Annual Cooling Degree Days (annual sum of the number of degrees that the daily mean temperature is above 22°C each day), projections for a range of future warming levels from UKCP18. Provided on a 12km BNG grid.This metric is related to power consumption for cooling systems and air conditioning required on hot days, so this index is useful for predicting future changes in energy demand for cooling. In practice, this varies greatly throughout the UK, depending on personal thermal comfort levels and building designs, so these results should be considered as rough estimates of overall demand changes on a large scale. This data contains a field for each warming level. They are named 'CDD' (Cooling Degree Days), the warming level, and 'upper' 'median' or 'lower' as per the description below. E.g. 'CDD 2.5 median' is the median value for the 2.5°C projection. Decimal points are included in field aliases but not field names e.g. 'CDD 2.5 median' is 'CDD_25_median'. Data defaults to displaying 'CDD 2.0°C median' values, use 'change style' to display other values.The warming levels used are 1.5°C, 2.0°C, 2.5°C, 3.0°C, 4.0°C, and two baselines are also provided for 1981-2000 (corresponding to 0.51°C warming) and 2000-2017 (corresponding to 0.835°C warming).What is the data?The data is from the UKCP18 regional projections using the RCP8.5 scenario. Rather than giving projections for a specific date under different scenarios, one scenario is used and projections are given at the different warming levels. So this data shows the expected Cooling Degree Days should these warming levels be reached, at the time that the warming level is reached.For full details, see 'Future Changes to high impact weather in the UK'. HM Hanlon, D Bernie, G Carigi and JA Lowe. Climatic Change, 166, 50 (2021) https://doi.org/10.1007/s10584-021-03100-5What do the 'median', 'upper', and 'lower' values mean?This scenario is run as 12 separate ensemble members. To select which ensemble members to use, a single value was taken from each ensemble member - the mean of a 21yr period centred on the year the warming level was reached. They were then ranked in order from lowest to highest.The 'lower' fields are the second lowest ranked ensemble member.The 'higher' fields are the second highest ranked ensemble member.The 'median' fields are the median average of all ensemble members.This gives a median average value, and a spread of the ensemble members indicating the level of uncertainty in the projections.This dataset forms part of the Met Office’s Climate Data Portal service. This service is currently in Beta. We would like your help to further develop our service, please send us feedback via the site - https://climate-themetoffice.hub.arcgis.com/

Annual Count of Frost Days (annual number of days where the minimum daily temperature is below 0 °C), projections for a range of future warming levels from UKCP18. Provided on a 12km BNG grid.Frost days have large negative impacts on crops, transportation, and energy demand. While there is a general reduction in frost days across the country, different administrative regions of the UK show a variation in the magnitude of the projected decrease in the numbers of frost days. There is a steady rate of decrease in frost days per year with global mean warming in all UK regions. See also Icing Days, which is a similar metric but measures more severe cold weather impacts.This data contains a field for each warming level. They are named 'Frost Days', the warming level, and 'upper' 'median' or 'lower' as per the description below. E.g. 'Frost Days 2.5 median' is the median value for the 2.5°C projection. Decimal points are included in field aliases but not field names e.g. 'Frost Days 2.5 median' is 'FrostDays_25_median'. Data defaults to displaying 'Frost Days 2.0°C median' values, use 'change style' to display other values.The warming levels used are 1.5°C, 2.0°C, 2.5°C, 3.0°C, 4.0°C, and two baselines are also provided for 1981-2000 (corresponding to 0.51°C warming) and 2000-2017 (corresponding to 0.835°C warming).What is the data?The data is from the UKCP18 regional projections using the RCP8.5 scenario. Rather than giving projections for a specific date under different scenarios, one scenario is used and projections are given at the different warming levels. So this data shows the expected number of Frost Days should these warming levels be reached, at the time that the warming level is reached.For full details, see 'Future Changes to high impact weather in the UK'. HM Hanlon, D Bernie, G Carigi and JA Lowe. Climatic Change, 166, 50 (2021) https://doi.org/10.1007/s10584-021-03100-5What do the 'median', 'upper', and 'lower' values mean?This scenario is run as 12 separate ensemble members. To select which ensemble members to use, a single value was taken from each ensemble member - the mean of a 21yr period centred on the year the warming level was reached. They were then ranked in order from lowest to highest.The 'lower' fields are the second lowest ranked ensemble member.The 'higher' fields are the second highest ranked ensemble member.The 'median' fields are the median average of all ensemble members.This gives a median average value, and a spread of the ensemble members indicating the level of uncertainty in the projections.This dataset forms part of the Met Office’s Climate Data Portal service. This service is currently in Beta. We would like your help to further develop our service, please send us feedback via the site - https://climate-themetoffice.hub.arcgis.com/

Annual Count of Icing Days (annual number of days where the maximum daily temperature is below 0°C), projections for a range of future warming levels from UKCP18. Provided on a 12km BNG grid.This metric is similar to frost days, but measures more severe cold weather impacts as it is defined as a day where the maximum daily temperature is below 0°C. In other words, the temperature does not rise above 0°C for the whole day. By definition, the daily minimum will also be below 0°C so all icing days are also counted as frost days. On an icing day, more ice will form, having a greater impact than other frost days. Frost days and Icing Days have large negative impacts on crops, transportation, and energy demand.This data contains a field for each warming level. They are named 'Icing Days', the warming level, and 'upper' 'median' or 'lower' as per the description below. E.g. 'Icing Days 2.5 median' is the median value for the 2.5°C projection. Decimal points are included in field aliases but not field names e.g. 'Icing Days 2.5 median' is 'IcingDays_25_median'. Data defaults to displaying 'Icing Days 2.0°C median' values, use 'change style' to display other values.The warming levels used are 1.5°C, 2.0°C, 2.5°C, 3.0°C, 4.0°C, and two baselines are also provided for 1981-2000 (corresponding to 0.51°C warming) and 2000-2017 (corresponding to 0.835°C warming).What is the data?The data is from the UKCP18 regional projections using the RCP8.5 scenario. Rather than giving projections for a specific date under different scenarios, one scenario is used and projections are given at the different warming levels. So this data shows the expected number of Icing Days should these warming levels be reached, at the time that the warming level is reached.For full details, see 'Future Changes to high impact weather in the UK'. HM Hanlon, D Bernie, G Carigi and JA Lowe. Climatic Change, 166, 50 (2021) https://doi.org/10.1007/s10584-021-03100-5What do the 'median', 'upper', and 'lower' values mean?This scenario is run as 12 separate ensemble members. To select which ensemble members to use, a single value was taken from each ensemble member - the mean of a 21yr period centred on the year the warming level was reached. They were then ranked in order from lowest to highest.The 'lower' fields are the second lowest ranked ensemble member.The 'higher' fields are the second highest ranked ensemble member.The 'median' fields are the median average of all ensemble members.This gives a median average value, and a spread of the ensemble members indicating the level of uncertainty in the projections.This dataset forms part of the Met Office’s Climate Data Portal service. This service is currently in Beta. We would like your help to further develop our service, please send us feedback via the site - https://climate-themetoffice.hub.arcgis.com/

Annual Count of Summer Days (annual number of days where the maximum daily temperature is above 25°C), projections for a range of future warming levels from UKCP18. Provided on a 12km BNG grid.Summer days is a measure of the health impact from high temperatures and heatwaves - it is based on temperature thresholds which, when exceeded, can pose risks to human health and wellbeing. Summer Days are shown to increase everywhere throughout the UK. There is a higher frequency in the South of the UK, and this is projected to increase considerably with global warming. Tropical Nights is another metric measuring health impacts of high temperatures.This data contains a field for each warming level. They are named 'Summer Days', the warming level, and 'upper' 'median' or 'lower' as per the description below. E.g. 'Summer Days 2.5 median' is the median value for the 2.5°C projection. Decimal points are included in field aliases but not field names e.g. 'Summer Days 2.5 median' is 'SummerDays_25_median'. Data defaults to displaying 'Summer Days 2.0°C median' values, use 'change style' to display other values.The warming levels used are 1.5°C, 2.0°C, 2.5°C, 3.0°C, 4.0°C, and two baselines are also provided for 1981-2000 (corresponding to 0.51°C warming) and 2000-2017 (corresponding to 0.835°C warming).What is the data?The data is from the UKCP18 regional projections using the RCP8.5 scenario. Rather than giving projections for a specific date under different scenarios, one scenario is used and projections are given at the different warming levels. So this data shows the expected number of Summer Days should these warming levels be reached, at the time that the warming level is reached.For full details, see 'Future Changes to high impact weather in the UK'. HM Hanlon, D Bernie, G Carigi and JA Lowe. Climatic Change, 166, 50 (2021) https://doi.org/10.1007/s10584-021-03100-5What do the 'median', 'upper', and 'lower' values mean?This scenario is run as 12 separate ensemble members. To select which ensemble members to use, a single value was taken from each ensemble member - the mean of a 21yr period centred on the year the warming level was reached. They were then ranked in order from lowest to highest.The 'lower' fields are the second lowest ranked ensemble member.The 'higher' fields are the second highest ranked ensemble member.The 'median' fields are the median average of all ensemble members.This gives a median average value, and a spread of the ensemble members indicating the level of uncertainty in the projections.This dataset forms part of the Met Office’s Climate Data Portal service. This service is currently in Beta. We would like your help to further develop our service, please send us feedback via the site - https://climate-themetoffice.hub.arcgis.com/

