming(2081–2100)Very likely range in °C(2081–2100)SSP2-4.5intermediate GHG emissions:CO2 emissions around current levels until 2050, then falling but not reaching net zero by 21002.0 °C2.7 °C2.1 – 3.5SSP3-7.0high GHG emissions:CO2 emissions double by 21002.1 °C3.6 °C2.8 – 4.6SSP5-8.5very high GHG emissions:CO2 emissions triple by 20752.4 °C4.4 °C3.3 – 5.7While the 8.5 scenario is no longer generally considered likely, SSP3 7.0 has been included and is considered the high end of possibilities. SSP5 8.5 has been retained since many organizations report to this threshold. The warming associated with SSP2 4.5 is equivalent to the global targets set at the 2021 United Nations COP26 meetings in Glasgow. Processing the Climate DataWorldClim provides 20-year averaged outputs for the various SSPs from 24 global climate models. A selection of 13 models were averaged for each variable and time based on Mahony et al 2022. These models included ACCESS-ESM1-5, BCC-CSM2-MR, CanESM5, CNRM-ESM2-1, EC-Earth3-Veg, GFDL-ESM4, GISS-E2-1-G, INM-CM5-0, IPSL-CM6A-LR, MIROC6, MPI-ESM1-2-HR, MRI-ESM2-0, UKESM1-0-LL. GFDL-ESM4 was not available for SSP2 4.5 or SSP5 8.5. Accessing the Multidimensional InformationThe time and SSP scenario are built into the layer using a multidimensional raster. Enable the time slider to move across the 20-year average periods. In ArcGIS Online and Pro, use the Multidimensional Filter to select the SSP (SSP2 4.5 is the default). What can you do with this layer?These multidimensional imagery tiles support analysis using ArcGIS Online or Pro. Use the Bioclimate Baseline layer to see the difference in pixels and calculate change from the historic period into the future. Use the Multidimensional tab in ArcGIS Pro to access a variety of useful tools. Each layer or variable can be styled using the Image Display options. Known Quality IssuesEach model is downscaled from ~100km resolution to ~5km resolution by WorldClim. Some artifacts are inevitable, especially at a global scale. Some variables have distinct transitions, especially in Greenland. Also, SSP2 4.5 has missing data for several variables in Antarctica. Related LayersBioclimate 1 Annual Mean TemperatureBioclimate 2 Mean Diurnal RangeBioclimate 3 IsothermalityBioclimate 4 Temperature SeasonalityBioclimate 5 Max Temperature of Warmest MonthBioclimate 6 Min Temperature Of Coldest MonthBioclimate 7 Temperature Annual RangeBioclimate 8 Mean Temperature Of Wettest QuarterBioclimate 9 Mean Temperature Of Driest QuarterBioclimate 10 Mean Temperature Of Warmest QuarterBioclimate 11 Mean Temperature Of Coldest QuarterBioclimate 12 Annual PrecipitationBioclimate 13 Precipitation Of Wettest MonthBioclimate 14 Precipitation Of Driest MonthBioclimate 15 Precipitation SeasonalityBioclimate 16 Precipitation Of Wettest QuarterBioclimate 17 Precipitation Of Driest QuarterBioclimate 18 Precipitation Of Warmest QuarterBioclimate 19 Precipitation Of Coldest QuarterBioclimate Baseline 1970-2000

Important Note: This beta item will be retired in December 2026. A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version.This layer represents CMIP6 future projections of temperature change over the course of the year. The larger the value, the greater the variability of temperature. This layer can be used to compare with recent climate histories to better understand the potential impacts of future climate change.WorldClim produced this projection as part of a series of 19 bioclimate variables identified by the USGS and provides this description:"Bioclimatic variables are derived from the monthly temperature and rainfall values in order to generate more biologically meaningful variables. These are often used in species distribution modeling and related ecological modeling techniques. The bioclimatic variables represent annual trends (e.g., mean annual temperature, annual precipitation) seasonality (e.g., annual range in temperature and precipitation) and extreme or limiting environmental factors (e.g., temperature of the coldest and warmest month, and precipitation of the wet and dry quarters). A quarter is a period of three months (1/4 of the year)."Time Extent: averages from 2021-2040, 2041-2060, 2061-2080, 2081-2100Units: %Cell Size: 2.5 minutes (~5 km)Source Type: StretchedPixel Type: 32 Bit FloatData Projection: GCS