The most current data is published on these sheets. Previously published data may be subject to revision. Any change from the originally published data will be highlighted by a comment on the cell in question. These comments will be maintained for at least a year after the date of the value change.

The AQUASTAT portal enables users to access the core database of country statistics, focused on water resources, water uses and agricultural water management. Along with it, other water information in the form of complementary databases, such as the irrigated crop calendars and the sub-national irrigation areas databases, the detailed database on dams and reservoirs and the water-and agriculture-related institutions database are available. The glossary is also an important component of AQUASTAT, offering multilingual definitions of 500+ water-related terms and key indicators, including detailed reference sources and links to related terms.

What does the data show? This dataset shows the change in annual temperature for a range of global warming levels, including the recent past (2001-2020), compared to the 1981-2000 baseline period. Note, as the values in this dataset are averaged over a year they do not represent possible extreme conditions.The dataset uses projections of daily average air temperature from UKCP18 which are averaged to give values for the 1981-2000 baseline, the recent past (2001-2020) and global warming levels. The warming levels available are 1.5°C, 2.0°C, 2.5°C, 3.0°C and 4.0°C above the pre-industrial (1850-1900) period. The recent past value and global warming level values are stated as a change (in °C) relative to the 1981-2000 value. This enables users to compare annual average temperature trends for the different periods. In addition to the change values, values for the 1981-2000 baseline (corresponding to 0.51°C warming) and recent past (2001-2020, corresponding to 0.87°C warming) are also provided. This is summarised in the table below. PeriodDescription 1981-2000 baselineAverage temperature (°C) for the period 2001-2020 (recent past)Average temperature (°C) for the period 2001-2020 (recent past) changeTemperature change (°C) relative to 1981-2000 1.5°C global warming level changeTemperature change (°C) relative to 1981-2000 2°C global warming level changeTemperature change (°C) relative to 1981-20002.5°C global warming level changeTemperature change (°C) relative to 1981-2000 3°C global warming level changeTemperature change (°C) relative to 1981-2000 4°C global warming level changeTemperature change (°C) relative to 1981-2000What is a global warming level?The Annual Average Temperature Change is calculated from the UKCP18 regional climate projections using the high emissions scenario (RCP 8.5) where greenhouse gas emissions continue to grow. Instead of considering future climate change during specific time periods (e.g. decades) for this scenario, the dataset is calculated at various levels of global warming relative to the pre-industrial (1850-1900) period. The world has already warmed by around 1.1°C (between 1850–1900 and 2011–2020), whilst this dataset allows for the exploration of greater levels of warming.   The global warming levels available in this dataset are 1.5°C, 2°C, 2.5°C, 3°C and 4°C. The data at each warming level was calculated using a 21 year period. These 21 year periods are calculated by taking 10 years either side of the first year at which the global warming level is reached. This time will be different for different model ensemble members. To calculate the value for the Annual Average Temperature Change, an average is taken across the 21 year period.We cannot provide a precise likelihood for particular emission scenarios being followed in the real world future. However, we do note that RCP8.5 corresponds to emissions considerably above those expected with current international policy agreements. The results are also expressed for several global warming levels because we do not yet know which level will be reached in the real climate as it will depend on future greenhouse emission choices and the sensitivity of the climate system, which is uncertain. Estimates based on the assumption of current international agreements on greenhouse gas emissions suggest a median warming level in the region of 2.4-2.8°C, but it could either be higher or lower than this level.What are the naming conventions and how do I explore the data?This data contains a field for the 1981-2000 baseline, 2001-2020 period and each warming level. They are named 'tas annual change' (change in air 'temperature at surface'), the warming level or historic time period, and 'upper' 'median' or 'lower' as per the description below. e.g. 'tas annual change 2.0 median' is the median value for the 2.0°C warming level. Decimal points are included in field aliases but not in field names, e.g. 'tas annual change 2.0 median' is named 'tas_annual_change_20_median'. To understand how to explore the data, refer to the New Users ESRI Storymap. Please note, if viewing in ArcGIS Map Viewer, the map will default to ‘tas annual change 2.0°C median’ values.What do the 'median', 'upper', and 'lower' values mean?Climate models are numerical representations of the climate system. To capture uncertainty in projections for the future, an ensemble, or group, of climate models are run. Each ensemble member has slightly different starting conditions or model set-ups. Considering all of the model outcomes gives users a range of plausible conditions which could occur in the future.For this dataset, the model projections consist of 12 separate ensemble members. To select which ensemble members to use, the Annual Average Temperature Change was calculated for each ensemble member and they were then ranked in order from lowest to highest for each location.The ‘lower’ fields are the second lowest ranked ensemble member. The ‘higher’ fields are the second highest ranked ensemble member. The ‘median’ field is the central value of the ensemble.This gives a median value, and a spread of the ensemble members indicating the range of possible outcomes in the projections. This spread of outputs can be used to infer the uncertainty in the projections. The larger the difference between the lower and higher fields, the greater the uncertainty.‘Lower’, ‘median’ and ‘upper’ are also given for the baseline period as these values also come from the model that was used to produce the projections. This allows a fair comparison between the model projections and recent past.  Useful linksFor further information on the UK Climate Projections (UKCP).Further information on understanding climate data within the Met Office Climate Data Portal.

