Extreme Heat

Extreme heat

Overview

• What is extreme heat?

Changes in extreme heat with global warming

• The frequency and intensity of hot extremes (including heatwaves) have increased since 1950 both globally and at regional scale, with more than 80% of AR6 regions showing similar changes.
• This trend is expected to persist as global warming continues. The IPCC AR6 report summarizes the projected changes in extreme heat with ongoing global warming, stating: "The frequency and intensity of hot extremes will continue to increase at global and continental scales and in nearly all inhabited regions with increasing global warming levels. This will be the case even if global warming is stabilized at 1.5°C. Relative to present-day conditions, changes in the intensity of extremes would be at least double at 2°C, and quadruple at 3°C of global warming, compared to changes at 1.5°C of global warming. The number of hot days and hot nights and the length, frequency, and/or intensity of warm spells or heatwaves will increase over most land areas. In most regions, future changes in the intensity of temperature extremes will very likely be proportional to changes in global warming, and up to two to three times larger. The highest increase of temperature of hottest days is projected in some mid-latitude and semi-arid regions and in the South American Monsoon region, at about 1.5 times to twice the rate of global warming (high confidence). The highest increase of temperature of coldest days is projected in Arctic regions, at about three times the rate of global warming (high confidence). The frequency of hot temperature extreme events will very likely increase nonlinearly with increasing global warming, with larger percentage increases for rarer events."

How it makes impacts: WG2 16.2.3.5 and WG1 12.3.1

Hot and humid heat episodes can be deadly, are associated with elevated hospital intake and lower safety and productivity of outdoor labourers. Elevated nighttime temperatures prevent the human body from experiencing relief from heat stress and can be tracked over extended periods of sequential day and night heat extremes (Murage et al., 2017; Mukherjee and Mishra, 2018). Extreme heat also exacerbates asthma, respiratory difficulties and response to airborne allergens such as hay fever (Upperman et al., 2017). Extreme heat affects outdoor exercise such as the use of bike-share facilities (Heaney et al., 2019; Vanos et al., 2020). Large-scale recreational and sporting events such as marathons and tennis tournaments monitor heat extremes when determining the viability of host cities (Smith et al., 2016, 2018).

• Indicators to measure it (based on impacts): WG1 Ch12.3.1

Heatwaves are a significant climate risk characterized by prolonged periods of excessively hot weather, which can be detrimental to human health and comfort. The ERA5-HEAT dataset provides essential insights into thermal comfort indices that quantify human thermal stress during such events. This dataset is instrumental for research and planning in climatology, urban development, and public health initiatives.

Metrics/indicators WG1 12.3.1

Since SREX (IPCC, 2012) and AR5 (IPCC, 2014), many regional-scale studies have examined trends in temperature extremes using different metrics that are based on daily temperatures, such as the Commission for Climatology/World Climate Research Program/Commission for Oceanography and Marine Meteorology joint Expert Team on Climate Change Detection and Indices (ETCCDI) indices (Dunn et al., 2020).

ERA5-HEAT: Human Thermal Comfort Analysis

Analysis

The ERA5-HEAT dataset comprises an extensive historical reconstruction of Mean Radiant Temperature (MRT) and the Universal Thermal Climate Index (UTCI), which are pivotal in assessing human thermal stress and discomfort in outdoor environments. Derived from the ERA5 reanalysis by the European Centre for Medium-Range Weather Forecasts (ECMWF), it merges model data with observations to offer a consistent global climate profile from January 1940 to the present.

Visualizations

Visual representations of the data illustrate the geographic distribution of thermal comfort levels across the globe and historical changes over time.

Global UTCI Map:

Error creating thumbnail: File missing

Universal Thermal Climate Index (UTCI) Global Map

Heatwaves in the USA:

Error creating thumbnail: File missing

Recent temperature increase in the USA summers.

Historical Heatwave Data:

Error creating thumbnail: File missing

Historical heatwaves.

Heatwave Characteristics:

Error creating thumbnail: File missing

Heatwave characteristics.

Sample Dataset

A sample of the ERA5-HEAT dataset is presented below, showcasing the format and type of data available.

