The highest average temperature recorded in 2024 until November was in August, at 16.8 degrees Celsius. Since 2015, the highest average daily temperature in the UK was registered in July 2018, at 18.7 degrees Celsius. The summer of 2018 was the joint hottest since institutions began recording temperatures in 1910. One noticeable anomaly during this period was in December 2015, when the average daily temperature reached 9.5 degrees Celsius. This month also experienced the highest monthly rainfall in the UK since before 2014, with England, Wales, and Scotland suffering widespread flooding. Daily hours of sunshine Unsurprisingly, the heat wave that spread across the British Isles in 2018 was the result of particularly sunny weather. July 2018 saw an average of 8.7 daily sun hours in the United Kingdom. This was more hours of sun than was recorded in July 2024, which only saw 5.8 hours of sun. Temperatures are on the rise Since the 1960s, there has been an increase in regional temperatures across the UK. Between 1961 and 1990, temperatures in England averaged nine degrees Celsius, and from 2013 to 2022, average temperatures in the country had increased to 10.3 degrees Celsius. Due to its relatively southern location, England continues to rank as the warmest country in the UK.

The average temperature across the United Kingdom presented a trend of continuous growth since 1961. During the first period, from 1961 to 1990, the country recorded an average temperature of *** degrees Celsius. In the next period, from 1991 to 2020, the UK's average temperature increased by *** degrees Celsius and increased further by *** degrees Celsius between 2014 and 2023. In the latter year, figures remained at ** degrees Celsius, *** degrees warmer than the average recorded between 1961 and 1990, illustrating the effects of climate change. Nevertheless, 2022 was the warmest year in the United Kingdom.

Temperature in the United Kingdom decreased to 9.88 celsius in 2024 from 10.14 celsius in 2023. This dataset includes a chart with historical data for the United Kingdom Average Temperature.

The annual mean temperature in the United Kingdom has fluctuated greatly since 1990. Temperatures during this period were at their highest in 2022, surpassing ** degrees Celsius. In 2010, the mean annual temperature stood at **** degrees, the lowest recorded during this time. Daily temperatures Average daily temperatures have remained stable since the turn of the century, rarely dropping below ** degrees Celsius. In 2010, they dropped to a low of **** degrees Celsius. The peak average daily temperature was recorded in 2022 when it reached **** degrees. This was an increase of *** degree Celsius compared to the long-term mean, and the most positive deviation during the period of consideration. Highs and lows The maximum average temperature recorded across the UK since 2015 was in July 2018. This month saw a maximum temperature of **** degrees Celsius. In comparison, the lowest monthly minimum temperature was in February of the same year, at just minus *** degrees. This was an especially cold February, as the previous year the minimum temperature for this month was *** degrees.

The UK Climate Projections 2009 (UKCP09) projections of temperature from low, medium and high emissions scenarios' equivalent global temperature changes. They are probabilistic climate predictions based on families of runs of the Met Office Hadley Centre climate models HadCM3, HadRM3 and HadSM3, plus climate models from other climate centres contributing to IPCC AR4 and CMIP3.

The equivalent changes in global temperatures are taken from three emissions scenarios: low (IPCC SRES: B1), medium (IPCC SRES: A1B), and high (IPCC SRES: A1FI). Each scenario provides estimates over seven 30 year period averages: 2010-2039, 2030s = 2020-2049, 2040s = 2030-2059, 2050s = 2040-2069, 2060s = 2050-2079, 2070s = 2060-2089, 2080s = 2070-2099. Temperature changes are given relative to 1961-1990.

Regional climate values for an element, ordered by year -Minimum Tempature. Allowances have been made for topographic, coastal and urban effects where relationships are found to exist. Seasons: Winter=Dec-Feb, Spring=Mar-May, Summer=June-Aug, Autumn=Sept-Nov. (Winter: Year refers to Jan/Feb).

This data-set contains 3 fields for each fixed period (1981-2000, 2001-2020) and Global Warming Level (1.5°C, 2°C, 2.5°C, 3°C, 3.5°C, 4°C) combination: the median, 2nd lowest and 2nd highest among the 12 ensemble members. The fields are named accordingly; e.g. the 2nd lowest at 2.5°C is tas_winter_25_lowerTo understand the data, refer to the LACS Scientific Detail.To understand how to explore the data, see the User Guides available on the Climate Data Portal.