WGS84Mosaic Projection: GCS WGS84Extent: GlobalSource: WorldClim CMIP6 Bioclimate Climate ScenariosThe CMIP6 climate experiments use Shared Socioeconomic Pathways (SSPs) to model future climate scenarios. Each SSP pairs a human/community behavior component with the traditional RCP greenhouse gas forcing from the previous CMIP5. Three SSPs were chosen by Esri to be included in the service based on user requests: SSP2 4.5, SSP3 7.0 and SSP5 8.5.SSPScenarioEstimated warming(2041–2060)Estimated warming(2081–2100)Very likely range in °C(2081–2100)SSP2-4.5intermediate GHG emissions:CO2 emissions around current levels until 2050, then falling but not reaching net zero by 21002.0 °C2.7 °C2.1 – 3.5SSP3-7.0high GHG emissions:CO2 emissions double by 21002.1 °C3.6 °C2.8 – 4.6SSP5-8.5very high GHG emissions:CO2 emissions triple by 20752.4 °C4.4 °C3.3 – 5.7While the 8.5 scenario is no longer generally considered likely, SSP3 7.0 has been included and is considered the high end of possibilities. SSP5 8.5 has been retained since many organizations report to this threshold. The warming associated with SSP2 4.5 is equivalent to the global targets set at the 2021 United Nations COP26 meetings in Glasgow. Processing the Climate DataWorldClim provides 20-year averaged outputs for the various SSPs from 24 global climate models. A selection of 13 models were averaged for each variable and time based on Mahony et al 2022. These models included ACCESS-ESM1-5, BCC-CSM2-MR, CanESM5, CNRM-ESM2-1, EC-Earth3-Veg, GFDL-ESM4, GISS-E2-1-G, INM-CM5-0, IPSL-CM6A-LR, MIROC6, MPI-ESM1-2-HR, MRI-ESM2-0, UKESM1-0-LL. GFDL-ESM4 was not available for SSP2 4.5 or SSP5 8.5. Accessing the Multidimensional InformationThe time and SSP scenario are built into the layer using a multidimensional raster. Enable the time slider to move across the 20-year average periods. In ArcGIS Online and Pro, use the Multidimensional Filter to select the SSP (SSP2 4.5 is the default). What can you do with this layer?These multidimensional imagery tiles support analysis using ArcGIS Online or Pro. Use the Bioclimate Baseline layer to see the difference in pixels and calculate change from the historic period into the future. Use the Multidimensional tab in ArcGIS Pro to access a variety of useful tools. Each layer or variable can be styled using the Image Display options. Known Quality IssuesEach model is downscaled from ~100km resolution to ~5km resolution by WorldClim. Some artifacts are inevitable, especially at a global scale. Some variables have distinct transitions, especially in Greenland. Also, SSP2 4.5 has missing data for several variables in Antarctica. Related LayersBioclimate 1 Annual Mean TemperatureBioclimate 2 Mean Diurnal RangeBioclimate 3 IsothermalityBioclimate 4 Temperature SeasonalityBioclimate 5 Max Temperature of Warmest MonthBioclimate 6 Min Temperature Of Coldest MonthBioclimate 7 Temperature Annual RangeBioclimate 8 Mean Temperature Of Wettest QuarterBioclimate 9 Mean Temperature Of Driest QuarterBioclimate 10 Mean Temperature Of Warmest QuarterBioclimate 11 Mean Temperature Of Coldest QuarterBioclimate 12 Annual PrecipitationBioclimate 13 Precipitation Of Wettest MonthBioclimate 14 Precipitation Of Driest MonthBioclimate 15 Precipitation SeasonalityBioclimate 16 Precipitation Of Wettest QuarterBioclimate 17 Precipitation Of Driest QuarterBioclimate 18 Precipitation Of Warmest QuarterBioclimate 19 Precipitation Of Coldest QuarterBioclimate Baseline 1970-2000

Retirement Notice: This beta item will be retired in December 2026. A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version.This layer represents CMIP6 future projections of temperature variation over an entire year. This layer can be used to compare with recent climate histories to better understand the potential impacts of future climate change.WorldClim produced this projection as part of a series of 19 bioclimate variables identified by the USGS and provides this description:"Bioclimatic variables are derived from the monthly temperature and rainfall values in order to generate more biologically meaningful variables. These are often used in species distribution modeling and related ecological modeling techniques. The bioclimatic variables represent annual trends (e.g., mean annual temperature, annual precipitation) seasonality (e.g., annual