The sample header of the dataset, displayed in a tabular format, includes the following columns:

time: The specific time point for the data (in this sample, all rows correspond to '2023-07-01'). lon: Longitude values, indicating the geographical longitude where the measurement was taken. lat: Latitude values, indicating the geographical latitude where the measurement was taken. utci: Values of the Universal Thermal Climate Index (UTCI) at the respective time and geographical coordinates. This tabular representation shows how the UTCI values are mapped against specific time points and geographic locations (latitude and longitude). The UTCI values are indicative of human thermal comfort at these locations and times.

Full dataset access: ERA5-HEAT Dataset

heat extreme indices

temperature or heat extreme data

Regional indices to measure heat

IPCC regional climate impact driver indices

Datasets:

The following six datasets were used, including four traditional datasets:

• Berkeley Earth: Rohde, R.A.; Hausfather, Z. The Berkeley Earth Land/Ocean Temperature Record. Earth System Science Data 2020, 12 (4), 3469–3479. https://doi.org/10.5194/essd-12-3469-2020.
• GISTEMP v4: GISTEMP Team, 2022: GISS Surface Temperature Analysis (GISTEMP), Version 4. NASA Goddard Institute for Space Studies, https://data.giss.nasa.gov/gistemp/.
• HadCRUT.5.0.2.0: Morice, C.P.; Kennedy, J.J.; Rayner, N.A. et al. An Updated Assessment of Near-surface Temperature Change from 1850: The HadCRUT5 Data Set. Journal of Geophysical Research: Atmospheres 2021, 126 (3), e2019JD032361. https://doi. org/10.1029/2019JD032361. HadCRUT.5.0.2.0 data were obtained from http://www. metoffice.gov.uk/hadobs/hadcrut5 on 17 January 2024 and are © British Crown Copyright, Met Office 2024, provided under an Open Government Licence, http://www. nationalarchives.gov.uk/doc/open-government-licence/version/3/.
• Lenssen, N.J.L.; Schmidt, G.A.; Hansen, J.E. et al. Improvements in the GISTEMP Uncertainty Model. Journal of Geophysical Research: Atmospheres 2019, 124 (12), 6307–6326. https://doi. org/10.1029/2018JD029522.
• NOAAGlobalTemp-Interim v5.1: Vose, R.S.; Huang, B.; Yin, X. et al. Implementing Full Spatial Coverage in NOAA’s Global Temperature Analysis. Geophysical Research Letters 2021, 48 (4), e2020GL090873. https://doi.org/10.1029/2020GL090873.
• And two reanalyses:
• ERA5: Hersbach, H.; Bell, B.; Berrisford, P. et al. ERA5 Monthly Averaged Data on Single Levels from 1940 to Present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS), 2023. https://cds.climate.copernicus.eu/cdsapp#!/dataset/10.24381/cds. f17050d7?tab=overview.
• JRA-55: Kobayashi, S.; Ota, Y.; Harada, Y. et al. The JRA-55 Reanalysis: General Specifications and Basic Characteristics. Journal of the Meteorological Society of Japan. Ser. II 2015, 93 (1), 5–48. https://doi.org/10.2151/jmsj.2015–001
• IPCC used an additional dataset. Combining the six datasets used in the present publication with Kadow et al., 2020 reduces the estimated global mean for 2023 by 0.01 °C and increases the uncertainty range by a similar amount:
  • Kadow, C.; Hall, D.M.; Ulbrich, U. Artificial Intelligence Reconstructs Missing Climate Information. Nature Geoscience 2020, 13, 408–413. https://doi.org/10.1038/s41561-020-0582-5.
• A new reanalysis produced by JRA-3Q is now also available. JRA-55 was used in the present publication for consistency with the provisional statement released in December 2023. For comparison, the values for 2023 are shown relative to the four baselines for JRA-3Q and JRA-55 in Table 2 (see below). Note that the replacement of JRA-55 with JRA-3Q in the mean of the six datasets has a negligible effect on the global mean temperature for 2023.

