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 8.3 degrees Celsius. In the next period, from 1991 to 2020, the UK's average temperature increased by 0.8 degrees Celsius and increased further by 0.5 degrees Celsius between 2014 and 2023. In the latter year, figures remained at 10 degrees Celsius, 1.7 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.

The annual mean temperature in the United Kingdom has fluctuated greatly since 1990. Temperatures during this period were at their highest in 2022, surpassing 10 degrees Celsius. In 2010, the mean annual temperature stood at 7.94 degrees, the lowest recorded during this time. Daily temperatures Average daily temperatures have remained stable since the turn of the century, rarely dropping below 10 degrees Celsius. In 2010, they dropped to a low of nine degrees Celsius. The peak average daily temperature was recorded in 2022 when it reached 11.2 degrees. This was an increase of one 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 22.6 degrees Celsius. In comparison, the lowest monthly minimum temperature was in February of the same year, at just minus 0.6 degrees. This was an especially cold February, as the previous year the minimum temperature for this month was 2.6 degrees.

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 February 2025, the mean air temperature was five degrees Celsius, 50 percent lower 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.

Monthly temperature deviations from the long-term mean in the United Kingdom have varied greatly in recent years. In January 2025, average temperatures were 1.2 degrees Celsius cooler than the long-term mean. In comparison, temperatures in January 2024 were 0.1 degrees Celsius warmer than the long-term mean. The most notable deviation during this period was in December 2015, when temperatures were 4.3 degrees warmer than normal.

[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 0.21°C.]What does the data show? This dataset shows the change in winter average 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. 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 winter 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 winter 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 Winter 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 Winter 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 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. 'tas 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. 'tas change winter 2.0 median' is named 'tas_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 ‘tas 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 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.

For an urban heat island map during an average summer see this dataset. A heatwave refers to a prolonged period of unusually hot weather. While there is no standard definition of a heatwave in England, the Met Office uses the World Meteorological Organization definition of a heatwave, which is "when the daily maximum temperature of more than five consecutive days exceeds the average maximum temperature by 5°C, the normal period being 1961-1990". They are common in the northern and southern hemisphere during summer have historically been associated with health problems and an increase in mortality. The urban heat island (UHI) is the phenomenon where temperatures are relatively higher in cities compared to surrounding rural areas due to, for example, the urban surfaces and anthropogenic heat sources. This urban heat island map was produced using LondUM, a specific set-up of the Met Office Unified Model version 6.1 for London. It uses the Met Office Reading Surface Exchange Scheme (MORUSES), as well as urban morphology data derived from Virtual London. The model was run from May until September 2006 and December 2006. This map shows average surface temperatures over the summer period of 2006 at a 1km by 1km resolution. To find out more about LondUM, see the University of Reading’s website. The hourly outputs from LondUM have been aggregated and mapped by Jonathon Taylor, UCL Institute for Environmental Design and Engineering. Variables include: WSAVGMAX= the average of the maximum daily temperatures across the summer period (May 26th-August 31st) WSAVG=the average temperature across the summer period WSAVGMIN = the average minimum daily temperature across the summer period HWAVGMAX= the average of the maximum daily temperatures across the 2006 heatwave (July 16th-19th) HWAVG=the average temperature across the across the 2006 heatwave HWAVGMIN = the average minimum daily temperature across 2006 heatwave period The maps are also available as one combined PDF. The gif below maps the temperatures across London during the four-day period of 16-19th July, which was considered a heatwave. If you make use of the LondUM data, please use the following citation to acknowledge the data and reference the publication below for model description: LondUM (2011). Model data generated by Sylvia I. Bohnenstengel (), Department of Meteorology, University of Reading and data retrieved from http://www.met.reading.ac.uk/~sws07sib/home/LondUM.html. () Now at Metoffice@Reading, Email: sylvia.bohnenstengel@metoffice.gov.uk Bohnenstengel SI, Evans S, Clark P and Belcher SeE (2011) Simulations of the London Urban Heat island. Quarterly journal of the Royal Meteorological Society, 137(659). pp. 1625-1640. ISSN 1477-870X doi 10.1002/qj.855. LondUM data (2013).