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/

What does the data show? A Cooling Degree Day (CDD) is a day in which the average temperature is above 22°C. It is the number of degrees above this threshold that counts as a Coolin Degree Day. For example if the average temperature for a specific day is 22.5°C, this would contribute 0.5 Cooling Degree Days to the annual sum, alternatively an average temperature of 27°C would contribute 5 Cooling Degree Days. Given the data shows the annual sum of Cooling Degree Days, this value can be above 365 in some parts of the UK.Annual Cooling Degree Days is calculated for two baseline (historical) periods 1981-2000 (corresponding to 0.51°C warming) and 2001-2020 (corresponding to 0.87°C warming) and for global warming levels of 1.5°C, 2.0°C, 2.5°C, 3.0°C, 4.0°C above the pre-industrial (1850-1900) period. This enables users to compare the future number of CDD to previous values.What are the possible societal impacts?Cooling Degree Days indicate the energy demand for cooling due to hot days. A higher number of CDD means an increase in power consumption for cooling and air conditioning, therefore 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.What is a global warming level?Annual Cooling Degree Days are calculated from the UKCP18 regional climate projections using the high emissions scenario (RCP 8.5) where greenhouse gas emissions continue to grow. Instead of considering future climate change during specific time periods (e.g. decades) for this scenario, the dataset is calculated at various levels of global warming relative to the pre-industrial (1850-1900) period. The world has already warmed by around 1.1°C (between 1850–1900 and 2011–2020), whilst this dataset allows for the exploration of greater levels of warming.   The global warming levels available in this dataset are 1.5°C, 2°C, 2.5°C, 3°C and 4°C. The data at each warming level was calculated using a 21 year period. These 21 year periods are calculated by taking 10 years either side of the first year at which the global warming level is reached. This time will be different for different model ensemble members. To calculate the value for the Annual Cooling Degree Days, an average is taken across the 21 year period. Therefore, the Annual Cooling Degree Days show the number of cooling degree days that could occur each year, for each given level of warming. We cannot provide a precise likelihood for particular emission scenarios being followed in the real world future. However, we do note that RCP8.5 corresponds to emissions considerably above those expected with current international policy agreements. The results are also expressed for several global warming levels because we do not yet know which level will be reached in the real climate as it will depend on future greenhouse emission choices and the sensitivity of the climate system, which is uncertain. Estimates based on the assumption of current international agreements on greenhouse gas emissions suggest a median warming level in the region of 2.4-2.8°C, but it could either be higher or lower than this level.What are the naming conventions and how do I explore the data?This data contains a field for each global warming level and two baselines. They are named ‘CDD’ (Cooling Degree Days), the warming level or baseline, 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'. To understand how to explore the data, see this page: https://storymaps.arcgis.com/stories/457e7a2bc73e40b089fac0e47c63a578Please note, if viewing in ArcGIS Map Viewer, the map will default to ‘CDD 2.0°C median’ values.What do the ‘median’, ‘upper’, and ‘lower’ values mean?Climate models are numerical representations of the climate system. To capture uncertainty in projections for the future, an ensemble, or group, of climate models are run. Each ensemble member has slightly different starting conditions or model set-ups. Considering all of the model outcomes gives users a range of plausible conditions which could occur in the future. For this dataset, the model projections consist of 12 separate ensemble members. To select which ensemble members to use, Annual Cooling Degree Days were calculated for each ensemble member and they were then ranked in order from lowest to highest for each location. The ‘lower’ fields are the second lowest ranked ensemble member. The ‘upper’ fields are the second highest ranked ensemble member. The ‘median’ field is the central value of the ensemble.This gives a median value, and a spread of the ensemble members indicating the range of possible outcomes in the projections. This spread of outputs can be used to infer the uncertainty in the projections. The larger the difference between the lower and upper fields, the greater the uncertainty.‘Lower’, ‘median’ and ‘upper’ are also given for the baseline periods as these values also come from the model that was used to produce the projections. This allows a fair comparison between the model projections and recent past.  Useful linksThis dataset was calculated following the methodology in the ‘Future Changes to high impact weather in the UK’ report and uses the same temperature thresholds as the 'State of the UK Climate' report.Further information on the UK Climate Projections (UKCP).Further information on understanding climate data within the Met Office Climate Data Portal.