LAND TEMPERATURES AND SEA-SURFACE TEMPERATURES

The land temperature assessment is based on three data sets:

• Berkeley Earth: Rohde, R.A.; Hausfather, Z. The Berkeley Earth Land/Ocean Temperature Record. Earth System Science Data 2020, 12 (4), 3469–3479. https://doi.org/10.5194/essd-12-3469-202.
• CRUTEM.5.0.2.0: Osborn, T.J.; Jones, P.D.; Lister, D.H. et al. Land Surface Air Temperature Variations Across the Globe Updated to 2019: The CRUTEM5 Data Set. Journal of Geophysical Research 2021, 126 (2), e2019JD032352. https://doi.org/10.1029/2019JD032352. CRUTEM.5.0.2.0 data were obtained from http://www.metoffice.gov.uk/hadobs/ crutem5 on 17 January 2024 and are © British Crown Copyright, Met Office 2024, provided under an Open Government Licence, http://www.nationalarchives.gov.uk/doc/ open-government-licence/version/3/.
• GHCNv4: Menne, M.J.; Gleason, B.E.; Lawrimore, J. et al. Global Historical Climatology Network – Monthly Temperature [Global mean]. NOAA National Centers for Environmental Information, 2017. doi:10.7289/V5XW4GTH.
• The sea-surface temperature (SST) assessment is based on two datasets:
  • HadSST.4.0.1.0: Kennedy, J.J.; Rayner, N.A.; Atkinson, C.P. et al. An Ensemble Data Set of Sea Surface Temperature Change from 1850: The Met Office Hadley Centre HadSST.4.0.0.0 Data Set. Journal of Geophysical Research: Atmospheres 2019, 124 (14), 7719–7763. https://doi. org/10.1029/2018JD029867. HadSST.4.0.1.0 data were obtained from http://www.metoffice. gov.uk/hadobs/hadsst4 on 17 January 2024 and are © British Crown Copyright, Met Office 2024, provided under an Open Government Licence, http://www.nationalarchives.gov.uk/ doc/open-government-licence/version/3/.
  • ERSSTv5: Huang, B.; Thorne, P.W.; Banzon, V.F. et al. NOAA Extended Reconstructed Sea-Surface Temperature (ERSST), Version 5. [Global mean]. NOAA National Centers for Environmental Information, 2017. doi:10.7289/V5T72FNM

Extreme heat by NRDC https://www.nrdc.org/resources/climate-change-and-health-extreme-heat#/map https://www.nrdc.org/sites/default/files/extreme_heat_chart.pdf

Historical temperature data for all cooperative weather stations for all years were downloaded from the Global Historical Climatology Network (GHCN), formerly the National Climatic Data Center.2 Geographic detail for stations was also downloaded from GHCN, which defines cooperative stations as “U.S. stations operated by local observers which generally report max/min temperatures and precipitation. National Weather Service (NWS) data are also included in this dataset. The data receive extensive automated + manual quality control.”

Heatwaves by EPA: https://www.epa.gov/climate-indicators/climate-change-indicators-heat-waves https://www.epa.gov/climate-indicators/climate-change-indicators-high-and-low-temperatures

projection of heat extremes as well as impacts: https://www.c2es.org/content/heat-waves-and-climate-change/

heatwaves by WMO: https://wmo.int/content/climate-change-and-heatwaves

heatwaves by US global change research: https://www.globalchange.gov/indicators/heat-waves

https://www.heat.gov/

HadEX3: Gridded Temperature and Precipitation Climate Extremes Indices (CLIMDEX data) https://climatedataguide.ucar.edu/climate-data/hadex3-gridded-temperature-and-precipitation-climate-extremes-indices-climdex-data

• Berkeley Earth Surface Temperature Dataset:
  • Provides global land and ocean temperature data, focusing on long-term temperature trends and extremes.
  • Berkeley Earth Dataset
• PRISM Climate Data:
  • High-resolution spatial climate datasets for the United States, including temperature, precipitation, and drought indices.

General Climate Extremes:

1. World Meteorological Organization (WMO) Global Data:
   • Offers a variety of datasets on climate extremes, including temperature and precipitation records.
   • WMO Data
2. NASA GISS Surface Temperature Analysis (GISTEMP):
   • Provides global temperature anomaly data, including extremes, from 1880 to the present.
   • NASA GISS Data
3. Climate Data Store (CDS) by Copernicus:
   • Offers access to various climate datasets, including heatwave indicators and temperature extremes.
   • Climate Data Store