Annual Count of Tropical Nights (annual number of days where the minimum daily temperature is above 20°C), projections for a range of future warming levels from UKCP18. Provided on a 12km BNG grid.Tropical nights is an index used for measuring how many extremely warm nights occur; it is relevant for human health because in periods of high daytime temperatures, it is important that the body has time to recover from the heat stress of the daytime during the lower temperatures at night. It should be noted that without examples in the present climate, it is not possible to validate this metric as effectively as the other metrics. Summer Days is another metric measuring health impacts of high temperatures.This data contains a field for each warming level. They are named 'Tropical Nights', the warming level, and 'upper' 'median' or 'lower' as per the description below. E.g. 'Tropical Nights 2.5 median' is the median value for the 2.5°C projection. Decimal points are included in field aliases but not field names e.g. 'Tropical Nights 2.5 median' is 'TropicalNights_25_median'. Data defaults to displaying 'Tropical Nights 2.0°C median' values, use 'change style' to display other values.The warming levels used are 1.5°C, 2.0°C, 2.5°C, 3.0°C, 4.0°C, and two baselines are also provided for 1981-2000 (corresponding to 0.51°C warming) and 2000-2017 (corresponding to 0.835°C warming).What is the data?The data is from the UKCP18 regional projections using the RCP8.5 scenario. Rather than giving projections for a specific date under different scenarios, one scenario is used and projections are given at the different warming levels. So this data shows the expected number of Tropical Nights should these warming levels be reached, at the time that the warming level is reached.For full details, see 'Future Changes to high impact weather in the UK'. HM Hanlon, D Bernie, G Carigi and JA Lowe. Climatic Change, 166, 50 (2021) https://doi.org/10.1007/s10584-021-03100-5What do the 'median', 'upper', and 'lower' values mean?This scenario is run as 12 separate ensemble members. To select which ensemble members to use, a single value was taken from each ensemble member - the mean of a 21yr period centred on the year the warming level was reached. They were then ranked in order from lowest to highest.The 'lower' fields are the second lowest ranked ensemble member.The 'higher' fields are the second highest ranked ensemble member.The 'median' fields are the median average of all ensemble members.This gives a median average value, and a spread of the ensemble members indicating the level of uncertainty in the projections.This dataset forms part of the Met Office’s Climate Data Portal service. This service is currently in Beta. We would like your help to further develop our service, please send us feedback via the site - https://climate-themetoffice.hub.arcgis.com/

Annual Growing Degree Days (annual sum of the number of degrees that the daily mean temperature is above 5.5°C each day), projections for a range of future warming levels from UKCP18. Provided on a 12km BNG grid.This metric is useful for measuring whether conditions are suitable for plant growth. The GDD index increases throughout the UK with warming level suggesting potential for larger crop yields. GDD is based purely on temperature and so does not estimate the growth of specific species as it does not include any measure of rainfall/drought, sunlight, day length or wind, species vulnerability, nor does it account for plant dieback in extremely high temperatures. So, there is only a positive impact from increased GDD until temperatures reach a critical level above which there are detrimental impacts on plant physiology.This data contains a field for each warming level. They are named 'GDD' (Growing Degree Days), the warming level, and 'upper' 'median' or 'lower' as per the description below. E.g. 'GDD 2.5 median' is the median value for the 2.5°C projection. Decimal points are included in field aliases but not field names e.g. 'GDD 2.5 median' is 'GDD_25_median'. Data defaults to displaying 'GDD 2.0°C median' values, use 'change style' to display other values.The warming levels used are 1.5°C, 2.0°C, 2.5°C, 3.0°C, 4.0°C, and two baselines are also provided for 1981-2000 (corresponding to 0.51°C warming) and 2000-2017 (corresponding to 0.835°C warming).What is the data?The data is from the UKCP18 regional projections using the RCP8.5 scenario. Rather than giving projections for a specific date under different scenarios, one scenario is used and projections are given at the different warming levels. So this data shows the expected Growing Degree Days should these warming levels be reached, at the time that the warming level is reached.For full details, see 'Future Changes to high impact weather in the UK'. HM Hanlon, D Bernie, G Carigi and JA Lowe. Climatic Change, 166, 50 (2021) https://doi.org/10.1007/s10584-021-03100-5What do the 'median', 'upper', and 'lower' values mean?This scenario is run as 12 separate ensemble members. To select which ensemble members to use, a single value was taken from each ensemble member - the mean of a 21yr period centred on the year the warming level was reached. They were then ranked in order from lowest to highest.The 'lower' fields are the second lowest ranked ensemble member.The 'higher' fields are the second highest ranked ensemble member.The 'median' fields are the median average of all ensemble members.This gives a median average value, and a spread of the ensemble members indicating the level of uncertainty in the projections.This dataset forms part of the Met Office’s Climate Data Portal service. This service is currently in Beta. We would like your help to further develop our service, please send us feedback via the site - https://climate-themetoffice.hub.arcgis.com/

Annual Heating Degree Days (annual sum of the number of degrees that the daily mean temperature is below 15.5°C each day), projections for a range of future warming levels from UKCP18. Provided on a 12km BNG grid.This metric is related to power consumption for heating required on cold days. Hence, this index is useful for predicting future changes in energy demand for heating.This data contains a field for each warming level. They are named 'HDD' (Heating Degree Days), the warming level, and 'upper' 'median' or 'lower' as per the description below. E.g. 'HDD 2.5 median' is the median value for the 2.5°C projection. Decimal points are included in field aliases but not field names e.g. 'HDD 2.5 median' is 'HDD_25_median'. Data defaults to displaying 'HDD 2.0°C median' values, use 'change style' to display other values.The warming levels used are 1.5°C, 2.0°C, 2.5°C, 3.0°C, 4.0°C, and two baselines are also provided for 1981-2000 (corresponding to 0.51°C warming) and 2000-2017 (corresponding to 0.835°C warming).What is the data?The data is from the UKCP18 regional projections using the RCP8.5 scenario. Rather than giving projections for a specific date under different scenarios, one scenario is used and projections are given at the different warming levels. So this data shows the expected Heating Degree Days should these warming levels be reached, at the time that the warming level is reached.For full details, see 'Future Changes to high impact weather in the UK'. HM Hanlon, D Bernie, G Carigi and JA Lowe. Climatic Change, 166, 50 (2021) https://doi.org/10.1007/s10584-021-03100-5What do the 'median', 'upper', and 'lower' values mean?This scenario is run as 12 separate ensemble members. To select which ensemble members to use, a single value was taken from each ensemble member - the mean of a 21yr period centred on the year the warming level was reached. They were then ranked in order from lowest to highest.The 'lower' fields are the second lowest ranked ensemble member.The 'higher' fields are the second highest ranked ensemble member.The 'median' fields are the median average of all ensemble members.This gives a median average value, and a spread of the ensemble members indicating the level of uncertainty in the projections.This dataset forms part of the Met Office’s Climate Data Portal service. This service is currently in Beta. We would like your help to further develop our service, please send us feedback via the site - https://climate-themetoffice.hub.arcgis.com/

Annual averages of precipitation (mm/day) for 2050-2079 from UKCP18 regional projections (12km grid), using the RCP8.5 pathway.This data contains a field for the average over the period. It is named 'pr' (precipitation) and 'upper' 'median' or 'lower' as per the description below. E.g. 'pr Lower'UKCP: https://www.metoffice.gov.uk/research/approach/collaboration/ukcp/indexWhat is the data?The data is from the UKCP18 regional projections using the RCP8.5 scenario. RCP8.5 is the highest of the plausible future emissions scenarios used by the IPCC, sometimes referred to as 'business as usual'.What do the 'median', 'upper', and 'lower' values mean?This scenario is run as 12 separate ensemble members. To select which ensemble members to use, a single value for the mean UK precipitation for the period 2050-2079 was taken from each ensemble member. They were then ranked in order from lowest precipitation to highest. The 'lower' field in this data is the second lowest ranked ensemble member. The 'higher' field is the second highest ranked ensemble member. The 'median' field is the central (7th) ranked ensemble member.This gives a median value, and a spread of the ensemble members indicating the level of uncertainty in the projections.Recommendations for use of this data:1. We don't recommend using this data at the resolution of a single cell.The higher resolution of this data improves representation of topography, coasts, etc. but at the same time increases some of the uncertainty for individual grid cells. And so it is recommended to work with multiple grid cells, or an average of grid cells around a point to improve certainty.2. Consider whether the lower, median, or upper projections, or a combination, are most suitable for your use case.As described above, the spread of the ensemble members shown by the lower, median, and upper values indicates the level of uncertainty in the projections.Data source:pr_rcp85_land-rcm_uk_12km_12_ann-30y_200912-207911.nc (median)pr_rcp85_land-rcm_uk_12km_05_ann-30y_200912-207911.nc (lower)pr_rcp85_land-rcm_uk_12km_04_ann-30y_200912-207911.nc (upper)UKCP18 v20190731 (downloaded 04/11/2021)This dataset forms part of the Met Office’s Climate Data Portal service. This service is currently in Beta. We would like your help to further develop our service, please send us feedback via the site - https://climate-themetoffice.hub.arcgis.com/