The wettest months in the United Kingdom tend to be at the start and end of the year. In the period of consideration, the greatest measurement of rainfall was nearly 217 millimeters, recorded in December 2015. The lowest level of rainfall was recorded in April 2021, at 20.6 millimeters. Rainy days The British Isles are known for their wet weather, and in 2024 there were approximately 164 rain days in the United Kingdom. A rainday is when more than one millimeter of rain falls within a day. Over the past 30 years, the greatest number of rain days was recorded in the year 2000. In that year, the average annual rainfall in the UK amounted to 1,242.1 millimeters. Climate change According to the Met Office, climate change in the United Kingdom has resulted in the weather getting warmer and wetter. In 2022, the annual average temperature in the country reached a new record high, surpassing 10 degrees Celsius for the first time. This represented an increase of nearly two degrees Celsius when compared to the annual average temperature recorded in 1910. In a recent survey conducted amongst UK residents, almost 80 percent of respondents had concerns about climate change.

UKCP09: 5 km gridded data - Annual averages for the summer heatwave duration. The data set contains 12 files (one for each month for the 1961-1990 average period). The individual grids are named according to the following convention: variablename_mmm_Average_Actual.txt where mmm is the month name (e.g. Jan).

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

The gridded Climatic Research Unit (CRU) Time-series (TS) data version 4.03 data are month-by-month variations in climate over the period 1901-2018, provided on high-resolution (0.5x0.5 degree) grids, produced by CRU at the University of East Anglia.

The CRU TS4.03 variables are cloud cover, diurnal temperature range, frost day frequency, potential evapotranspiration (PET), precipitation, daily mean temperature, monthly average daily maximum and minimum temperature, and vapour pressure for the period January 1901 - December 2018.

The CRU TS4.03 data were produced using angular-distance weighting (ADW) interpolation. All version 4 releases used triangulation routines in IDL. Please see the release notes for full details of this version update.

The CRU TS4.03 data are monthly gridded fields based on monthly observational data calculated from daily or sub-daily data by National Meteorological Services and other external agents. The ASCII and NetCDF data files both contain monthly mean values for the various parameters. The NetCDF versions contain an additional integer variable, ’stn’, which provides, for each datum in the main variable, a count (between 0 and 8) of the number of stations used in that interpolation. The missing value code for 'stn' is -999.

All CRU TS output files are actual values - NOT anomalies.

Projected regional average change in seasonal and annual temperature and precipitation extremes for the IPCC SREX regions for CMIP5. The data were produced in 2013 by the Intergovernmental Panel on Climate Change (IPCC) Working Group II (WGII) Chapter 14 supplementary material (SM) author team for the IPCC Fifth Assessment Report (AR5).

Regional average seasonal and annual temperature and precipitation extremes for the periods 2016-2035, 2046-2065 and 2081-2100 for CMIP5 General Circulation Model (GCM) projections are compared to a baseline of 1986-2005 from each model's historical simulation. The temperature and precipitation data are based on the difference between the projected periods and the historical baseline for which the 25th, 50th and 75th percentiles, and the lowest and highest responses among the 32 models which are expressed for temperature as degrees Celsius change and for precipitation as a per cent change. The temperature responses are averaged over the boreal winter and summer seasons; December, January, February (DJF) and June, July and August (JJA) respectively. The precipitation responses are averaged over half year periods, boreal winter (BW); October, November, December, January, February and March (ONDJFM) and boreal summer (BS); April, May, June, July, August and September (AMJJAS).

Regional averages are based on the SREX regions defined by the IPCC Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation (IPCC, 2012: also known as "SREX"). Added to the SREX regions are additional regions containing the two polar regions, the Caribbean, Indian Ocean and Pacific Island States. The data are further categorised by the land and sea mask for each SREX region.