Annual number of 10mm rainfall days (days where there is greater than or equal to 10mm rainfall) averaged over 1991-2020, provided on a 2km BNG grid.This data contains a field for the average over the period, named 'Rainfall 10mm Days'.Data source:HadUK-Grid v1.1.0.0 (downloaded 11/03/2022)More about HadUK-Grid - https://www.metoffice.gov.uk/research/climate/maps-and-data/data/haduk-grid/haduk-grid 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 number of frost days (days where minimum temperature falls below 0C) averaged over 1991-2020, provided on a 2km BNG grid.This data contains a field for the average over the period, named 'Airfrost Days'.Data source:HadUK-Grid v1.1.0.0 (downloaded 11/03/2022)More about HadUK-Grid - https://www.metoffice.gov.uk/research/climate/maps-and-data/data/haduk-grid/haduk-grid 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 number of icing days (days where maximum temperature is below 0C) averaged over 1991-2020, provided on a 2km BNG grid.This data contains a field for the average over the period, named 'Icing Days'.Data source:HadUK-Grid v1.1.0.0 (downloaded 11/03/2022)More about HadUK-Grid - https://www.metoffice.gov.uk/research/climate/maps-and-data/data/haduk-grid/haduk-grid 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 number of summer days (days where maximum temperature exceeds 25C) averaged over 1991-2020, provided on a 2km BNG grid.This data contains a field for the average over the period, named 'Summer Days'.Data source:HadUK-Grid v1.1.0.0 (downloaded 11/03/2022)More about HadUK-Grid - https://www.metoffice.gov.uk/research/climate/maps-and-data/data/haduk-grid/haduk-grid 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 Traveller Families 2009 to 2012

