Context

The dataset featured below was created by reconciling measurements from requests of individual weather attributes provided by the European Climate Assessment (ECA). The measurements of this particular dataset were recorded by a weather station near Heathrow airport in London, UK.

-> This weather dataset is a great addition to this London Energy Dataset. You can join both datasets on the 'date' attribute, after some preprocessing, and perform some interesting data analytics regarding how energy consumption was impacted by the weather in London.

Content

The size for the file featured within this Kaggle dataset is shown below — along with a list of attributes and their description summaries: - london_weather.csv - 15341 observations x 10 attributes

1. date - recorded date of measurement - (int)
2. cloud_cover - cloud cover measurement in oktas - (float)
3. sunshine - sunshine measurement in hours (hrs) - (float)
4. global_radiation - irradiance measurement in Watt per square meter (W/m2) - (float)
5. max_temp - maximum temperature recorded in degrees Celsius (°C) - (float)
6. mean_temp - mean temperature in degrees Celsius (°C) - (float)
7. min_temp - minimum temperature recorded in degrees Celsius (°C) - (float)
8. precipitation - precipitation measurement in millimeters (mm) - (float)
9. pressure - pressure measurement in Pascals (Pa) - (float)
10. snow_depth - snow depth measurement in centimeters (cm) - (float)

Source

Weather Data - https://www.ecad.eu/dailydata/index.php

In 2022, several locations across the United Kingdom exceeded temperatures of more than ** degrees Celsius for the time time on record. The village of Coningsby in eastern England reached **** degrees Celsius on July 19, 2022. That same day, temperatures at Heathrow and St James's Park in London, as well as Pitsford, Northamptonshire, also recorded a maximum temperature of over ** degrees Celsius. 2022 was the UK's hottest year on record.

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.

The United Kingdom's hottest summer ever recorded was in 2018, with an average temperature of ***** degrees Celsius. Meanwhile, 2023 saw the eighth hottest summer in the UK, with an average temperature of ***** degrees. In the last couple of decades, five of the top 10 warmest summers in the UK were recorded. New temperature records in 2022 In summer 2022, record-breaking temperatures of more than ** degrees Celsius were recorded at several locations across the UK. Accordingly, 2022 was also the UK's warmest year on record, with the average annual temperature rising above ** degrees Celsius for the first time. Since temperature recording began in ****, the hottest years documented in the country have all occurred after 2003. England: the warmest country in the UK Amongst the countries that comprise the United Kingdom, England has generally seen the highest annual mean temperatures. In 2022, England’s average temperature also reached a new record high, at nearly ** degrees Celsius. And while it’s not a typical sight in the United Kingdom, England also registered the most hours of sunshine on average, with Scotland being the gloomiest country out of the four.

During the heat wave in 2022, the highest temperature recorded in the United Kingdom was **** degrees Celsius on ******* at Coningsby, Lincolnshire. An unprecedented extreme heatwave was experienced in the United Kingdom from ** to ** *********, and extreme temperatures at over 40°C were recorded for the first time since recording of temperatures began.

This record is created as a data supplement for the manuscript "Estimated mortality attributable to the urban heat island during the record-breaking 2022 heatwave in London".

These data were produced using the Weather Research Forecasting model with BEP-BEM. The model setup is described in Brousse et al (2023) 10.1175/JAMC-D-22-0142.1. These data cover the period 2022-07-10 to 2022-07-25, during which temperatures exceding 40 °C were recorded in London for the first time.

The data comprise two NetCDF files. One is labelled "Urb" one "Nourb". In the "Nourb" file, the urban tile is removed from the model and the land surface replaced by the nearest natural tile. This can be used to estimate the influence of the urban tile on the local climate.

Variables included in the file are T2 (temperature at 2 m elevation in Kelvin), V10 and U10 (winds at 10 m elevation in metres per second), PSFC (surface level pressure in Pascal), RAINNC (rain in mm), TH2 (potential temperature at 2m elevation in Kelvin), and Q2 (specific humidity at 2 m elevation, which is dimensionless). All variables are provided at hourly timestep.

Queries about this dataset can be directed to o.brousse@ucl.ac.uk

This dataset contains estimates of mortality and number of hospital admissions that can be attributed to temperature, from observations and climate projections, and includes some of the underlying climate data. The data are divided into the subdirectories ‘epi_model’, ‘HadUKgrid’, ‘London’, ‘regimes’, and ‘UKCP18’ as follows:

epi_model: - Model fits of exposure-response relationships

HadUKgrid: - Temperature-attributable mortality/hospital admission time series for the observed record (1981/1991-2018) - List of the 10 highest mortality days from 1991 to 2018 based on UK-total temperature-related mortality

London: - Average daily temperature by London boroughs simulated with an urban model, October 2015 to 2019 - Attributable hospital admission by London boroughs based on the above temperature time series

regimes: - Weather regime and pattern classification for the observed record (1850/1979-2019)

UKCP18: - Attributable mortality time series for UKCP18 climate projections (1900-2099)

Further details including file contents and methods can be found in the README.txt files for each dataset. This dataset was produced for the UK Climate Resilience Programme - Addressing the resilience needs of the UK health sector: climate service pilots.

