The world just saw its hottest day ever, here’s how it was analyzed

On Sunday, July 21, the world had its hottest day on record. Just 24 hours later, that record was broken again, making last Monday most likely the hottest day in thousands of years.

It may seem unlikely that scientists will measure the world’s hottest day, given that they do not have temperature monitors in every corner of the world and have less than a century of relatively widespread observations. But they have developed a technique that is increasingly useful as the planet warms.

This month’s shocking heat findings, announced by the EU’s Copernicus Climate Change Service, are based on “reanalysis”, a technique that mixes temperature data and models to provide a global view of the climate. The center creates a near real-time picture of Earth’s climate, including temperature, wind and precipitation, for (roughly) every 30 square kilometer patch of the planet’s surface.

This reanalysis dates back to 1940 and allows researchers to reliably say when a record is broken, whether by a day, month or year. In addition to the new daily heat record, the data also shows that 2023 was the hottest year on record and that every month in the last 13 months has been the hottest on record.

Although there are not thermometers in every corner of the world, Copernicus receives a large amount of meteorological data that it uses to inform its reanalysis. “We have this constant flow of information reaching the center,” says Carlo Buontempo, director of the Climate Change Service, which is part of the European Center for Medium-Range Weather Forecasts (ECMWF).

The center’s scientists receive 100 million readings a day about weather conditions from around the world. Observations come from planes, satellites, ships, radars and surface weather stations – all feeding real-time information about temperature, wind, rain and snow, as well as other factors like air pollution. This information is fed into a model, known as ERA5, which is already equipped with historical information about the global climate.

There are gaps in these observations because data sources do not cover all parts of the world. Weather conditions such as cloudy skies can also reduce the amount of data coming from sources such as satellites. To fill these gaps, scientists take the predictions they have already made, based on the long-term ERA5 model, and test them against observations. This means that a forecast predicting a particular temperature in a particular location will be tested against all the data researchers receive about the climate in that location and nearby, as well as broader forces such as ocean currents and air circulation.

This is done repeatedly while evaluating how compatible the prediction is with what was actually recorded. The model also accounts for any errors in recorded data and is based on the laws of physics, including the weather patterns, currents and air flow that govern how the global climate works.

This way, it is possible to create a complete and as accurate image as possible. This is what allows scientists to confidently declare records as when the world experienced the hottest day in human history.

Globally, five meteorological services – the US National Oceanic and Atmospheric Administration and NASA, the ECMWF, the China Meteorological Administration and the Japan Meteorological Agency – conduct continuous assessments of global temperature using this technique. Although their models are slightly different, the five groups reached similar conclusions about the record heat in recent months and years.

Historical data is more difficult to obtain. The longest temperature series, the Central England Temperature in the United Kingdom, began in the 17th century. Data before humans systematically monitored temperatures came from sources such as gas bubbles trapped in glacial ice or tree rings. These sources are not as specific as a thermometer reading, but it is possible to say with confidence that recent temperatures are probably the highest in the last 100,000 years, says Copernicus.

Meteorologists also have a good idea of ​​when a particularly significant day, like the hottest day on record, is on the way. This is in part because global average temperatures generally peak between early July and early August. Last year’s hottest day – which was the previous record for hottest day ever – occurred in early July, in the middle of a historic ocean heatwave. The intensification of El Nino – a natural global climate phenomenon that normally means warmer temperatures globally – provided yet another clue that record heat was brewing.

Until July of this year, it looked like the world wouldn’t set a new daily record, says Buontempo. “The average global ocean temperature has started to rise again,” he says. “Some of the people who systematically monitor our forecasts have started to sound the alarm.” Early last week, they were paying increased attention to the reanalysis and preparing to make an announcement.

This technique isn’t just useful for making “hottest day ever” announcements: it’s being used to train AI forecasting models, especially for “joint” weather forecasts that represent multiple possible future scenarios. It’s also used by solar energy companies to help homeowners calculate how much energy their panels can generate, and by wind energy companies to plan where to place wind farms.

Copernicus is currently working on a new model, known as ERA6, which will be more accurate – dividing the world into 14-kilometre squares – and will incorporate many more historical data sources, including early satellite readings from the 1970s.

For Buontempo, more important than any day is the recent extraordinary series of record-breaking months, as it is a better indicator of how quickly the world is warming. But pinpointing a specific day makes climate change seem much more immediate.

“I think we have to make it more tangible, more direct, more visible,” he says. “It’s important that people are informed.”

(Except the headline, this story has not been edited by NDTV staff and is published from a syndicated feed.)