range in temperature and precipitation) and extreme or limiting environmental factors (e.g., temperature of the coldest and warmest month, and precipitation of the wet and dry quarters). A quarter is a period of three months (1/4 of the year)."Time Extent: averages from 2021-2040, 2041-2060, 2061-2080, 2081-2100Units: deg CCell Size: 2.5 minutes (~5 km)Source Type: StretchedPixel Type: 32 Bit FloatData Projection: GCS WGS84Mosaic Projection: GCS WGS84Extent: GlobalSource: WorldClim CMIP6 Bioclimate Climate ScenariosThe CMIP6 climate experiments use Shared Socioeconomic Pathways (SSPs) to model future climate scenarios. Each SSP pairs a human/community behavior component with the traditional RCP greenhouse gas forcing from the previous CMIP5. Three SSPs were chosen by Esri to be included in the service based on user requests: SSP2 4.5, SSP3 7.0 and SSP5 8.5.SSPScenarioEstimated warming(2041–2060)Estimated warming(2081–2100)Very likely range in °C(2081–2100)SSP2-4.5intermediate GHG emissions:CO2 emissions around current levels until 2050, then falling but not reaching net zero by 21002.0 °C2.7 °C2.1 – 3.5SSP3-7.0high GHG emissions:CO2 emissions double by 21002.1 °C3.6 °C2.8 – 4.6SSP5-8.5very high GHG emissions:CO2 emissions triple by 20752.4 °C4.4 °C3.3 – 5.7While the 8.5 scenario is no longer generally considered likely, SSP3 7.0 has been included and is considered the high end of possibilities. SSP5 8.5 has been retained since many organizations report to this threshold. The warming associated with SSP2 4.5 is equivalent to the global targets set at the 2021 United Nations COP26 meetings in Glasgow. Processing the Climate DataWorldClim provides 20-year averaged outputs for the various SSPs from 24 global climate models. A selection of 13 models were averaged for each variable and time based on Mahony et al 2022. These models included ACCESS-ESM1-5, BCC-CSM2-MR, CanESM5, CNRM-ESM2-1, EC-Earth3-Veg, GFDL-ESM4, GISS-E2-1-G, INM-CM5-0, IPSL-CM6A-LR, MIROC6, MPI-ESM1-2-HR, MRI-ESM2-0, UKESM1-0-LL. GFDL-ESM4 was not available for SSP2 4.5 or SSP5 8.5. Accessing the Multidimensional InformationThe time and SSP scenario are built into the layer using a multidimensional raster. Enable the time slider to move across the 20-year average periods. In ArcGIS Online and Pro, use the Multidimensional Filter to select the SSP (SSP2 4.5 is the default). What can you do with this layer?These multidimensional imagery tiles support analysis using ArcGIS Online or Pro. Use the Bioclimate Baseline layer to see the difference in pixels and calculate change from the historic period into the future. Use the Multidimensional tab in ArcGIS Pro to access a variety of useful tools. Each layer or variable can be styled using the Image Display options. Known Quality IssuesEach model is downscaled from ~100km resolution to ~5km resolution by WorldClim. Some artifacts are inevitable, especially at a global scale. Some variables have distinct transitions, especially in Greenland. Also, SSP2 4.5 has missing data for several variables in Antarctica.Related LayersBioclimate 1 Annual Mean TemperatureBioclimate 2 Mean Diurnal RangeBioclimate 3 IsothermalityBioclimate 4 Temperature SeasonalityBioclimate 5 Max Temperature of Warmest MonthBioclimate 6 Min Temperature Of Coldest MonthBioclimate 7 Temperature Annual RangeBioclimate 8 Mean Temperature Of Wettest QuarterBioclimate 9 Mean Temperature Of Driest QuarterBioclimate 10 Mean Temperature Of Warmest QuarterBioclimate 11 Mean Temperature Of Coldest QuarterBioclimate 12 Annual PrecipitationBioclimate 13 Precipitation Of Wettest MonthBioclimate 14 Precipitation Of Driest MonthBioclimate 15 Precipitation SeasonalityBioclimate 16 Precipitation Of Wettest QuarterBioclimate 17 Precipitation Of Driest QuarterBioclimate 18 Precipitation Of Warmest QuarterBioclimate 19 Precipitation Of Coldest QuarterBioclimate Baseline 1970-2000