What does the data show? A Growing Degree Day (GDD) is a day in which the average temperature is above 5.5°C. It is the number of degrees above this threshold that counts as a Growing Degree Day. For example if the average temperature for a specific day is 6°C, this would contribute 0.5 Growing Degree Days to the annual sum, alternatively an average temperature of 10.5°C would contribute 5 Growing Degree Days. Given the data shows the annual sum of Growing Degree Days, this value can be above 365 in some parts of the UK.Annual Growing Degree Days are calculated for two baseline (historical) periods 1981-2000 (corresponding to 0.51°C warming) and 2001-2020 (corresponding to 0.87°C warming) and for global warming levels of 1.5°C, 2.0°C, 2.5°C, 3.0°C, 4.0°C above the pre-industrial (1850-1900) period. This enables users to compare the future number of GDD to previous values. What are the possible societal impacts?Annual Growing Degree Days indicate if conditions are suitable for plant growth. An increase in GDD can indicate larger crop yields due to increased crop growth from warm temperatures, but crop growth also depends on other factors. For example, GDD do not include any measure of rainfall/drought, sunlight, day length or wind, species vulnerability, or plant dieback in extremely high temperatures. GDD can indicate increased crop growth until temperatures reach a critical level above which there are detrimental impacts on plant physiology.GDD does not estimate the growth of specific species and is not a measure of season length.What is a global warming level?Annual Growing Degree Days are calculated from the UKCP18 regional climate projections using the high emissions scenario (RCP 8.5) where greenhouse gas emissions continue to grow. Instead of considering future climate change during specific time periods (e.g. decades) for this scenario, the dataset is calculated at various levels of global warming relative to the pre-industrial (1850-1900) period. The world has already warmed by around 1.1°C (between 1850–1900 and 2011–2020), whilst this dataset allows for the exploration of greater levels of warming.   The global warming levels available in this dataset are 1.5°C, 2°C, 2.5°C, 3°C and 4°C. The data at each warming level was calculated using a 21 year period. These 21 year periods are calculated by taking 10 years either side of the first year at which the global warming level is reached. This time will be different for different model ensemble members. To calculate the value for the Annual Growing Degree Days, an average is taken across the 21 year period. Therefore, the Annual Growing Degree Days show the number of growing degree days that could occur each year, for each given level of warming. We cannot provide a precise likelihood for particular emission scenarios being followed in the real world future. However, we do note that RCP8.5 corresponds to emissions considerably above those expected with current international policy agreements. The results are also expressed for several global warming levels because we do not yet know which level will be reached in the real climate as it will depend on future greenhouse emission choices and the sensitivity of the climate system, which is uncertain. Estimates based on the assumption of current international agreements on greenhouse gas emissions suggest a median warming level in the region of 2.4-2.8°C, but it could either be higher or lower than this level.What are the naming conventions and how do I explore the data?This data contains a field for each global warming level and two baselines. They are named 'GDD' (Growing Degree Days), the warming level or baseline, 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’. To understand how to explore the data, see this page: https://storymaps.arcgis.com/stories/457e7a2bc73e40b089fac0e47c63a578Please note, if viewing in ArcGIS Map Viewer, the map will default to ‘GDD 2.0°C median’ values.What do the ‘median’, ‘upper’, and ‘lower’ values mean?Climate models are numerical representations of the climate system. To capture uncertainty in projections for the future, an ensemble, or group, of climate models are run. Each ensemble member has slightly different starting conditions or model set-ups. Considering all of the model outcomes gives users a range of plausible conditions which could occur in the future. For this dataset, the model projections consist of 12 separate ensemble members. To select which ensemble members to use, Annual Growing Degree Days were calculated for each ensemble member and they were then ranked in order from lowest to highest for each location. The ‘lower’ fields are the second lowest ranked ensemble member. The ‘upper’ fields are the second highest ranked ensemble member. The ‘median’ field is the central value of the ensemble.This gives a median value, and a spread of the ensemble members indicating the range of possible outcomes in the projections. This spread of outputs can be used to infer the uncertainty in the projections. The larger the difference between the lower and upper fields, the greater the uncertainty.‘Lower’, ‘median’ and ‘upper’ are also given for the baseline periods as these values also come from the model that was used to produce the projections. This allows a fair comparison between the model projections and recent past.  Useful linksThis dataset was calculated following the methodology in the ‘Future Changes to high impact weather in the UK’ report and uses the same temperature thresholds as the 'State of the UK Climate' report.Further information on the UK Climate Projections (UKCP).Further information on understanding climate data within the Met Office Climate Data Portal.