Annual averages of surface temperature (C) for 2050-2079 from UKCP18 regional projections (12km grid), using the RCP8.5 pathway.This data contains a field for the average over the period. It is named 'tas' (temperature at surface) and 'upper' 'median' or 'lower' as per the description below. E.g. 'tas Upper'UKCP: https://www.metoffice.gov.uk/research/approach/collaboration/ukcp/indexWhat is the data?The data is from the UKCP18 regional projections using the RCP8.5 scenario. RCP8.5 is the highest of the plausible future emissions scenarios used by the IPCC, sometimes referred to as 'business as usual'.What do the 'median', 'upper', and 'lower' values mean?This scenario is run as 12 separate ensemble members. To select which ensemble members to use, a single value for the mean UK temperature for the period 2050-2079 was taken from each ensemble member. They were then ranked in order from lowest temperature to highest. The 'lower' field in this data is the second lowest ranked ensemble member. The 'higher' field is the second highest ranked ensemble member. The 'median' field is the central (7th) ranked ensemble member.This gives a median value, and a spread of the ensemble members indicating the level of uncertainty in the projections.Recommendations for use of this data:1. We don't recommend using this data at the resolution of a single cell.The higher resolution of this data improves representation of topography, coasts, etc. but at the same time increases some of the uncertainty for individual grid cells. And so it is recommended to work with multiple grid cells, or an average of grid cells around a point to improve certainty.2. Consider whether the lower, median, or upper projections, or a combination, are most suitable for your use case.As described above, the spread of the ensemble members shown by the lower, median, and upper values indicates the level of uncertainty in the projections.Data source:tas_rcp85_land-rcm_uk_12km_01_ann-30y_200912-207911.nc (median)tas_rcp85_land-rcm_uk_12km_07_ann-30y_200912-207911.nc (lower)tas_rcp85_land-rcm_uk_12km_08_ann-30y_200912-207911.nc (upper)UKCP18 v20190731 (downloaded 04/11/2021)This dataset forms part of the Met Office’s Climate Data Portal service. This service is currently in Beta. We would like your help to further develop our service, please send us feedback via the site - https://climate-themetoffice.hub.arcgis.com/

Aqueduct’s tools map water risks such as floods, droughts, and stress, using open-source, peer reviewed data. Beyond the tools, the Aqueduct team works one-on-one with companies, governments, and research partners to help advance best practices in water resources management and enable sustainable growth in a water-constrained world. Over the past six years, the Aqueduct tools have reached hundreds of thousands of users across the globe, and informed decision-makers in and beyond the water sector. Aqueduct data and insights have been featured in major media outlets including, the Economist, the Guardian, Bloomberg Businessweek, the New York Times and Vox’s Netflix show Explained.

Drought Severity Index, 12-Month Accumulations. Projections for a range of future warming levels from UKCP18. Provided on a 12km BNG grid.This index is not threshold based. Instead, it is calculated with 12-month rainfall deficits provided as a percentage of the mean annual climatological total rainfall (1981–2000) for that location. It is therefore a measure of drought severity, not frequency, and higher values indicate more severe drought.12-month accumulations have been selected as this is likely to indicate hydrological drought - water scarcity over a much longer period of time which heavily deplete water resources on a large scale (as opposed to meterological or agricultural drought, which generally occur on shorter timescales of 3-12 months). However this categorisation is not fixed, because rainfall deficits accumulated over 12-months could lead to different types of drought and drought impacts, depending on the level of vulnerability to reduced rainfall in a region.This data contains a field for each warming level. They are named 'DSI12' (Drought Severity Index for 12 month accumulations), the warming level, and 'upper' 'median' or 'lower' as per the description below. E.g. 'DSI12 2.5 median' is the median value for the 2.5°C projection. Decimal points are included in field aliases but not field names e.g. 'DSI12 2.5 median' is 'DSI12_25_median'. Data defaults to displaying 'DSI12 2.0 median' values, use 'change style' to display other values.The warming levels used are 1.5°C, 2.0°C, 2.5°C, 3.0°C, 4.0°C, and two baselines are also provided for 1981-2000 (corresponding to 0.51°C warming) and 2000-2017 (corresponding to 0.835°C warming).What is the data?The data is from the UKCP18 regional projections using the RCP8.5 scenario. Rather than giving projections for a specific date under different scenarios, one scenario is used and projections are given at the different warming levels. So this data shows the expected Drought Severity Index should these warming levels be reached, at the time that the warming level is reached.For full details, see 'Future Changes to high impact weather in the UK'. HM Hanlon, D Bernie, G Carigi and JA Lowe. Climatic Change, 166, 50 (2021) https://doi.org/10.1007/s10584-021-03100-5What do the 'median', 'upper', and 'lower' values mean?This scenario is run as 12 separate ensemble members. To select which ensemble members to use, a single value was taken from each ensemble member - the mean of a 21yr period centred on the year the warming level was reached. They were then ranked in order from lowest to highest.The 'lower' fields are the second lowest ranked ensemble member.The 'higher' fields are the second highest ranked ensemble member.The 'median' fields are the median average of all ensemble members.This gives a median average value, and a spread of the ensemble members indicating the level of uncertainty in the projections.This dataset forms part of the Met Office’s Climate Data Portal service. This service is currently in Beta. We would like your help to further develop our service, please send us feedback via the site - https://climate-themetoffice.hub.arcgis.com/

The US Energy Information Administration is committed to making its data available through an Application Programming Interface (API) to better serve our customers. APIs allows computers to more easily access our public data. By making EIA data available is this machine readable format, the creativity in the private, the non-profit, and the public sectors can be harnessed to find new ways to analyze and create added-value services powered by public data. On September 21, 2012, EIA's API was released as a beta product with the initial 408,000 electricity series. On Jan 24, 2013 the entire State Energy Data System was added, comprised of over 30,000 additional time-series. On August 23, 126,000 petroleum and natural gas series were added. As we add EIA's coal and Annual Energy Outlook data over the coming months, a significant portion of EIA's data will become available through this interface. The EIA API is offered as a free public service, although registration is required. The registration and compliance with the API Terms of Service will allow EIA to monitor usage and ensure service availability. The API is provided free of charge and should be used in compliance with our Copyrights and Reuse page. Internet Archive URL: https://web.archive.org/web/*/http://www.eia.gov/tools/models/datatools.cfm

Transport for NSW provides projections of employment at the small area (Travel Zone or TZ) level for NSW. The latest version is Travel Zone Projections 2022 (TZP22), released November 2022. This new version TZP22 is an update on the previously published [TZP19](https://opendata.transport.nsw.gov.au/dataset/employment-projections/resource/77e880c1-0073-42bd-850a-ddf974e26cd6) and aligns with the [NSW Government Common Planning Assumptions](https://www.treasury.nsw.gov.au/information-public-entities/common-planning-assumptions). TZP22 Employment Projections are for employed persons by place of work. They are provided by Industry using two breakdowns: * 33 industry categories (equivalent to the ABS 1-digit Australia and New Zealand Standard Industrial Classification (ANZSIC) codes with the exception of Manufacturing which is at 2-digit level). * 4 Broad Industry Categories (groupings of the above) The projections in this release, TZP22 are presented annually 2016 to 2026 and five-yearly from 2026 to 2066 and are in TZ16 geography. Please note, TZP22 is based on best available data as at early to mid 2022. It includes the impacts from the Covid-19 pandemic and does not include results from the ABS 2021 Census as the relevant data had not been released at the time of TZP22 production. **Key Data Inputs used:** * TZP22 Workforce Projections * Census Journey to Work 2016 dataset by Destination Zone - ABS * State-level Employment projections – NSW Treasury * Employment by industry projections - Victoria University * Future Employment Development Database (FEDD) - a custom dataset compiled by TfNSW in late 2019 and updated in mid-2022, that presents the number of jobs expected from major projects based on publicly available documents. For a summary of the TZP22 Projections method please refer to the [TZP22 Factsheet](https://opendata.transport.nsw.gov.au/dataset/employment-projections/resource/cabdece8-98a2-4004-b2bc-30e4d153a2da) For more detail on the projection process please refer to the [TZP22 Technical Guide](https://opendata.transport.nsw.gov.au/dataset/employment-projections/resource/ca2fcd4d-fcaf-412a-b761-e5c86af6f570) Additional land use information for [population](https://opendata.transport.nsw.gov.au/dataset/population-projections) and [workforce](https://opendata.transport.nsw.gov.au/dataset/workforce-projections) as well as [Travel Zone boundaries for NSW](https://opendata.transport.nsw.gov.au/dataset/travel-zones-2016) are also available for download on the Open Data Hub. A visualisation of the employment projections is available on the Transport for NSW Website under [Reference Information.](https://www.transport.nsw.gov.au/data-and-research/reference-information/travel-zone-explorer-visualisation) **Cautions** The TZP22 dataset represents one view of the future aligned with the NSW Government Common Planning Assumptions and population and economic projections. The projections are not based on specific assumptions about future new transport infrastructure, but do take into account known land-use developments underway or planned, and strategic plans. * TZP22 is a strategic state-wide dataset and caution should be exercised when considering results at detailed breakdowns. * The TZP22 outputs represent a point in time set of projections (as at early to mid 2022). * The projections are not government targets. * Travel Zone (TZ) level outputs are projections only and should be used as a guide. As with all small area data, aggregating of travel zone projections to higher geographies leads to more robust results. * As a general rule, TZ-level projections are illustrative of a possible future only. * More specific advice about data reliability for the specific variables projected is provided in the “Read Me” page of the Excel format summary spreadsheets on the TfNSW Open Data Hub. * Caution is advised when comparing TZP22 with the previous set of projections (TZP19) due to addition of new data sources for the most recent years, and adjustments to methodology. **Further cautions and notes can be found in the TZP22 Technical Guide.**