Important Note: This beta item will be retired in December 2026. A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version.This layer represents CMIP6 future projections of temperature variation over an entire year. This layer can be used to compare with recent climate histories to better understand the potential impacts of future climate change.WorldClim produced this projection as part of a series of 19 bioclimate variables identified by the USGS and provides this description:"Bioclimatic variables are derived from the monthly temperature and rainfall values in order to generate more biologically meaningful variables. These are often used in species distribution modeling and related ecological modeling techniques. The bioclimatic variables represent annual trends (e.g., mean annual temperature, annual precipitation) seasonality (e.g., annual range in temperature and precipitation) and extreme or limiting environmental factors (e.g., temperature of the coldest and warmest month, and precipitation of the wet and dry quarters). A quarter is a period of three months (1/4 of the year)."Time Extent: averages from 2021-2040, 2041-2060, 2061-2080, 2081-2100Units: deg CCell Size: 2.5 minutes (~5 km)Source Type: StretchedPixel Type: 32 Bit FloatData Projection: GCS WGS84Mosaic Projection: GCS WGS84Extent: GlobalSource: WorldClim CMIP6 Bioclimate Climate ScenariosThe CMIP6 climate experiments use Shared Socioeconomic Pathways (SSPs) to model future climate scenarios. Each SSP pairs a human/community behavior component with the traditional RCP greenhouse gas forcing from the previous CMIP5. Three SSPs were chosen by Esri to be included in the service based on user requests: SSP2 4.5, SSP3 7.0 and SSP5 8.5.SSPScenarioEstimated warming(2041–2060)Estimated warming(2081–2100)Very likely range in °C(2081–2100)SSP2-4.5intermediate GHG emissions:CO2 emissions around current levels until 2050, then falling but not reaching net zero by 21002.0 °C2.7 °C2.1 – 3.5SSP3-7.0high GHG emissions:CO2 emissions double by 21002.1 °C3.6 °C2.8 – 4.6SSP5-8.5very high GHG emissions:CO2 emissions triple by 20752.4 °C4.4 °C3.3 – 5.7While the 8.5 scenario is no longer generally considered likely, SSP3 7.0 has been included and is considered the high end of possibilities. SSP5 8.5 has been retained since many organizations report to this threshold. The warming associated with SSP2 4.5 is equivalent to the global targets set at the 2021 United Nations COP26 meetings in Glasgow. Processing the Climate DataWorldClim provides 20-year averaged outputs for the various SSPs from 24 global climate models. A selection of 13 models were averaged for each variable and time based on Mahony et al 2022. These models included ACCESS-ESM1-5, BCC-CSM2-MR, CanESM5, CNRM-ESM2-1, EC-Earth3-Veg, GFDL-ESM4, GISS-E2-1-G, INM-CM5-0, IPSL-CM6A-LR, MIROC6, MPI-ESM1-2-HR, MRI-ESM2-0, UKESM1-0-LL. GFDL-ESM4 was not available for SSP2 4.5 or SSP5 8.5. Accessing the Multidimensional InformationThe time and SSP scenario are built into the layer using a multidimensional raster. Enable the time slider to move across the 20-year average periods. In ArcGIS Online and Pro, use the Multidimensional Filter to select the SSP (SSP2 4.5 is the default). What can you do with this layer?These multidimensional imagery tiles support analysis using ArcGIS Online or Pro. Use the Bioclimate Baseline layer to see the difference in pixels and calculate change from the historic period into the future. Use the Multidimensional tab in ArcGIS Pro to access a variety of useful tools. Each layer or variable can be styled using the Image Display options. Known Quality IssuesEach model is downscaled from ~100km resolution to ~5km resolution by WorldClim. Some artifacts are inevitable, especially at a global scale. Some variables have distinct transitions, especially in Greenland. Also, SSP2 4.5 has missing data for several variables in Antarctica.Related LayersBioclimate 1 Annual Mean TemperatureBioclimate 2 Mean Diurnal RangeBioclimate 3 IsothermalityBioclimate 4 Temperature SeasonalityBioclimate 5 Max Temperature of Warmest MonthBioclimate 6 Min Temperature Of Coldest MonthBioclimate 7 Temperature Annual RangeBioclimate 8 Mean Temperature Of Wettest QuarterBioclimate 9 Mean Temperature Of Driest QuarterBioclimate 10 Mean Temperature Of Warmest QuarterBioclimate 11 Mean Temperature Of Coldest QuarterBioclimate 12 Annual PrecipitationBioclimate 13 Precipitation Of Wettest MonthBioclimate 14 Precipitation Of Driest MonthBioclimate 15 Precipitation SeasonalityBioclimate 16 Precipitation Of Wettest QuarterBioclimate 17 Precipitation Of Driest QuarterBioclimate 18 Precipitation Of Warmest QuarterBioclimate 19 Precipitation Of Coldest QuarterBioclimate Baseline 1970-2000