What does the data show? A Heating Degree Day (HDD) is a day in which the average temperature is below 15.5°C. It is the number of degrees above this threshold that counts as a Heating Degree Day. For example if the average temperature for a specific day is 15°C, this would contribute 0.5 Heating Degree Days to the annual sum, alternatively an average temperature of 10.5°C would contribute 5 Heating Degree Days. Given the data shows the annual sum of Heating Degree Days, this value can be above 365 in some parts of the UK.Annual Heating Degree Days is calculated for two baseline (historical) periods 1981-2000 (corresponding to 0.51°C warming) and 2001-2020 (corresponding to 0.87°C warming) and for global warming levels of 1.5°C, 2.0°C, 2.5°C, 3.0°C, 4.0°C above the pre-industrial (1850-1900) period. This enables users to compare the future number of HDD to previous values.What are the possible societal impacts?Heating Degree Days indicate the energy demand for heating due to cold days.  A higher number of HDD means an increase in power consumption for heating, therefore this index is useful for predicting future changes in energy demand for heating.What is a global warming level?Annual Heating Degree Days are calculated from the UKCP18 regional climate projections using the high emissions scenario (RCP 8.5) where greenhouse gas emissions continue to grow. Instead of considering future climate change during specific time periods (e.g. decades) for this scenario, the dataset is calculated at various levels of global warming relative to the pre-industrial (1850-1900) period. The world has already warmed by around 1.1°C (between 1850–1900 and 2011–2020), whilst this dataset allows for the exploration of greater levels of warming.   The global warming levels available in this dataset are 1.5°C, 2°C, 2.5°C, 3°C and 4°C. The data at each warming level was calculated using a 21 year period. These 21 year periods are calculated by taking 10 years either side of the first year at which the global warming level is reached. This time will be different for different model ensemble members. To calculate the value for the Annual Heating Degree Days, an average is taken across the 21 year period. Therefore, the Annual Heating Degree Days show the number of heating degree days that could occur each year, for each given level of warming. We cannot provide a precise likelihood for particular emission scenarios being followed in the real world future. However, we do note that RCP8.5 corresponds to emissions considerably above those expected with current international policy agreements. The results are also expressed for several global warming levels because we do not yet know which level will be reached in the real climate as it will depend on future greenhouse emission choices and the sensitivity of the climate system, which is uncertain. Estimates based on the assumption of current international agreements on greenhouse gas emissions suggest a median warming level in the region of 2.4-2.8°C, but it could either be higher or lower than this level.What are the naming conventions and how do I explore the data?This data contains a field for each warming level and two baselines. They are named ‘HDD’ (Heating Degree Days), the warming level or baseline, 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'. To understand how to explore the data, see this page: https://storymaps.arcgis.com/stories/457e7a2bc73e40b089fac0e47c63a578Please note, if viewing in ArcGIS Map Viewer, the map will default to ‘HDD 2.0°C median’ values.What do the ‘median’, ‘upper’, and ‘lower’ values mean?Climate models are numerical representations of the climate system. To capture uncertainty in projections for the future, an ensemble, or group, of climate models are run. Each ensemble member has slightly different starting conditions or model set-ups. Considering all of the model outcomes gives users a range of plausible conditions which could occur in the future. For this dataset, the model projections consist of 12 separate ensemble members. To select which ensemble members to use, Annual Heating Degree Days were calculated for each ensemble member and they were then ranked in order from lowest to highest for each location. The ‘lower’ fields are the second lowest ranked ensemble member. The ‘upper’ fields are the second highest ranked ensemble member. The ‘median’ field is the central value of the ensemble.This gives a median value, and a spread of the ensemble members indicating the range of possible outcomes in the projections. This spread of outputs can be used to infer the uncertainty in the projections. The larger the difference between the lower and upper fields, the greater the uncertainty.‘Lower’, ‘median’ and ‘upper’ are also given for the baseline periods as these values also come from the model that was used to produce the projections. This allows a fair comparison between the model projections and recent past.  Useful linksThis dataset was calculated following the methodology in the ‘Future Changes to high impact weather in the UK’ report and uses the same temperature thresholds as the 'State of the UK Climate' report.Further information on the UK Climate Projections (UKCP).Further information on understanding climate data within the Met Office Climate Data Portal.