[Updated 28/01/25 to fix an issue in the ‘Lower’ values, which were not fully representing the range of uncertainty. ‘Median’ and ‘Higher’ values remain unchanged. The size of the change varies by grid cell and fixed period/global warming levels but the average difference between the 'lower' values before and after this update is 0.09°C.]What does the data show? This dataset shows the change in summer average temperature for a range of global warming levels, including the recent past (2001-2020), compared to the 1981-2000 baseline period. Here, summer is defined as June-July-August. Note, as the values in this dataset are averaged over a season they do not represent possible extreme conditions.The dataset uses projections of daily average air temperature from UKCP18 which are averaged over the summer period 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 summer 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.PeriodDescription1981-2000 baselineAverage temperature (°C) for the period2001-2020 (recent past)Average temperature (°C) for the period2001-2020 (recent past) changeTemperature change (°C) relative to 1981-20001.5°C global warming level changeTemperature change (°C) relative to 1981-20002°C global warming level changeTemperature change (°C) relative to 1981-20002.5°C global warming level changeTemperature change (°C) relative to 1981-20003°C global warming level changeTemperature change (°C) relative to 1981-20004°C global warming level changeTemperature change (°C) relative to 1981-2000What is a global warming level?The Summer 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 Summer 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?These data contain a field for each warming level and the 1981-2000 baseline. They are named 'tas summer change' (change in air 'temperature at surface'), the warming level or baseline, and 'upper' 'median' or 'lower' as per the description below. e.g. 'tas summer change 2.0 median' is the median value for summer for the 2.0°C warming level. Decimal points are included in field aliases but not in field names, e.g. 'tas summer change 2.0 median' is named 'tas_summer_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 summer 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 Summer 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.

England's highest monthly mean air temperatures are typically recorded in July and August of each year. Since 2015, the warmest mean temperature was measured in July 2018 at 18.8 degrees Celsius. On the other hand, February of that same year registered the coolest temperature, at 2.6 degrees Celsius. In April 2025, the mean air temperature was 10.3 degrees Celsius, slightly higher than the same month the previous year. The English weather England is the warmest region in the United Kingdom and the driest. In 2024, the average annual temperature in England amounted to 10.73 degrees Celsius – around 1.1 degrees above the national mean. That same year, precipitation in England stood at about 1,020 millimeters. By contrast, Scotland – the wettest region in the UK – recorded over 1,500 millimeters of rainfall in 2024. Temperatures on the rise Throughout the last decades, the average temperature in the United Kingdom has seen an upward trend, reaching a record high in 2022. Global temperatures have experienced a similar pattern over the same period. This gradual increase in the Earth's average temperature is primarily due to various human activities, such as burning fossil fuels and deforestation, which lead to the emission of greenhouse gases. This phenomenon has severe consequences, including more frequent and intense weather events, rising sea levels, and adverse effects on human health and the environment.

What does the data show?

This data shows the monthly averages of surface temperature (°C) for 2040-2069 using a combination of the CRU TS (v. 4.06) and UKCP18 global RCP2.6 datasets. The RCP2.6 scenario is an aggressive mitigation scenario where greenhouse gas emissions are strongly reduced.

The data combines a baseline (1981-2010) value from CRU TS (v. 4.06) with an anomaly from UKCP18 global. Where the anomaly is the change in temperature at 2040-2069 relative to 1981-2010.

The data is provided on the WGS84 grid which measures approximately 60km x 60km (latitude x longitude) at the equator.

Limitations of the data

We recommend the use of multiple grid cells or an average of grid cells around a point of interest to help users get a sense of the variability in the area. This will provide a more robust set of values for informing decisions based on the data.

What are the naming conventions and how do I explore the data?

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’. E.g. ‘tas Mar Lower’ is the average of the daily average temperatures in March throughout 2040-2069, in the second lowest ensemble member.

To understand how to explore the data, see this page: https://storymaps.arcgis.com/stories/457e7a2bc73e40b089fac0e47c63a578

Please note, if viewing in ArcGIS Map Viewer, the map will default to ‘tas Jan 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.

To select which ensemble members to use, the monthly averages of surface temperature for the period 2040-2069 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.

Data source

CRU TS v. 4.06 - (downloaded 12/07/22)

UKCP18 v.20200110 (downloaded 17/08/22)

Useful links

Further information on CRU TS Further information on the UK Climate Projections (UKCP) Further information on understanding climate data within the Met Office Climate Data Portal