As a result of high oil prices in the mid-1970s, many European and Scandinavian countries initiated research programmes investigating fuel production from energy crops. Initial studies were aimed at identifying suitable crop systems. One of the systems tested involved planting coppicing tree species at high densities (around 10,000 stools per hectare) and harvesting above ground growth every two to five years. This system was termed ‘Short Rotation Coppice’ (SRC). In the UK, numerous coppicing tree species were tested using this system (Potter, 1990). Examples include Salix viminalis clones, Populus interamericana clones, Eucalyptus archeri, Alnus cordata, and Northofagus procera. Willow and poplar clones emerged favourably from these trials, producing high yields without succumbing to disease or frost. Other research programmes concentrated on developing harvesting, processing and power generation equipment that could cope with biomass produced by a variety of crop systems including SRC. Political backing for SRC was shown on 20 December 1994 when the UK minister for Energy announced government support for three power generation projects using woodfuel gasification technology. These projects were expected to ‘stimulate substantial commitment to coppicing’. Although informative, results from early research programmes could not predict the yield of willow or poplar SRC under different environmental conditions. Without this information planners could not make informed decisions as to where SRC plantations and power generation plants should be sited in order to maximise yield and land use efficiency. Growers also needed information on likely yields achievable by different site/clone combinations, in order to estimate their financial return from these crops. For these reasons the Department of Trade and Industry (DTI), the Ministry of Agriculture, Fisheries and Food (now incorporated into the Department of the Environment, Farming and Rural Affairs [Defra]) and the Forestry Commission (FC) sought to quantify and model the yield potential of a diverse range of willow and poplar clones when grown as SRC on agricultural sites across the UK. The subsequent research programme ‘Yield models for energy coppice of poplar and willow’ was coordinated by ETSU and carried out by Forest Research (FR) and the Department of Agriculture and Rural Development, Northern Ireland (DARDNI, formally Department of Agriculture, Northern Ireland). The backbone of this research programme was a network of 49 field trials established on agricultural land throughout England, Scotland, Wales and Northern Ireland. Data collected from these sites continues to be used in the development of empirical yield models and process based predictive yield models capable of estimating the productivity of varieties grown under a range of environmental conditions. This data set contains the meteorological data collected at these sites during the project. The variables recorded were: Mean air temperature (oC); Wet bulb temperature (oC); Maximum air temperature (oC); Minimum air temperature (oC); Mean soil temperature (oC); Maximum soil temperature (oC); Minimum soil temperature (oC); Rainfall (mm); Mean relative humidity (%); Surface wetness; Net solar radiation (W.m-2); Global solar radiation (W.m-2); Wind direction (o); Wind speed (ms-1) See also Evans S (coordinator), Baldwin M, Casella E, Henshall P, Morgan G, Poole J, Sayce M, Stokes V, Taylor P, Tubby I (2007) Final Report: Yield Models for Energy: Coppice of Poplar and Willow. Report to DTI (B/W2/00624/00/00). Ed: T. Randle and I. Tubby. Attribution statement: Quote Forest Research as the source of the data if used in any subsequent products (including papers and reports)

The gridded Climatic Research Unit (CRU) Time-series (TS) data version 4.01 data are month-by-month variations in climate over the period 1901-2016, provided on high-resolution (0.5x0.5 degree) grids, produced by CRU at the University of East Anglia. The CRU TS4.01 variables are cloud cover, diurnal temperature range, frost day frequency, potential evapotranspiration (PET), precipitation, daily mean temperature, monthly average daily maximum and minimum temperature, and vapour pressure for the period January 1901 - December 2016. The CRU TS4.01 data were produced using angular-distance weighting (ADW) interpolation. All version 3 releases used triangulation routines in IDL. Please see the release notes for full details of this version update. CRU TS4.01 is a full release, differing only in methodology from the parallel release, v3.25. Both are released concurrently to support comparative evaluations between these two versions, however, this will be the last release of version 3. The CRU TS4.01 data are monthly gridded fields based on monthly observational data calculated from daily or sub-daily data by National Meteorological Services and other external agents. The ASCII and NetCDF data files both contain monthly mean values for the various parameters. The NetCDF versions contain an additional integer variable, ’stn’, which provides, for each datum in the main variable, a count (between 0 and 8) of the number of stations used in that interpolation. The missing value code for 'stn' is -999. All CRU TS output files are actual values - NOT anomalies.

A novel temperature dataset for northern high latitude Seas (ATLAS) is a dataset of three-dimensional temperature derived from combining quality controlled Argo float measurements with marine mammal mounted Satellite Relay Data Loggers (SRDLs) profiles. Using data values gathered from across the North Atlantic region, a 1×1 degree gridded temperature dataset of the average monthly values from January 2004 to December 2008, with 15 vertical layers between 0–700 m was produced. Built as complementary to existing ship‐based fields, the ATLAS dataset is a community resource to help determine the impacts of climate change on the Labrador and Nordic Seas regions. The data were collated by the National Oceanography Centre (NOC) and are made available from the British Oceanographic Data Centre (BODC).