Prior to 1974 the data was based on surveys of existing house sales in Dublin carried out by the Valuation Office on behalf of the D. O. E. Since 1974 the data has been based on information supplied by all lending agencies on the average price of mortgage financed existing house transactions. Average house prices are derived from data supplied by the mortgage lending agencies on loans approved by them rather than loans paid. In comparing house prices figures from one period to another, account should be taken of the fact that changes in the mix of houses (incl apartments) will affect the average figures. Data for 1969/1970 is not available for Cork, Limerick, Galway, Waterford and Other areas The most current data is published on these sheets. Previously published data may be subject to revision. Any change from the originally published data will be highlighted by a comment on the cell in question. These comments will be maintained for at least a year after the date of the value change. National and Other Areas figure changed for 2015 on 27/6/15 as revised data received from Local Authorities Prices includes houses and apartments measured in €

Aqueduct Floods is an online platform that measures riverine and coastal flood risks under both current baseline conditions and future projections in 2030, 2050, an 2080

The Aqueduct Global Flood Risk Country Ranking ranks 163 countries by their current annual average population affected by river floods.

Aqueduct 3.0 introduces an updated water risk framework and new and improved indicators. It also features different hydrological sub-basins. We introduce indicators based on a new hydrological model that now features (1) integrated water supply and demand, (2) surface water and groundwater modeling, (3) higher spatial resolution, and (4) a monthly time series that enables the provision of monthly scores for selected indicators.

Bell Creek Field micellar-polymer pilot demonstration. Fourth annual report, October 1979-September 1980 DOE/SF/01802-56

Developed through collaboration between The Nature Conservancy, The University of Washington, and The University of Southern Mississippi, the Climate Wizard enables technical and non-technical audiences alike to easily and intuitively access leading climate change information and visualize the impacts anywhere on Earth. Climate Wizard Custom is a new tool where a user can define a relatively small geographic area of interest and conduct site-specific analyses using both historical data and possible future conditions that are based on low (B1), moderate (A1B), and high (A2) carbon emissions scenarios. Sixteen general circulation models are available to provide a range of possible outcomes, and users can analyze absolute and percentage changes in annual, seasonal or monthly climate conditions in graphic or map form. Since the large climate datasets are stored and analyzed remotely on powerful computers, users of the tool do not need to have fast computers or expensive software, but simply need access to the internet. Using web technologies to develop tools that make climate change analysis more accessible scientists, managers, and policy makers now have the ability to assess the potential impacts of climate change and help guide decisions and actions to prepare for and mitigate those impacts to natural systems and the services they provide.

Determination of Optimum Air (Gas) Injection Rate in Aerated Drilling Operations, Annual Report; May 1, 1979-April 30, 1980

Development of Mobility Control Methods to Improve Oil Recovery by CO2, Second Annual Report, September 1982

Development of Mobility Control Methods to Improve Oil Recovery by CO2, Annual Report, March 1981

DOE/MC/03259-10

Enhanced Oil Recovery by Surfactant-Enhanced Volumetric Sweep Efficiency, Second Annual Report, September 1986-September 1987

DOE/BC/14447-10

The GFMS is a NASA-funded experimental system using real-time TRMM Multi-satellite Precipitation Analysis (TMPA) and Global Precipitation Measurement (GPM) Integrated Multi-Satellite Retrievals for GPM (IMERG) precipitation information as input to a quasi-global (50°N - 50°S) hydrological runoff and routing model running on a 1/8th degree latitude/longitude grid. Flood detection/intensity estimates are based on 13 years of retrospective model runs with TMPA input, with flood thresholds derived for each grid location using surface water storage statistics (95th percentile plus parameters related to basin hydrologic characteristics). Streamflow,surface water storage,inundation variables are also calculated at 1km resolution.In addition, the latest maps of instantaneous precipitation and totals from the last day, three days and seven days are displayed.

This dataset provides near-surface meteorological data for driving land surface models and other terrestrial modeling systems. It blends reanalysis data with observations and disaggregates in time and space. The dataset is currently available at 1.0 degree (plus 0.5 and 0.25 degree), 3-hourly (plus daily and monthly) resolution globally for 1948-2008. Experimental updates include a 1901-2012 version (that will become V2), real-time updates, higher resolution versions for Africa (that assimilates all available gauge data) and future climate projections based on bias-corrected climate model output

This archive contains estimates of runoff to the ocenas for all river outlets globally, excluding Greenland and Antarctica, based on routing through the simulated topological network at 30-minute spatial resolution (STN-30p, version 6.01; 2004–07) flow network [Vörösmarty et al. 2000; downloaded from Water Systems Analysis Group (2007)] at 1/2-degree latitude-by-longitude resolution using the Lohmann et al. (1996, 1998) routing model. The data set is a hybrid of simulated and observed streamflow for 4 model-method combinations, as described in Clark et al., J. Hydrometeor. (2015).