[Updated 28/01/25 to fix an issue in the ‘Lower’ values, which were not fully representing the range of uncertainty. ‘Median’ and ‘Higher’ values remain unchanged. The size of the change varies by grid cell and fixed period/global warming levels but the average difference between the 'lower' values before and after this update is 0.37°C.]What does the data show? This dataset shows the change in winter minimum temperature for a range of global warming levels, including the recent past (2001-2020), compared to the 1981-2000 baseline period. Here, winter is defined as December-January-February.The dataset uses projections of daily minimum 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 winter minimum 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.PeriodDescription1981-2000 baselineAverage temperature (°C) for the period2001-2020 (recent past)Average temperature (°C) for the period2001-2020 (recent past) changeTemperature change (°C) relative to 1981-20001.5°C global warming level changeTemperature change (°C) relative to 1981-20002°C global warming level changeTemperature change (°C) relative to 1981-20002.5°C global warming level changeTemperature change (°C) relative to 1981-20003°C global warming level changeTemperature change (°C) relative to 1981-20004°C global warming level changeTemperature change (°C) relative to 1981-2000What is a global warming level?The Winter Minimum 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 Winter Minimum 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?These data contain a field for each warming level and the 1981-2000 baseline. They are named 'tasmin winter change' (change in air 'temperature at surface'), the warming level or baseline, and 'upper' 'median' or 'lower' as per the description below. e.g. ‘tasmin winter change 2.0 median' is the median value for winter for the 2.0°C warming level. Decimal points are included in field aliases but not in field names, e.g. 'tasmin winter change 2.0 median' is named ‘tasmin_winter_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 ‘tasmin winter 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 Winter Minimum 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.

This dataset provides daily-mean sea surface temperatures (SST), presented on global 0.05° latitude-longitude grid, spanning 1980 to present. This is a Level 4 product, with gaps between available daily observations filled by statistical means.

The SST CCI Analysis product contains estimates of daily mean SST and sea ice concentration. Each SST value has an associated uncertainty estimate.

The dataset has been produced as part of the version 3 Climate Data Record (CDR) produced by the European Space Agency (ESA) Climate Change Initiative Sea Surface Temperature project (ESA SST_cci). The CDR accurately maps the surface temperature of the global oceans over the period 1980 to 2021 using observations from many satellites, with a high degree of independence from in situ measurements. The data provide independently quantified SSTs to a quality suitable for climate research.

Data from 2022 onwards are provided as an Interim Climate Data Record (ICDR) and will be updated daily at one month behind present. The Copernicus Climate Change Service (C3S) funded the development of the ICDR extension and production of the ICDR during 2022. From 2023 onwards the production of the ICDR is funded by the UK Earth Observation Climate Information Service (EOCIS) and Marine and Climate Advisory Service (MCAS).

This CDR Version 3.0 product supersedes the CDR v2.1 product. Compared to the previous version the major changes are:

• Longer time series: 1980 to 2021 (previous CDR was Sept 1981 to 2016)

• Improved retrieval to reduce systematic biases using bias-aware optimal methods (for single view sensors)

• Improved retrieval with respect to desert-dust aerosols

• Addition of dual-view SLSTR data from 2016 onwards

• Addition of early AVHRR/1 data in 1980s, and improved AVHRR processing to reduce data gaps in 1980s

• Use of full-resolution MetOp AVHRR data (previously used ‘global area coverage’ Level 1 data)

• Inclusion of L2P passive microwave AMSR data

Data are made freely and openly available under a Creative Commons License by Attribution (CC By 4.0) https://creativecommons.org/licenses/by/4.0/

When citing this dataset please also cite the associated data paper:

Embury, O., Merchant, C.J., Good, S.A., Rayner, N.A., Høyer, J.L., Atkinson, C., Block, T., Alerskans, E., Pearson, K.J., Worsfold, M., McCarroll, N., Donlon, C. Satellite-based time-series of sea-surface temperature since 1980 for climate applications. Scientific Data 11, 326 (2024). https://doi.org/10.1038/s41597-024-03147-w

This data represents the probabilistic climate projections component of the past (observed) and future climate scenario projections data, produced as part of the UK Climate Projections 2018 (UKCP18) project. Data has been produced by the UK Met Office Hadley Centre, and provides information on changes in 21st century climate for the UK, helping to inform adaptation to a changing climate.

The data represents mean global temperature anomalies with respect to the baseline periods 1981-2000, 1961-1990 or 1981-2010, and cover the period 1861 to 2100.

UKCP09: Gridded datasets of annual values.Winter heatwave duration. The day-by-day sum of the mean number of degrees by which the air temperature is more than a value of 22 °C As summer heat wave but for November–April.

The datasets have been created with financial support from the Department for Environment, Food and Rural Affairs (Defra) and they are being promoted by the UK Climate Impacts Programme (UKCIP) as part of the UK Climate Projections (UKCP09). http://ukclimateprojections.defra.gov.uk/content/view/12/689/.