TThe ERS International Macroeconomic Data Set provides historical and projected data for 181 countries that account for more than 99 percent of the world economy. These data and projections are assembled explicitly to serve as underlying assumptions for the annual USDA agricultural supply and demand projections, which provide a 10-year outlook on U.S. and global agriculture. The macroeconomic projections describe the long-term, 10-year scenario that is used as a benchmark for analyzing the impacts of alternative scenarios and macroeconomic shocks. Explore the International Macroeconomic Data Set 2015 for annual growth rates, consumer price indices, real GDP per capita, exchange rates, and more. Get detailed projections and forecasts for countries worldwide. Annual growth rates, Consumer price indices (CPI), Real GDP per capita, Real exchange rates, Population, GDP deflator, Real gross domestic product (GDP), Real GDP shares, GDP, projections, Forecast, Real Estate, Per capita, Deflator, share, Exchange Rates, CPI Afghanistan, Albania, Algeria, Angola, Antigua and Barbuda, Argentina, Armenia, Australia, Austria, Azerbaijan, Bahamas, Bahrain, Bangladesh, Barbados, Belarus, Belgium, Belize, Benin, Bhutan, Bolivia, Bosnia and Herzegovina, Botswana, Brazil, Brunei, Bulgaria, Burkina Faso, Burundi, Côte d'Ivoire, Cabo Verde, Cambodia, Cameroon, Canada, Central African Republic, Chad, Chile, China, Colombia, Congo, Costa Rica, Croatia, Cuba, Cyprus, Denmark, Djibouti, Dominica, Dominican Republic, Ecuador, Egypt, El Salvador, Equatorial Guinea, Eritrea, Estonia, Eswatini, Ethiopia, Fiji, Finland, France, Gabon, Gambia, Georgia, Germany, Ghana, Greece, Grenada, Guatemala, Guinea, Guinea-Bissau, Guyana, Haiti, Honduras, Hungary, Iceland, India, Indonesia, Iran, Iraq, Ireland, Israel, Italy, Jamaica, Japan, Jordan, Kazakhstan, Kenya, Kuwait, Kyrgyzstan, Laos, Latvia, Lebanon, Lesotho, Liberia, Libya, Lithuania, Luxembourg, Madagascar, Malawi, Malaysia, Maldives, Mali, Malta, Mauritania, Mauritius, Mexico, Moldova, Mongolia, Morocco, Mozambique, Myanmar, Namibia, Nepal, Netherlands, New Zealand, Nicaragua, Niger, Nigeria, Norway, Oman, Pakistan, Panama, Papua New Guinea, Paraguay, Peru, Philippines, Poland, Portugal, Qatar, Romania, Russia, Rwanda, Samoa, Saudi Arabia, Senegal, Serbia, Seychelles, Sierra Leone, Singapore, Slovakia, Slovenia, Solomon Islands, South Africa, Spain, Sri Lanka, Sudan, Suriname, Sweden, Switzerland, Syria, Tajikistan, Tanzania, Thailand, Togo, Tonga, Trinidad and Tobago, Tunisia, Turkey, Turkmenistan, Uganda, Ukraine, United Arab Emirates, United Kingdom, Uruguay, Uzbekistan, Vanuatu, Venezuela, Vietnam, Yemen, Zambia, Zimbabwe, WORLD Follow data.kapsarc.org for timely data to advance energy economics research. Developed countries/1 Australia, New Zealand, Japan, Other Western Europe, European Union 27, North America Developed countries less USA/2 Australia, New Zealand, Japan, Other Western Europe, European Union 27, Canada Developing countries/3 Africa, Middle East, Other Oceania, Asia less Japan, Latin America;  Low-income developing countries/4 Haiti, Afghanistan, Nepal, Benin, Burkina Faso, Burundi, Central African Republic, Chad, Democratic Republic of Congo, Eritrea, Ethiopia, Gambia, Guinea, Guinea-Bissau, Liberia, Madagascar, Malawi, Mali, Mozambique, Niger, Rwanda, Senegal, Sierra Leone, Somalia, Tanzania, Togo, Uganda, Zimbabwe; Emerging markets/5  Mexico, Brazil, Chile, Czech Republic, Hungary, Poland, Slovakia, Russia, China, India, Korea, Taiwan, Indonesia, Malaysia, Philippines, Thailand, Vietnam, Singapore BRIICs/5 Brazil, Russia, India, Indonesia, China; Former Centrally Planned Economies Former centrally planned economies/7 Cyprus, Malta, Recently acceded countries, Other Central Europe, Former Soviet Union USMCA/8 Canada, Mexico, United States Europe and Central Asia/9  Europe, Former Soviet Union Middle East and North Africa/10 Middle East and North Africa Other Southeast Asia outlook/11 Malaysia, Philippines, Thailand, Vietnam Other South America outlook/12 Chile, Colombia, Peru, Bolivia, Paraguay, Uruguay Notes: Indicator Source Real gross domestic product (GDP)  World Bank World Development Indicators, IHS Global Insight, Oxford Economics Forecasting, as well as estimated and projected values developed by the Economic Research Service all converted to a 2015 base year.  Real GDP per capita U.S. Department of Agriculture, Economic Research Service, Macroeconomic Data Set, GDP table and Population table. GDP deflator World Bank World Development Indicators, IHS Global Insight, Oxford Economics Forecasting, as well as estimated and projected values developed by the Economic Research Service, all converted to a 2015 base year. Real GDP shares U.S. Department of Agriculture, Economic Research Service, Macroeconomic Data Set, GDP table. Real exchange rates U.S. Department of Agriculture, Economic Research Service, Macroeconomic Data Set, CPI table, and Nominal XR and Trade Weights tables developed by the Economic Research Service. Consumer price indices (CPI) International Financial Statistics International Monetary Fund, IHS Global Insight, Oxford Economics Forecasting, as well as estimated and projected values developed by the Economic Research Service, all converted to a 2015 base year.  Population Department of Commerce, Bureau of the Census, U.S. Department of Agriculture, Economic Research Service, International Data Base.

Monthly averages of global maximum surface temperatures (°C) for 2040-2069 from CRU TS and UKCP18 RCP2.6, provided on an approximately 60km grid.This data contains a field for each month’s average over the period. They are named 'tmax' (temperature maximum), the month, and 'upper' 'median' or 'lower' as per the description below. E.g. 'tmax March Median' is the mean of daily-maximum temperatures in March throughout 2040-2069, in the median ensemble member.Data defaults to displaying January averages. Each monthly average is a field in the data. Use 'show table' to view all values, and 'change style' to change which month is displayed in the map.The grid is a lat-long grid, with cells close to the equator measuring approximately 60kmx60km.More about CRU TS - https://crudata.uea.ac.uk/cru/data/hrg/More about UKCP - https://www.metoffice.gov.uk/research/approach/collaboration/ukcp/indexWhat is the data?The data combines a baseline 1981-2010 value from CRU TS with an anomaly (the temperature change in °C relative to 1981-2010) from UKCP18.The anomaly data is from the UKCP18 regional projections using the RCP2.6 scenario. RCP2.6 is a low emissions scenario, representing a mitigation scenario aiming to limit the increase of global mean temperature to around 2°C above preindustrial levels .What do the 'median', 'upper', and 'lower' values mean?This scenario is run as 12 separate ensemble members. To select which ensemble members to use, a single value for the mean global precipitation for the period 2040-2069 was taken from each ensemble member. They were then ranked in order from lowest precipitation to highest. The 'lower' fields are this data is the second lowest ranked ensemble member. The 'higher' fields are the second highest ranked ensemble member. The 'median' fields are the central (7th) ranked ensemble member.This gives a median value, and a spread of the ensemble members indicating the level of uncertainty in the projections.Recommendations for use of this data:1. We don't recommend using this data at the resolution of a single cell.The higher resolution of this data improves representation of topography, coasts, etc. but at the same time increases some of the uncertainty for individual grid cells. And so it is recommended to work with multiple grid cells, or an average of grid cells around a point to improve certainty.2. Consider whether the lower, median, or upper projections, or a combination, are most suitable for your use case.As described above, the spread of the ensemble members shown by the lower, median, and upper values indicates the level of uncertainty in the projections.Data source: CRU TS v. 4.06 - (downloaded 12/07/22)UKCP18 v.20200110 (downloaded 17/08/22)This dataset forms part of the Met Office’s Climate Data Portal service. This service is currently in Beta. We would like your help to further develop our service, please send us feedback via the site - https://climate-themetoffice.hub.arcgis.com/