DOE/BC/10321-5

The overarching project objective is to demonstrate the feasibility of using an innovative PowerTake-Off (PTO) Module in Columbia Power's utility-scale wave energy converter (WEC). The PTO Module uniquely combines a large-diameter, direct-drive, rotary permanent magnet generator; a patent-pending rail-bearing system; and a corrosion-resistant fiber-reinforced-plastic structure

Values in Euro for all files.

Measuring and Predicting Reservoir Heterogeneity in Complex Deposystems, Annual Report; August 1992

This series does not include house prices. Measured in €

This series does not include apartment prices. 2015 Figure changed on the 27/6/16 as revised data received from the Local authority Measured in €

This series includes both house and apartment prices. 2015 Figure changed on the 27/6/16 as revised data received from the Local authority Measured in €

Numerical Modeling of Massive Hydraulic Fractures, Annual Report; July 1983

Numerical Modeling of Massive Hydraulic Fractures, First Annual Report; September 1980-August 1981

Polymers for Mobility Control in Enhanced Oil Recovery, Third Annual Report, October 1987-September 1988

Annual New Property prices by cities from 1969 to 2015 Prior to 1974 the data was based on surveys of existing house sales in Dublin carried out by the Valuation Office on behalf of the D. O. E. Since 1974 the data has been based on information supplied by all lending agencies on the average price of mortgage financed existing house transactions. Average house prices are derived from data supplied by the mortgage lending agencies on loans approved by them rather than loans paid. In comparing house prices figures from one period to another, account should be taken of the fact that changes in the mix of houses (incl apartments) will affect the average figures. Data for 1969/1970 is not available for Cork, Limerick, Galway, Waterford and Other areas The most current data is published on these sheets. Previously published data may be subject to revision. Any change from the originally published data will be highlighted by a comment on the cell in question. These comments will be maintained for at least a year after the date of the value change. National and Other Areas figure changed for 2015 on 27/6/15 as revised data received from Local Authorities Prices includes houses and apartments measured in €

Research in the SUPRI Heavy Oil Research Project is summarized here. There are six subdivisions in this project. The goal of Project 1 is to assess the influence of different reservoir conditions on the absolute and relative permeability to oil and water and on capillary pressure. Project 2 deals with the evaluation of the effects of different reservoir parameters on the in-situ combustion process including reaction kinetics. The object of Project 3 is to develop and understand the mechanisms of the process using commercially available surfactants for reduction of gravity override and channeling of steam. Project 4 is concerned with the development of techniques of formation evaluation such as tracer tests and pressure transient tests. Finally, Project 5 is concerned with the technical support for the design and monitoring of DOE sponsored or industry initiated field projects.

This series excludes second hand house prices. Measured in €

This series excludes second hand apartment prices. 2015 Figure changed on the 27/6/16 as revised data received from the Local authority Measured in €

Teal is a free visual tool that enables you to explore climate variables for the past 70+ years, from 1950 to near real time at annual, monthly, seasonal, and daily frequency.

Global Active Archive of Large Flood Events, 1985-Present

A tool that globally detects and monitors flood events. It provides a real-time overview of ongoing flood events based on filtered Twitter data. Specifically, the global flood monitor (GFM) detects, in real-time, regions with enhanced flood-related Twitter activity and classifies these as flood events.

annual sum of the global radiation amount. Klimaindizes für Globalstrahlung von 1980 bis 2012, Jahreswerte.

monthly sum of the global radiation amount. Klimaindizes für Globalstrahlung von 1980 bis 2012, Monatswerte.

seasonal sum of the global radiation amount. Klimaindizes für Globalstrahlung von 1980 bis 2012, saisonale Werte