To view this data you will have to register on the Met Office website, here: http://www.metoffice.gov.uk/research/climate/climate-monitoring/UKCP09/register

UKCP09 Time series of winter coldwave duration. Sum of days with daily minimum temperature more than 3 °C below 1961–90 daily normal for ≥5 consecutive days (November-April). The datasets have been created with financial support from the Department for Environment, Food and Rural Affairs (Defra) and they are being promoted by the UK Climate Impacts Programme (UKCIP) as part of the UK Climate Projections (UKCP09). http://ukclimateprojections.defra.gov.uk/content/view/12/689/. To view this data you will have to register on the Met Office website, here: http://www.metoffice.gov.uk/research/climate/climate-monitoring/UKCP09/register

This dataset is associated with the following publication, where further details are provided and which should be cited for further applications:

Huang et al. 2022, Non-linear response of temperature-related mortality risk to global warming in England and Wales, Environ. Res. Lett., https://doi.org/10.1088/1748-9326/ac50d5.

The data contain daily temperature-related mortality estimates for ten NUTS 1 regions of England and Wales over the period 1900 to 2099, based on temperatures from the 2018 UK Climate Projections (UKCP18) simulations. Exposure-response relationships are based on present-day observations and extrapolated where necessary.

Variables in the csv files are as follows:

"tmean": daily mean temperature (in degrees C)
"bAD": backward attributable deaths
"fAD": forward attributable deaths

RCP 8.5 and RCP 2.6 scenarios are considered, as indicated in the file names. Model numbers refer to UKCP18 climate models.

Some say climate change is the biggest threat of our age while others say it’s a myth based on dodgy science. We are turning some of the data over to you so you can form your own view.

Even more than with other data sets that Kaggle has featured, there’s a huge amount of data cleaning and preparation that goes into putting together a long-time study of climate trends. Early data was collected by technicians using mercury thermometers, where any variation in the visit time impacted measurements. In the 1940s, the construction of airports caused many weather stations to be moved. In the 1980s, there was a move to electronic thermometers that are said to have a cooling bias.

Given this complexity, there are a range of organizations that collate climate trends data. The three most cited land and ocean temperature data sets are NOAA’s MLOST, NASA’s GISTEMP and the UK’s HadCrut.

We have repackaged the data from a newer compilation put together by the Berkeley Earth, which is affiliated with Lawrence Berkeley National Laboratory. The Berkeley Earth Surface Temperature Study combines 1.6 billion temperature reports from 16 pre-existing archives. It is nicely packaged and allows for slicing into interesting subsets (for example by country). They publish the source data and the code for the transformations they applied. They also use methods that allow weather observations from shorter time series to be included, meaning fewer observations need to be thrown away.

In this dataset, we have include several files:

Global Land and Ocean-and-Land Temperatures (GlobalTemperatures.csv):

• Date: starts in 1750 for average land temperature and 1850 for max and min land temperatures and global ocean and land temperatures
• LandAverageTemperature: global average land temperature in celsius
• LandAverageTemperatureUncertainty: the 95% confidence interval around the average
• LandMaxTemperature: global average maximum land temperature in celsius
• LandMaxTemperatureUncertainty: the 95% confidence interval around the maximum land temperature
• LandMinTemperature: global average minimum land temperature in celsius
• LandMinTemperatureUncertainty: the 95% confidence interval around the minimum land temperature
• LandAndOceanAverageTemperature: global average land and ocean temperature in celsius
• LandAndOceanAverageTemperatureUncertainty: the 95% confidence interval around the global average land and ocean temperature

Other files include:

• Global Average Land Temperature by Country (GlobalLandTemperaturesByCountry.csv)
• Global Average Land Temperature by State (GlobalLandTemperaturesByState.csv)
• Global Land Temperatures By Major City (GlobalLandTemperaturesByMajorCity.csv)
• Global Land Temperatures By City (GlobalLandTemperaturesByCity.csv)

The raw data comes from the Berkeley Earth data page.

This file contains average rainfall (mm) and average temperature (centigrade) for the North East England and East England for period 2010-2019.

This dataset shows the average rainfall in millimeters and average temperature in centigrade by month, year, and meteorological season. It also has an annual figure for each year.

Site specific (293 individual stations) monthly average (1981 - 2010)

        The data consists of:
        Max Temp (degrees C) 
        Min Temp (degrees C) 
        Sunshine (hours) 
        Rainfall (mm) 
        Raindays >=1.0mm (days) 
        Days of Air Frost (days) 
        Monthly mean wind speeds at 10m (knots)

        District and Region monthly average (1961-1990, 1971-2000, 1981-2010)

        The data consists of:
        Max Temp (degrees C) 
        Min Temp (degrees C) 
        Sunshine (hours) 
        Rainfall (mm) 
        Raindays >=1.0mm (days) 
        Days of Air Frost (days)

        UK monthly average (1961-1990, 1971-2000, 1981-2010)

        The data consists of:
        Max Temp (degrees C) 
        Min Temp (degrees C) 
        Sunshine (hours) 
        Rainfall (mm) 
        Raindays >=1.0mm (days) 
        Days of Air Frost (days)