Monthly averages of global maximum surface temperatures (°C) for 2070-2099 from CRU TS and UKCP18 RCP2.6, provided on an approximately 60km grid.This data contains a field for each month’s average over the period. They are named 'tmax' (temperature maximum), the month, and 'upper' 'median' or 'lower' as per the description below. E.g. 'tmax March Median' is the mean of daily-maximum temperatures in March throughout 2070-2099, in the median ensemble member.Data defaults to displaying January averages. Each monthly average is a field in the data. Use 'show table' to view all values, and 'change style' to change which month is displayed in the map.The grid is a lat-long grid, with cells close to the equator measuring approximately 60kmx60km.More about CRU TS - https://crudata.uea.ac.uk/cru/data/hrg/More about UKCP - https://www.metoffice.gov.uk/research/approach/collaboration/ukcp/indexWhat is the data?The data combines a baseline 1981-2010 value from CRU TS with an anomaly (the temperature change in °C relative to 1981-2010) from UKCP18.The anomaly data is from the UKCP18 regional projections using the RCP2.6 scenario. RCP2.6 is a low emissions scenario, representing a mitigation scenario aiming to limit the increase of global mean temperature to around 2°C above preindustrial levels .What do the 'median', 'upper', and 'lower' values mean?This scenario is run as 12 separate ensemble members. To select which ensemble members to use, a single value for the mean global precipitation for the period 2070-2099 was taken from each ensemble member. They were then ranked in order from lowest precipitation to highest. The 'lower' fields are this data is the second lowest ranked ensemble member. The 'higher' fields are the second highest ranked ensemble member. The 'median' fields are the central (7th) ranked ensemble member.This gives a median value, and a spread of the ensemble members indicating the level of uncertainty in the projections.Recommendations for use of this data:1. We don't recommend using this data at the resolution of a single cell.The higher resolution of this data improves representation of topography, coasts, etc. but at the same time increases some of the uncertainty for individual grid cells. And so it is recommended to work with multiple grid cells, or an average of grid cells around a point to improve certainty.2. Consider whether the lower, median, or upper projections, or a combination, are most suitable for your use case.As described above, the spread of the ensemble members shown by the lower, median, and upper values indicates the level of uncertainty in the projections.Data source: CRU TS v. 4.06 - (downloaded 12/07/22)UKCP18 v.20200110 (downloaded 17/08/22)This dataset forms part of the Met Office’s Climate Data Portal service. This service is currently in Beta. We would like your help to further develop our service, please send us feedback via the site - https://climate-themetoffice.hub.arcgis.com/

Monthly averages of global minimum surface temperatures (°C) for 2040-2069 from CRU TS and UKCP18 RCP2.6, provided on an approximately 60km grid.This data contains a field for each month’s average over the period. They are named 'tmin' (temperature minimum), the month, and 'upper' 'median' or 'lower' as per the description below. E.g. 'tmin March Median' is the mean of daily-minimum temperatures in March throughout 2040-2069, in the median ensemble member.Data defaults to displaying January averages. Each monthly average is a field in the data. Use 'show table' to view all values, and 'change style' to change which month is displayed in the map.The grid is a lat-long grid, with cells close to the equator measuring approximately 60kmx60km.More about CRU TS - https://crudata.uea.ac.uk/cru/data/hrg/More about UKCP - https://www.metoffice.gov.uk/research/approach/collaboration/ukcp/indexWhat is the data?The data combines a baseline 1981-2010 value from CRU TS with an anomaly (the temperature change in °C relative to 1981-2010) from UKCP18.The anomaly data is from the UKCP18 regional projections using the RCP2.6 scenario. RCP2.6 is a low emissions scenario, representing a mitigation scenario aiming to limit the increase of global mean temperature to around 2°C above preindustrial levels .What do the 'median', 'upper', and 'lower' values mean?This scenario is run as 12 separate ensemble members. To select which ensemble members to use, a single value for the mean global precipitation for the period 2040-2069 was taken from each ensemble member. They were then ranked in order from lowest precipitation to highest. The 'lower' fields are this data is the second lowest ranked ensemble member. The 'higher' fields are the second highest ranked ensemble member. The 'median' fields are the central (7th) ranked ensemble member.This gives a median value, and a spread of the ensemble members indicating the level of uncertainty in the projections.Recommendations for use of this data:1. We don't recommend using this data at the resolution of a single cell.The higher resolution of this data improves representation of topography, coasts, etc. but at the same time increases some of the uncertainty for individual grid cells. And so it is recommended to work with multiple grid cells, or an average of grid cells around a point to improve certainty.2. Consider whether the lower, median, or upper projections, or a combination, are most suitable for your use case.As described above, the spread of the ensemble members shown by the lower, median, and upper values indicates the level of uncertainty in the projections.Data source: CRU TS v. 4.06 - (downloaded 12/07/22)UKCP18 v.20200110 (downloaded 17/08/22)This dataset forms part of the Met Office’s Climate Data Portal service. This service is currently in Beta. We would like your help to further develop our service, please send us feedback via the site - https://climate-themetoffice.hub.arcgis.com/

Monthly averages of global minimum surface temperatures (°C) for 2070-2099 from CRU TS and UKCP18 RCP2.6, provided on an approximately 60km grid.This data contains a field for each month’s average over the period. They are named 'tmin' (temperature minimum), the month, and 'upper' 'median' or 'lower' as per the description below. E.g. 'tmin March Median' is the mean of daily-minimum temperatures in March throughout 2070-2099, in the median ensemble member.Data defaults to displaying January averages. Each monthly average is a field in the data. Use 'show table' to view all values, and 'change style' to change which month is displayed in the map.The grid is a lat-long grid, with cells close to the equator measuring approximately 60kmx60km.More about CRU TS - https://crudata.uea.ac.uk/cru/data/hrg/More about UKCP - https://www.metoffice.gov.uk/research/approach/collaboration/ukcp/indexWhat is the data?The data combines a baseline 1981-2010 value from CRU TS with an anomaly (the temperature change in °C relative to 1981-2010) from UKCP18.The anomaly data is from the UKCP18 regional projections using the RCP2.6 scenario. RCP2.6 is a low emissions scenario, representing a mitigation scenario aiming to limit the increase of global mean temperature to around 2°C above preindustrial levels .What do the 'median', 'upper', and 'lower' values mean?This scenario is run as 12 separate ensemble members. To select which ensemble members to use, a single value for the mean global precipitation for the period 2070-2099 was taken from each ensemble member. They were then ranked in order from lowest precipitation to highest. The 'lower' fields are this data is the second lowest ranked ensemble member. The 'higher' fields are the second highest ranked ensemble member. The 'median' fields are the central (7th) ranked ensemble member.This gives a median value, and a spread of the ensemble members indicating the level of uncertainty in the projections.Recommendations for use of this data:1. We don't recommend using this data at the resolution of a single cell.The higher resolution of this data improves representation of topography, coasts, etc. but at the same time increases some of the uncertainty for individual grid cells. And so it is recommended to work with multiple grid cells, or an average of grid cells around a point to improve certainty.2. Consider whether the lower, median, or upper projections, or a combination, are most suitable for your use case.As described above, the spread of the ensemble members shown by the lower, median, and upper values indicates the level of uncertainty in the projections.Data source: CRU TS v. 4.06 - (downloaded 12/07/22)UKCP18 v.20200110 (downloaded 17/08/22)This dataset forms part of the Met Office’s Climate Data Portal service. This service is currently in Beta. We would like your help to further develop our service, please send us feedback via the site - https://climate-themetoffice.hub.arcgis.com/

Monthly averages of global rainfall amount (mm) for 2040-2069 from CRU TS and UKCP18 RCP2.6, provided on an approximately 60km grid.This data contains a field for each month’s average over the period. They are named 'pr' (precipitation), the month, and 'upper' 'median' or 'lower' as per the description below. E.g. 'pr March Median' is the mean of monthly-total rainfall in March throughout 2040-2069, in the median ensemble member.Data defaults to displaying January averages. Each monthly average is a field in the data. Use 'show table' to view all values, and 'change style' to change which month is displayed in the map.Data has been removed and replaced with 'Null' where the baseline 1981-2010 value was <1mm/month. This is because the percentage change may be unreliable with a very small baseline. 'Null' means that data is not provided, it doesn't mean 0mm precipitation. The grid is a lat-long grid, with cells close to the equator measuring approximately 60kmx60km.More about CRU TS - https://crudata.uea.ac.uk/cru/data/hrg/More about UKCP - https://www.metoffice.gov.uk/research/approach/collaboration/ukcp/indexWhat is the data?The data combines a baseline 1981-2010 value from CRU TS with a percentage change relative to 1981-2010 from UKCP18. Where the baseline value was <1mm/month, the projection value has been replaced with 'Null' because the percentage change may be unreliable with a very small baseline.The percentage change data is from the UKCP18 regional projections using the RCP2.6 scenario. RCP2.6 is a low emissions scenario, representing a mitigation scenario aiming to limit the increase of global mean temperature to around 2°C above preindustrial levels .What do the 'median', 'upper', and 'lower' values mean?This scenario is run as 12 separate ensemble members. To select which ensemble members to use, a single value for the mean global precipitation for the period 2040-2069 was taken from each ensemble member. They were then ranked in order from lowest precipitation to highest. The 'lower' fields are this data is the second lowest ranked ensemble member. The 'higher' fields are the second highest ranked ensemble member. The 'median' fields are the central (7th) ranked ensemble member.This gives a median value, and a spread of the ensemble members indicating the level of uncertainty in the projections.Recommendations for use of this data:1. We don't recommend using this data at the resolution of a single cell.The higher resolution of this data improves representation of topography, coasts, etc. but at the same time increases some of the uncertainty for individual grid cells. And so it is recommended to work with multiple grid cells, or an average of grid cells around a point to improve certainty.2. Consider whether the lower, median, or upper projections, or a combination, are most suitable for your use case.As described above, the spread of the ensemble members shown by the lower, median, and upper values indicates the level of uncertainty in the projections.Data source: CRU TS v. 4.06 - (downloaded 12/07/22)UKCP18 v.20200110 (downloaded 17/08/22)This dataset forms part of the Met Office’s Climate Data Portal service. This service is currently in Beta. We would like your help to further develop our service, please send us feedback via the site - https://climate-themetoffice.hub.arcgis.com/