England's hottest summers ever recorded were in 2022 and 2018, both with an average temperature of **** degrees Celsius. During summer 2022, record-breaking temperatures exceeding ** degrees Celsius were reached at several locations in England, such as Heathrow and St James's Park in London.

The longest available instrumental record of temperature in the world is now available at the BADC. The daily data starts in 1772.

The mean, minimum and maximum datasets are updated monthly, with data for a month usually available by the 3rd of the next month. A provisional CET value for the current month is calculated on a daily basis. The mean daily data series begins in 1772. Mean maximum and minimum daily and monthly data are also available, beginning in 1878. Yearly files are provided from 1998 onwards.

These historical temperature series are representative of the Midlands region in England, UK (a roughly triangular area of the United Kingdom enclosed by Bristol, Lancashire and London).

The following stations are used by the Met Office to compile the CET data: Rothamsted, Malvern, Squires Gate and Ringway.

But in November 2004, the weather station Stonyhurst replaced Ringway and revised urban warming and bias adjustments have now been applied to the Stonyhurst data after a period of reduced reliability from the station in the summer months.

The data set is compiled by the Met Office Hadley Centre.

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 United Kingdom recorded its hottest-ever year in 2022, with an average temperature of ***** degrees Celsius. Since the start of temperature recording in ****, the ** warmest years recorded in the UK have been from 2003 onwards. Weather conditions are predicted to become more extreme due to climate change.

Supporting data for "Modelled temperature, mortality impact, and external benefits of cool roofs and rooftop photovoltaics in London"

Included are outputs from the Weather Research and Forecast (WRF) model. All simulations cover London, United Kingdom over summer 2018. Scenarios include a "baseline" which represents the real urban climate of the region, and scenarios which model 100% coverage of rooftops with either high albedo materials or solar panels. Data are provided in netCDF format.

• The baseline simulation which models the current urban climate of the region WRF_Urb_BouLac_T2-V10-U10_20180525-20180831.nc
• The 100% rooftop-solar simulation WRF_Urb_BouLac_PV_T2-V10-U10-PSFC-RAINNC-TH2-Q2_20180525-20180831.nc
• The 100% high-albedo roof simulation WRF_Urb_BouLac_ClRf_T2-V10-U10-PSFC-RAINNC-TH2-Q2_20180525-20180831.nc
• The non-urban scenario is in WRF_NoUrb_BouLac_T2-V10-U10-PSFC-RAINNC-TH2-Q2_20180525-20180831.nc
• The power production estimates solarpv_prod_2018.nc
• wrf_popweighting-main.zip contains the analysis code. It is provided as-is with no guarantee of usability.

T2 means air temperature at 2m height. V10 and U10 are windspeeds at 10m height. PSFC is surface level pressure. TH2 is potential temperature. Q2 is specific humidity at 2m height.

More description of the simulations is given in the citing article.

The dataset comprises three file categories: Multiyear (MY), Typical meteorological year (TMY) and Heatwave year (HWY). The MY files in .CSV format contain the hourly values of the bias-corrected climate projections for three 20-year reference periods: 2001-2020, 2041-2060 and 2081-2100. The TMYs files represent typical city meteorological conditions corresponding to historical (2001-2020), medium-term future (2041-2060) and long-term future (2081-2100) periods. The TMYs are provided in EPW format, a weather file format commonly used in building energy simulation tools such as EnergyPlus and similar. The HWYs, also provided in EPW format, are weather files with extreme heatwaves, i.e. the years with the most intense, most severe and longest heatwaves experienced in the three reference periods.

2013 - London LUMA TLI Thames River Water temperature

1. Site: TLI
2. Country\City\Location: UK\London\ river Thames Lifeboat south of KCL Strand CampusTLI
3. Height: in river - moving up and down with the tide so staying approximately the same depth under the water

1. Sensor: Tinytag Water temperature logger
2. raw data 1 min

1. Files: rawTwater_120910_1202924.csv
2. _YYMMDD to _YYMMDD
3. Format: CSV ascii comma delimited
4. Files randomly downloaded by hand
5. Raw Tiny Tag format also present
6. Header in file
7. ,Time,1
8. S/N,,571884
9. Type,,TG-4100
10. Description,,Aquatic
11. Property,,Maximum Temperature
12. 1,2012-09-10 10:54:41,18.991 °C

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 UK hourly weather observation data contain meteorological values measured on an hourly time scale. The measurements of the concrete state, wind speed and direction, cloud type and amount, visibility, and temperature were recorded by observation stations operated by the Met Office across the UK and transmitted within SYNOP, DLY3208, AWSHRLY and NCM messages. The sunshine duration measurements were transmitted in the HSUN3445 message. The data spans from 1875 to 2019.

This version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. Of particular note, however, is that as well as including data for 2019, historical data recovery has added temperature and weather data for Bude (1937-1958), Teignmouth (1912-1930), and Eskdalemuir (1915-1948).

For details on observing practice see the message type information in the MIDAS User Guide linked from this record and relevant sections for parameter types.

This dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. Note, METAR message types are not included in the Open version of this dataset. Those data may be accessed via the full MIDAS hourly weather data.

[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 percentage change between the 'lower' values before and after this update is -1%.]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.

The records were taken two times a Day at 9:30 and 15:30. In 1852 the Royal Engineers (British Army) under the supervision of Colonel Sir Henry James started a network of meteorological observations in the principal foreign stations. Sir James born in 1803 in Rose Vale (Cornwall, UK) study at the Royal Military Academy (Woolwich) and he commissioned the 22 September 1826 in the Royal Engineers. He was promoted to Capitan in 1846 and to Colonel in 1857. From 1854 he was Director-General of the Ordnance Survey (the national mapping agency of Great Britain). He collaborates in the invention of the photozincography (1860) and used this method to preserve historic manuscripts. He retired in 1875 and died on 14 June 1877 in Southampton. The stations were supplied with meteorological instruments and a book entitled ""Instructions for taking Meteorological Observations"" (James, 1851) revised in 1861 (James, 1861). So, the Royal Engineers start to take homogenous meteorological measurements (same instruments, same observational methodology) all around the world. The observations were taken twice a Day (at 9.30h and 15.30h), for the barometer, the dry and wet bulb thermometer, wind (direction and force), amount of cloud, together with the computed values of the dew point, vapour tension, and relative humidity. Also give daily record of maximum temperature in the sun, maximum temperature in the shade, maximum temperature of evaporation, minimum temperature in the shade, minimum temperature on the grass, minimum temperature of evaporation, rainfall in past 24 hours on the ground, rainfall in past 24 hours at 20 feet above the ground, maximum pressure of wind in past 24 hours, amount of ozone, and Remarks (state of the sky, prevalent diseases, arrival of birds of passage, leafing of trees). In addition hourly readings of the instruments were taken on 21st March, 21st June, 21st September, and 21st December and at certain stations readings were taken all the 21st. Unfortunately not all the variables were taken in all stations, for this we explain in each location the retrieved observations. James H 1851. Instructions for taking Meteorological Observations at the Principal Foreign Stations of the Royal Engineers. London: HMSO./ James H 1861. Instructions for taking Meteorological Observations with tables for their correction, and notes on meteorological phenomena. London: George E Eyre and William Spottiswoode. […]

AWS processed:

Processed and quality-control checked data from a Davis Vantage Pro Plus located in the city of London (Saunders et al. 2024).

CNR4 processed:

Processed and quality-control checked data from a Kipp & Zonen CNR4 radiometer in the city of London (Saunders et al. 2024).

LAS raw:

Raw data from a single beam Kipp and Zonen MKII LAS (850 nm wavelength) sensor defined as the scintillometer path ‘BCT-IMU’ (Saunders et al. 2024) located between the City of London and Islington.

LAS source areas:

Source areas for the scintillometer path ‘BCT-IMU’. Data are derived using the methodology as described by Saunders et al. 2024 (see Fig. 2), and were written using the ‘scintools’ python code (10.5281/zenodo.7434074). Digital surface models used for these cases are also included as part of the ‘scintools’ zenodo repository.

Source areas for the specific case study day are processed using the python code ‘scint_fp’ (included in 10.5281/zenodo.7434153) using automatic weather station data included here (in the directory AWS processed). csv files included in each subdirectory of ‘LAS_Source_Areas’ are the inputs given to ‘scint_fp’.

Source areas are calculated every hour using inputs averaged over the last 10 minutes of that our (time-ending). For example, a 1200 source area is calculated using meteorological conditions averaged over 1150-1200. The end of each file name indicates the time period (time ending) of which the source area applies.

LAS processed:

Processed data from the scintillometer path ‘BCT-IMU’. Data were derived using the methodology as described by Saunders et al. 2024 (see Fig. 3), and written using the ‘scint_flux’ python code (10.5281/zenodo.7434143) and using scintillometer source areas derived from the ‘scintools’ python code (10.5281/zenodo.7434074).

Files ending with PERIOD_VAR_## refer to the averaging period performed on the LAS raw data as number in minutes (where ## is 1, 10, and 60 minutes). Files with a name including ‘sa10min_ending’ use source areas calculated every hour with input meteorological conditions averaged over 10 minutes.

Objective: To clarify whether deaths associated with hot and cold days are among the frail who would have died anyway in the next few weeks or months. Design: Time series regression analysis of annual deaths in relation to annual summaries of cold and heat. Setting: London, UK. Participants: 3 530 280 deaths from all natural causes among London residents between October 1949 and September 2006. Main outcome measures: Change in annual risk of death (all natural cause, cardiovascular and respiratory) associated with each additional 1°C of average cold (or heat) below (above) the threshold (18°C) across each year. Results: Cold years were associated with increased deaths from all causes. For each additional 1° of cold across the year, all-cause mortality increased by 2.3% (95% CI 0.7% to 3.8%), after adjustment for influenza and secular trends. The estimated association between hot years and all-cause mortality was very imprecise and thus inconclusive (effect estimate 1.7%, −2.9% to 6.5%)....