Hot days could last four hours longer by the end of the century under a high-emissions scenario

Extreme heat is intensifying due to climate change – heat whose hourly fluctuations are not captured by traditional daily temperature indicators. Research published in Nature Climate Change has analysed global hourly data from 1981 to 2023, alongside climate projections through to the end of the 21st century. More than 80 per cent of the world’s land surface showed an increase in heat. Under a high-emissions scenario, the authors predict that, for the period 2070–2099, each hot day could include more than four hours of additional high temperatures compared with current levels (2001–2023). They also predict that non-hot days could see a further three hours of high temperatures, which would likely go undetected by daily measurements. Low- and middle-income countries are the hardest hit, bearing more than three-quarters of current and future heat exposure.

Expert reactions

Ernesto Rodríguez Camino - calor HHE

Ernesto Rodríguez Camino

Senior State Meteorologist and president of Spanish Meteorological Association

Science Media Centre Spain

This study describes episodes of extreme heat using both observational and model-based hourly data, in contrast to most studies carried out to date, which use data on average daily temperatures and daily maximum or minimum temperatures. This higher temporal resolution reveals new ‘peaks’ of extreme heat on an hourly scale which, until now, had gone unnoticed due to the use of daily data.

The use of hourly data, as done in this study to analyse extreme heat events, is equally relevant for other climatological variables such as precipitation, wind, etc. The analysis of the consequences of heavy rainfall, in the form of flash floods or flooding, is clearly not the same whether we use hourly data or aggregate it on a daily basis. Whilst daily data smooth out precipitation extremes, hourly data – both in observations and in model-based forecasts – reveal peaks of intense precipitation whose impacts are clearly more destructive.

Until relatively recently, weather observations were carried out manually on a daily basis and, consequently, studies and analyses were based exclusively on daily data. The gradual automation of observations has made it possible, as in this study, to begin working with hourly time series, significantly increasing the temporal resolution and revealing meteorological and climatic behaviour at a sub-daily scale. Similarly, the increasing spatial resolution of models and the ability to generate – and, above all, store – hourly simulations allow us to project the behaviour of extreme meteorological variables on an hourly scale, opening up a vast field for exploring climate behaviour on the smallest temporal scales.

The author has not responded to our request to declare conflicts of interest
EN

José Miguel Viñas - calor HHE

José Miguel Viñas

Meteorologist at Meteored at www.tiempo.com and consultant for the WMO (Spain)

Science Media Centre Spain

Alongside the growing impact of extreme heat – such as that which is currently wreaking havoc across Europe and other regions of the world this summer – an increasing number of studies are emerging that analyse the observed intensification of heat, the mechanisms driving these increasingly frequent and more severe heat events, and their consequences.

This research has focused on a novel aspect: the hourly-scale assessment of temperature distribution during extreme heatwaves. This will enable a better characterisation of the impact on human health of persistent high temperatures, both at peak levels reached during the day and at night. The insights provided by this study may also help to improve adaptation measures and the design of early-warning systems for the public that are more effective than current ones, providing information on the most critical moments of heatwaves.

The author has not responded to our request to declare conflicts of interest
EN
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Nature Climate Change
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Liao et al.

Study types:
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  • Peer reviewed
  • Modelling
  • Observational study
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