Monthly averages of global rainfall amount (mm) for 2070-2099 from CRU TS and UKCP18 RCP2.6, provided on an approximately 60km grid.This data contains a field for each month’s average over the period. They are named 'pr' (precipitation), the month, and 'upper' 'median' or 'lower' as per the description below. E.g. 'pr March Median' is the mean of monthly-total rainfall in March throughout 2070-2099, in the median ensemble member.Data defaults to displaying January averages. Each monthly average is a field in the data. Use 'show table' to view all values, and 'change style' to change which month is displayed in the map.Data has been removed and replaced with 'Null' where the baseline 1981-2010 value was <1mm/month. This is because the percentage change may be unreliable with a very small baseline. 'Null' means that data is not provided, it doesn't mean 0mm precipitation. The grid is a lat-long grid, with cells close to the equator measuring approximately 60kmx60km.More about CRU TS - https://crudata.uea.ac.uk/cru/data/hrg/More about UKCP - https://www.metoffice.gov.uk/research/approach/collaboration/ukcp/indexWhat is the data?The data combines a baseline 1981-2010 value from CRU TS with a percentage change relative to 1981-2010 from UKCP18. Where the baseline value was <1mm/month, the projection value has been replaced with 'Null' because the percentage change may be unreliable with a very small baseline.The percentage change data is from the UKCP18 regional projections using the RCP2.6 scenario. RCP2.6 is a low emissions scenario, representing a mitigation scenario aiming to limit the increase of global mean temperature to around 2°C above preindustrial levels .What do the 'median', 'upper', and 'lower' values mean?This scenario is run as 12 separate ensemble members. To select which ensemble members to use, a single value for the mean global precipitation for the period 2070-2099 was taken from each ensemble member. They were then ranked in order from lowest precipitation to highest. The 'lower' fields are this data is the second lowest ranked ensemble member. The 'higher' fields are the second highest ranked ensemble member. The 'median' fields are the central (7th) ranked ensemble member.This gives a median value, and a spread of the ensemble members indicating the level of uncertainty in the projections.Recommendations for use of this data:1. We don't recommend using this data at the resolution of a single cell.The higher resolution of this data improves representation of topography, coasts, etc. but at the same time increases some of the uncertainty for individual grid cells. And so it is recommended to work with multiple grid cells, or an average of grid cells around a point to improve certainty.2. Consider whether the lower, median, or upper projections, or a combination, are most suitable for your use case.As described above, the spread of the ensemble members shown by the lower, median, and upper values indicates the level of uncertainty in the projections.Data source: CRU TS v. 4.06 - (downloaded 12/07/22)UKCP18 v.20200110 (downloaded 17/08/22)This dataset forms part of the Met Office’s Climate Data Portal service. This service is currently in Beta. We would like your help to further develop our service, please send us feedback via the site - https://climate-themetoffice.hub.arcgis.com/

Monthly averages of global surface temperatures (°C) for 2040-2069 from CRU TS and UKCP18 RCP2.6, provided on an approximately 60km grid.This data contains a field for each month’s average over the period. They are named 'tas' (temperature at surface), the month, and 'upper' 'median' or 'lower' as per the description below. E.g. 'tas March Median' is the mean of daily-mean temperatures in March throughout 2040-2069, in the median ensemble member.Data defaults to displaying January averages. Each monthly average is a field in the data. Use 'show table' to view all values, and 'change style' to change which month is displayed in the map.The grid is a lat-long grid, with cells close to the equator measuring approximately 60kmx60km.More about CRU TS - https://crudata.uea.ac.uk/cru/data/hrg/More about UKCP - https://www.metoffice.gov.uk/research/approach/collaboration/ukcp/indexWhat is the data?The data combines a baseline 1981-2010 value from CRU TS with an anomaly (the temperature change in °C relative to 1981-2010) from UKCP18.The anomaly data is from the UKCP18 regional projections using the RCP2.6 scenario. RCP2.6 is a low emissions scenario, representing a mitigation scenario aiming to limit the increase of global mean temperature to around 2°C above preindustrial levels .What do the 'median', 'upper', and 'lower' values mean?This scenario is run as 12 separate ensemble members. To select which ensemble members to use, a single value for the mean global precipitation for the period 2040-2069 was taken from each ensemble member. They were then ranked in order from lowest precipitation to highest. The 'lower' fields are this data is the second lowest ranked ensemble member. The 'higher' fields are the second highest ranked ensemble member. The 'median' fields are the central (7th) ranked ensemble member.This gives a median value, and a spread of the ensemble members indicating the level of uncertainty in the projections.Recommendations for use of this data:1. We don't recommend using this data at the resolution of a single cell.The higher resolution of this data improves representation of topography, coasts, etc. but at the same time increases some of the uncertainty for individual grid cells. And so it is recommended to work with multiple grid cells, or an average of grid cells around a point to improve certainty.2. Consider whether the lower, median, or upper projections, or a combination, are most suitable for your use case.As described above, the spread of the ensemble members shown by the lower, median, and upper values indicates the level of uncertainty in the projections.Data source: CRU TS v. 4.06 - (downloaded 12/07/22)UKCP18 v.20200110 (downloaded 17/08/22)This dataset forms part of the Met Office’s Climate Data Portal service. This service is currently in Beta. We would like your help to further develop our service, please send us feedback via the site - https://climate-themetoffice.hub.arcgis.com/

Monthly averages of global surface temperatures (°C) for 2070-2099 from CRU TS and UKCP18 RCP2.6, provided on an approximately 60km grid.This data contains a field for each month’s average over the period. They are named 'tas' (temperature at surface), the month, and 'upper' 'median' or 'lower' as per the description below. E.g. 'tas March Median' is the mean of daily-mean temperatures in March throughout 2070-2099, in the median ensemble member.Data defaults to displaying January averages. Each monthly average is a field in the data. Use 'show table' to view all values, and 'change style' to change which month is displayed in the map.The grid is a lat-long grid, with cells close to the equator measuring approximately 60kmx60km.More about CRU TS - https://crudata.uea.ac.uk/cru/data/hrg/More about UKCP - https://www.metoffice.gov.uk/research/approach/collaboration/ukcp/indexWhat is the data?The data combines a baseline 1981-2010 value from CRU TS with an anomaly (the temperature change in °C relative to 1981-2010) from UKCP18.The anomaly data is from the UKCP18 regional projections using the RCP2.6 scenario. RCP2.6 is a low emissions scenario, representing a mitigation scenario aiming to limit the increase of global mean temperature to around 2°C above preindustrial levels .What do the 'median', 'upper', and 'lower' values mean?This scenario is run as 12 separate ensemble members. To select which ensemble members to use, a single value for the mean global precipitation for the period 2070-2099 was taken from each ensemble member. They were then ranked in order from lowest precipitation to highest. The 'lower' fields are this data is the second lowest ranked ensemble member. The 'higher' fields are the second highest ranked ensemble member. The 'median' fields are the central (7th) ranked ensemble member.This gives a median value, and a spread of the ensemble members indicating the level of uncertainty in the projections.Recommendations for use of this data:1. We don't recommend using this data at the resolution of a single cell.The higher resolution of this data improves representation of topography, coasts, etc. but at the same time increases some of the uncertainty for individual grid cells. And so it is recommended to work with multiple grid cells, or an average of grid cells around a point to improve certainty.2. Consider whether the lower, median, or upper projections, or a combination, are most suitable for your use case.As described above, the spread of the ensemble members shown by the lower, median, and upper values indicates the level of uncertainty in the projections.Data source: CRU TS v. 4.06 - (downloaded 12/07/22)UKCP18 v.20200110 (downloaded 17/08/22)This dataset forms part of the Met Office’s Climate Data Portal service. This service is currently in Beta. We would like your help to further develop our service, please send us feedback via the site - https://climate-themetoffice.hub.arcgis.com/