Between 2001 and 2023, the average rainfall in the United Kingdom varied greatly. In 2010, rainfall dropped to a low of 1,020 millimeters, which was a noticeable decrease when compared to the previous year. However, the following year rainfall increased significantly to a peak of 1,889 millimeters. During the period in consideration, rainfall rarely rose above 1,500 millimeters. In 2023, the annual average rainfall in the UK surpassed 1,381 millimeters.

Monthly rainfall

On average, rainfall is most common at the start and end of the year. Between 2014 and 2023, monthly rainfall peaked in December 2015 at approximately 217 millimeters. This was the first of only two times during this period that the average monthly rainfall rose above 200 millimeters. This was a deviation from December’s long-term mean of some 134 millimeters.

Rainfall highest in Scotland

In the United Kingdom, rain is often concentrated around mountainous regions such as the Scottish Highlands, so it is no surprise to see that – on average – it is Scotland that receives the most rainfall annually. In 2023, the average rainfall in Scotland amounted to approximately 1,574 millimeters. Geographically, it is the north and west of the United Kingdom that receives the lion's share of rain, as it is more susceptible to rainfall coming in from the Atlantic.

The United Kingdom's average minimum temperature in July 2021 measured 12.1 degrees Celsius. This month, recorded the highest minimum temperature during the reported period. Since 2015, the lowest monthly minimum temperature in the UK was recorded in February 2018, at -0.7 degrees Celsius. This was the first time during this period that the average monthly minimum temperature dropped below zero degrees Celsius, while in January 2021 the second time took place, at -0.5 degrees Celsius. Further information about the weather in the United Kingdom can be found here.

Based on current monthly figures, on average, German climate has gotten a bit warmer. The average temperature for January 2025 was recorded at around 2 degrees Celsius, compared to 1.5 degrees a year before. In the broader context of climate change, average monthly temperatures are indicative of where the national climate is headed and whether attempts to control global warming are successful. Summer and winter Average summer temperature in Germany fluctuated in recent years, generally between 18 to 19 degrees Celsius. The season remains generally warm, and while there may not be as many hot and sunny days as in other parts of Europe, heat waves have occurred. In fact, 2023 saw 11.5 days with a temperature of at least 30 degrees, though this was a decrease compared to the year before. Meanwhile, average winter temperatures also fluctuated, but were higher in recent years, rising over four degrees on average in 2024. Figures remained in the above zero range since 2011. Numbers therefore suggest that German winters are becoming warmer, even if individual regions experiencing colder sub-zero snaps or even more snowfall may disagree. Rain, rain, go away Average monthly precipitation varied depending on the season, though sometimes figures from different times of the year were comparable. In 2024, the average monthly precipitation was highest in May and September, although rainfalls might increase in October and November with the beginning of the cold season. In the past, torrential rains have led to catastrophic flooding in Germany, with one of the most devastating being the flood of July 2021. Germany is not immune to the weather changing between two extremes, e.g. very warm spring months mostly without rain, when rain might be wished for, and then increased precipitation in other months where dry weather might be better, for example during planting and harvest seasons. Climate change remains on the agenda in all its far-reaching ways.

The gridded Climatic Research Unit (CRU) Time-series (TS) data version 4.04 data are month-by-month variations in climate over the period 1901-2019, provided on high-resolution (0.5x0.5 degree) grids, produced by CRU at the University of East Anglia and funded by the UK National Centre for Atmospheric Science (NCAS), a NERC collaborative centre.

The CRU TS4.04 variables are cloud cover, diurnal temperature range, frost day frequency, wet day frequency, potential evapotranspiration (PET), precipitation, daily mean temperature, monthly average daily maximum and minimum temperature, and vapour pressure for the period January 1901 - December 2019.

The CRU TS4.04 data were produced using angular-distance weighting (ADW) interpolation. All versions prior to 4.00 used triangulation routines in IDL. Please see the release notes for full details of this version update.

The CRU TS4.04 data are monthly gridded fields based on monthly observational data calculated from daily or sub-daily data by National Meteorological Services and other external agents. The ASCII and NetCDF data files both contain monthly mean values for the various parameters. The NetCDF versions contain an additional integer variable, ’stn’, which provides, for each datum in the main variable, a count (between 0 and 8) of the number of stations used in that interpolation. The missing value code for 'stn' is -999.

All CRU TS output files are actual values - NOT anomalies.