Monthly averages of precipitation (mm/day) for 2050-2079 from UKCP18 regional projections (12km grid), using the RCP8.5 pathway.This data contains a field for each month’s average over the period. They are named 'pr' (precipitation), the month, and 'upper' 'median' or 'lower' as per the description below. E.g. 'pr July Median'.UKCP: https://www.metoffice.gov.uk/research/approach/collaboration/ukcp/indexWhat is the data?The data is from the UKCP18 regional projections using the RCP8.5 scenario. RCP8.5 is the highest of the plausible future emissions scenarios used by the IPCC, sometimes referred to as 'business as usual'.What do the 'median', 'upper', and 'lower' values mean?This scenario is run as 12 separate ensemble members. To select which ensemble members to use, a single value for the mean UK precipitation for the period 2050-2079 was taken from each ensemble member. They were then ranked in order from lowest precipitation to highest. The 'lower' fields are this data is the second lowest ranked ensemble member. The 'higher' fields are the second highest ranked ensemble member. The 'median' fields are the central (7th) ranked ensemble member.This gives a median value, and a spread of the ensemble members indicating the level of uncertainty in the projections.Recommendations for use of this data:1. We don't recommend using this data at the resolution of a single cell.The higher resolution of this data improves representation of topography, coasts, etc. but at the same time increases some of the uncertainty for individual grid cells. And so it is recommended to work with multiple grid cells, or an average of grid cells around a point to improve certainty.2. Consider whether the lower, median, or upper projections, or a combination, are most suitable for your use case.As described above, the spread of the ensemble members shown by the lower, median, and upper values indicates the level of uncertainty in the projections.Data source:pr_rcp85_land-rcm_uk_12km_12_mon-30y_200912-207911.nc (median)pr_rcp85_land-rcm_uk_12km_05_mon-30y_200912-207911.nc (lower)pr_rcp85_land-rcm_uk_12km_04_mon-30y_200912-207911.nc (upper)UKCP18 v20190731 (downloaded 04/11/2021)This dataset forms part of the Met Office’s Climate Data Portal service. This service is currently in Beta. We would like your help to further develop our service, please send us feedback via the site - https://climate-themetoffice.hub.arcgis.com/

Monthly averages of surface temperature (C) for 2050-2079 from UKCP18 regional projections (12km grid), using the RCP8.5 pathway.This data contains a field for each month’s average over the period. They are named 'tas' (temperature at surface), the month, and 'upper' 'median' or 'lower' as per the description below. E.g. 'tas July Median'.Data defaults to displaying January averages. Each monthly average is a field in the data. Use 'show table' to view all values, and 'change style' to change which month is displayed in the map.UKCP: https://www.metoffice.gov.uk/research/approach/collaboration/ukcp/indexWhat is the data?The data is from the UKCP18 regional projections using the RCP8.5 scenario. RCP8.5 is the highest of the plausible future emissions scenarios used by the IPCC, sometimes referred to as 'business as usual'.What do the 'median', 'upper', and 'lower' values mean?This scenario is run as 12 separate ensemble members. To select which ensemble members to use, a single value for the mean UK temperature for the period 2050-2079 was taken from each ensemble member. They were then ranked in order from lowest temperature to highest. The 'lower' fields are this data is the second lowest ranked ensemble member. The 'higher' fields are the second highest ranked ensemble member. The 'median' fields are the central (7th) ranked ensemble member.This gives a median value, and a spread of the ensemble members indicating the level of uncertainty in the projections.Recommendations for use of this data:1. We don't recommend using this data at the resolution of a single cell.The higher resolution of this data improves representation of topography, coasts, etc. but at the same time increases some of the uncertainty for individual grid cells. And so it is recommended to work with multiple grid cells, or an average of grid cells around a point to improve certainty.2. Consider whether the lower, median, or upper projections, or a combination, are most suitable for your use case.As described above, the spread of the ensemble members shown by the lower, median, and upper values indicates the level of uncertainty in the projections.Data source:tas_rcp85_land-rcm_uk_12km_01_ann-30y_200912-207911.nc (median)tas_rcp85_land-rcm_uk_12km_07_ann-30y_200912-207911.nc (lower)tas_rcp85_land-rcm_uk_12km_08_ann-30y_200912-207911.nc (upper)UKCP18 v20190731 (downloaded 04/11/2021)This dataset forms part of the Met Office’s Climate Data Portal service. This service is currently in Beta. We would like your help to further develop our service, please send us feedback via the site - https://climate-themetoffice.hub.arcgis.com/

Scénarios de consommation de gaz à horizon 2050 (Perspectives Gaz édition 2022) Ce jeu de données présente le scénario de référence de consommation de gaz en France à horizon 2050 présenté dans le document « Perspectives Gaz 2022 ». Ce document est issu d’une collaboration de GRDF, GRTgaz, Teréga et le SPEGNN, conformément aux préconisations du code de l'énergie. L’article L. 141-10 du code de l’énergie, confère en effet aux gestionnaires de réseaux de transport et de distribution de gaz la responsabilité d’établir, tous les ans, des prévisions pluriannuelles de la demande de gaz et de la production de gaz renouvelables en France. Cette édition 2022 présente une mise à jour du scénario « TERRITOIRES » présenté dans l’édition 2021, lequel intègre une double contrainte : avoir réduit de 50% les émissions de gaz à effet de serre en 2030 ; atteindre l’objectif de neutralité carbone à l'horizon 2050 avec en partis pris un recours limité aux imports possibles de gaz renouvelables et un recours mineur aux voies de séquestration de CO2. Dans le cadre de l’exercice 2021 des Perspectives Gaz, un scénario « TERRITOIRES » avait été élaboré en suivant une approche de modélisation ascendante (ou « bottom-up ») de chaque secteur de consommation. Elle reposait sur l'utilisation et l'exploitation de données émanant de nombreuses études externes (INSEE, SDES, CEREN, ADEME, RTE, AFG, DGEC, ENTSOG, …) et visait à retraduire les dynamiques territoriales déclinées dans les documents de planification régionaux. La révision 2022 de ce scénario (« TERRITOIRES ajusté ») est marginale et vise à refléter l’évolution de contextes sectoriels : la consommation de gaz pour la mobilité a été revue à la baisse pour faire suite aux annonces européennes sur la fin du véhicule thermique léger en 2035 : les consommations de GNV sont désormais uniquement concentrées sur la mobilité lourde, y compris pour la mobilité maritime ; le volume de gaz alloué à la production d’électricité a été ajusté pour coïncider avec les prévisions de RTE (vision intermédiaire entre les différents scénario des Futurs énergétiques 2050). Ce scénario « TERRITOIRES ajusté » demeure donc un scénario cohérent avec une vision nationale basée sur la complémentarité des énergies et des solutions. Les données de consommation de gaz sont présentées par secteur : bâtiment, industrie (hors production d'électricité et cogénération), production d’électricité centralisée et cogénération (nommé "PEC + cogé") et mobilité au gaz. Pour l’ensemble des secteurs, les années 2021 et suivantes sont simulées ; les valeurs fournies pour 2020 correspondent à l'historique des consommations corrigées du climat. L'évolution des secteurs du bâtiment (tertiaire et résidentiel) a été simulée année par année ; pour les autres secteurs, les années 2030 et 2050 ont été simulées puis complétées d'une interpolation pour les années intermédiaires.

Explore population projections for China on this dataset webpage. Get valuable insights into the future demographic trends of one of the world's most populous countries. Population, China, projections ChinaFollow data.kapsarc.org for timely data to advance energy economics research..Total population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship. The values shown are midyear estimatesSource: (1) United Nations Population Division. World Population Prospects: 2019 Revision. (2) Census reports and other statistical publications from national statistical offices, (3) Eurostat: Demographic Statistics, (4) United Nations Statistical Division. Population and Vital Statistics Reprot (various years), (5) U.S. Census Bureau: International Database, and (6) Secretariat of the Pacific Community: Statistics and Demography Programme.

Transport for NSW provides projections of population and dwellings at the small area (Travel Zone or TZ) level for NSW. The latest version is Travel Zone Projections 2022 (TZP22), released November 2022. The projections are developed to support a strategic view of NSW and are aligned with the [NSW Government Common Planning Assumptions](https://www.treasury.nsw.gov.au/information-public-entities/common-planning-assumptions). This new version TZP22 is an update on the previously published [TZP19](https://opendata.transport.nsw.gov.au/dataset/population-projections/resource/08dffce8-081b-4117-91b1-9075566618ac) **The TZP22 Population & Dwellings Projections dataset covers the following variables:** * Estimated Resident Population * Occupied Private Dwellings * Population in Occupied Private Dwellings, by 5-year Age categories & by Sex * Population in Non-Private Dwellings The projections in this release, TZP22, are presented annually 2016 to 2026 and five-yearly from 2026 to 2066, and are in TZ16 geography. Please note, TZP22 is based on best available data as at early to mid 2022. It includes the impacts from the Covid-19 pandemic and does not include results from the ABS 2021 Census as the relevant data had not been released at the time of TZP22 production. **Key Data Inputs used in TZP22:** * [2022 NSW Population projections data](https://www.planning.nsw.gov.au/Research-and-Demography/Population-projections) – NSW Department of Planning, Industry & Environment * [2022 NSW Household and Dwelling projections data](https://www.planning.nsw.gov.au/Research-and-Demography/Population-projections) – NSW Department of Planning, Industry & Environment * [2016 Census data](https://www.abs.gov.au/) - Australian Bureau of Statistics (including dwellings by occupancy, total dwellings by Mesh Block, historical household sizes, private dwellings by occupancy, population age and gender, persons by place of usual residence) * The 2022 NSW Population, Household and Dwelling projections do not include 2021 Census data as the relevant data has not been released at the time of TZP22 production. For a summary of the TZP22 Projections method please refer to the [TZP22 Factsheet](https://opendata.transport.nsw.gov.au/dataset/population-projections/resource/cadd7bb9-da0f-4409-80ea-db0eb4603b8e) For more detail on the projection process please refer to the [TZP22 Technical Guide](https://opendata.transport.nsw.gov.au/dataset/population-projections/resource/cb7f1454-dad7-49f1-97b6-679780a1ffa2) Additional land use information for [workforce](https://opendata.transport.nsw.gov.au/dataset/workforce-projections) and [employment](https://opendata.transport.nsw.gov.au/dataset/employment-projections) as well as [Travel Zone boundaries](https://opendata.transport.nsw.gov.au/dataset/travel-zones-2016) and concordance files are also available for download on the Open Data Hub. A visualisation of the population projections is available on the Transport for NSW Website under [Reference Information](https://www.transport.nsw.gov.au/data-and-research/reference-information/travel-zone-explorer-visualisation). **Cautions** The TZP22 dataset represents one view of the future aligned with the NSW Government Common Planning Assumptions and population and economic projections. The projections are not based on specific assumptions about future new transport infrastructure, but do take into account known land-use developments underway or planned, and strategic plans. * TZP22 is a strategic state-wide dataset and caution should be exercised when considering results at detailed breakdowns. * The TZP22 outputs represent a point in time set of projections (as at early to mid 2022). * The projections are not government targets. * Travel Zone (TZ) level outputs are projections only and should be used as a guide. As with all small area data, aggregating of travel zone projections to higher geographies leads to more robust results. * As a general rule, TZ-level projections are illustrative of a possible future only. * More specific advice about data reliability for the specific variables projected is provided in the “Read Me” page of the Excel format summary spreadsheets on the TfNSW Open Data Hub. * Caution is advised when comparing TZP22 with the previous set of projections (TZP19) due to addition of new data sources for the most recent years, and adjustments to methodology. **Further cautions and notes can be found in the TZP22 Technical Guide**

This API provides data back to 1990 and projections annually, monthly, and quarterly for 18 months. Summarizes the outlook for supply, consumption, inventory, and production capacity for international petroleum and other liquids. Users of the EIA API are required to obtain an API Key via this registration form: http://www.eia.gov/beta/api/register.cfm

This API provides data back to 1990 and projections annually, monthly, and quarterly for 18 months. Summarizes CO2 emissions from coal, fossil fuels, natural gas, and petroleum and other liquid fuels.Users of the EIA API are required to obtain an API Key via this registration form: http://www.eia.gov/beta/api/register.cfm

This API provides data back to 1990 and projections annually, monthly, and quarterly for 18 months. Summarizes the outlook for supply, consumption, inventories, prices and market indicators for U.S. coal. Users of the EIA API are required to obtain an API Key via this registration form: http://www.eia.gov/beta/api/register.cfm

This API provides data back to 1990 and projections annually, monthly, and quarterly for 18 months. It provides data on economic output, income, expenditures, employment, production and price indexes. Users of the EIA API are required to obtain an API Key via this registration form: http://www.eia.gov/beta/api/register.cfm

This API provides data back to 1990 and projections annually, monthly, and quarterly for 18 months. Summarizes the outlook for U.S electricity generation, consumption, retail prices, fuel consumption, fuel inventories, fuel costs, residential usage, and residential customers. Users of the EIA API are required to obtain an API Key via this registration form: http://www.eia.gov/beta/api/register.cfm

This API provides data back to 1990 and projections annually, monthly, and quarterly for 18 months. Summarizes the outlook for supply, consumption, inventories, and prices for U.S. natural gas. Users of the EIA API are required to obtain an API Key via this registration form: http://www.eia.gov/beta/api/register.cfm

This API provides data back to 1990 and projections annually, monthly, and quarterly for 18 months. Summarizes the outlook for U.S. petroleum and other liquids supply, consumption, inventories, refining, and prices. Users of the EIA API are required to obtain an API Key via this registration form: http://www.eia.gov/beta/api/register.cfm

This API provides data back to 1990 and projections annually, monthly, and quarterly for 18 months. Summarizes the outlook for prices of petroleum, natural gas, electricity and coal. Users of the EIA API are required to obtain an API Key via this registration form: http://www.eia.gov/beta/api/register.cfm

This API provides data back to 1990 and projections annually, monthly, and quarterly for 18 months. Summarizes the outlook for renewable energy consumption and renewable generation capacity. Users of the EIA API are required to obtain an API Key via this registration form: http://www.eia.gov/beta/api/register.cfm

This API provides data back to 1990 and projections annually, monthly, and quarterly for 18 months. It provides data on U.S. heating degree days and cooling degree days. Users of the EIA API are required to obtain an API Key via this registration form: http://www.eia.gov/beta/api/register.cfm

Reports in pdf and csv format from the US Energy Information Administration (EIA) with forecast models on crude oil and petroleum liquids, gasoline, diesel, natural gas, electricity, coal prices, supply, and demand projections. This page updates frequently - this snapshot was made Feb. 4, 2017. Includes monthly short-term forecasts (released: the first Tuesday following the first Thursday of each month); Annual projections to 2050; and International projections to 2040. Internet Archive URL: https://web.archive.org/web/2019*/http://www.eia.gov/analysis/projection-data.cfm

Transport for NSW provides projections of workforce at the small area (Travel Zone or TZ) level for NSW. The latest version is Travel Zone Projections 2022 (TZP22), released November 2022. This new version TZP22 is an update on the previously published [TZP19](https://opendata.transport.nsw.gov.au/dataset/workforce-projections/resource/5e331b37-5b9d-4da1-ba36-91b7a265723a) aligned with the [NSW Government Common Planning Assumptions](https://www.treasury.nsw.gov.au/information-public-entities/common-planning-assumptions). TZP22 Workforce Projections cover persons who reside in Occupied Private Dwellings, aged 15 years and over, and are presented by their usual place of residence. The following Workforce variables are presented in TZP22: \* Employed People, 15 years and over in Occupied Private Dwellings \* Unemployed People, 15 years and over in Occupied Private Dwellings \* People not in the workforce, 15 years and over in Occupied Private Dwellings The projections in this release, TZP22, are presented annually 2016 to 2026 and five-yearly from 2026 to 2066, and are in TZ16 geography. Please note, TZP22 is based on best available data as at early to mid 2022. It includes the impacts from the Covid-19 pandemic and does not include results from the ABS 2021 Census as the relevant data had not been released at the time of TZP22 production. **Key Data Inputs used:** \* TZP22 Population and Dwellings projections \* Workforce participation rates - NSW Treasury \* Historical labour force data - ABS Labour Force Survey For a summary of the TZP22 Projections method please refer to the [TZP22 Factsheet](https://opendata.transport.nsw.gov.au/dataset/workforce-projections/resource/dc4a7146-61e3-414b-aa3a-192b409351a6) For more detail on the projection process please refer to the [TZP22 Technical Guide](https://opendata.transport.nsw.gov.au/dataset/workforce-projections/resource/c7336584-b55f-4549-a060-8ec90219c120) Additional land use information for [population](https://opendata.transport.nsw.gov.au/dataset/population-projections) and [employment](https://opendata.transport.nsw.gov.au/dataset/employment-projections) as well as [Travel Zone boundaries for NSW](https://opendata.transport.nsw.gov.au/dataset/travel-zones-2016) and concordance files are also available for download on the Open Data Hub. A visualisation of the workforce projections is available on the Transport for NSW Website under [Reference Information](https://www.transport.nsw.gov.au/data-and-research/reference-information/travel-zone-explorer-visualisation). **Cautions** The TZP22 dataset represents one view of the future aligned with the NSW Government Common Planning Assumptions and population and economic projections. The projections are not based on specific assumptions about future new transport infrastructure, but do take into account known land-use developments underway or planned, and strategic plans. * TZP22 is a strategic state-wide dataset and caution should be exercised when considering results at detailed breakdowns. * The TZP22 outputs represent a point in time set of projections (as at early to mid 2022). * The projections are not government targets. * Travel Zone (TZ) level outputs are projections only and should be used as a guide. As with all small area data, aggregating of travel zone projections to higher geographies leads to more robust results. * As a general rule, TZ-level projections are illustrative of a possible future only. * More specific advice about data reliability for the specific variables projected is provided in the “Read Me” page of the Excel format summary spreadsheets on the TfNSW Open Data Hub. * Caution is advised when comparing TZP22 with the previous set of projections (TZP19) due to addition of new data sources for the most recent years, and adjustments to methodology. **Further cautions and notes can be found in the TZP22 Technical Guide**