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Salon
Salon
Science
Matthew Rozsa

We had our hottest summer ever — again

For the second summer in a row, global temperatures broke temperature records, according to the European climate service Copernicus, putting this year on track to be the hottest in recorded history. Specifically, summer 2024 was 0.69 degrees Celsius hotter than the 1991 to 2020 average and was, additionally, 0.03 degrees hotter than summer 2023's record-setting temperatures.

More concerningly, Earth is creeping closer to the 1.5 degrees Celsius threshold established by the Paris climate accord in 2015 that experts agree is necessary to avoid greater calamity. Indeed, a recent study found that 1.6 degrees Celsius is the best we can hope for at this point, but even fraction of a degree counts.

As the global average temperatures reach and surpass that level, they will lead to a phenomenon that Dr. Twila Moon, a climatologist and deputy lead scientist at NASA's National Snow and Ice Data Center, told Salon in July can be described as "global weirding."

This will include "more extreme weather events producing conditions that are entirely new for communities, weather whiplash as folks may experience quick swings between hot and cold or drought and flood, and many challenges for crops, wildlife, recreation, and being able to plan for what we previously considered normal weather conditions."

According to the recent Copernicus data, the Earth's average temperature in August 2024 was on average 16.82 degrees Celsius (62.28 Fahrenheit), 1.51 degrees Celsius warmer than an average August in the pre-industrial era. Meanwhile the period from September 2023 to August 2024 was the hottest on record for any year-long period, or 1.64 degrees Celsius above pre-industrial levels.

"I am 100% certain that worsening heat waves across Earth are due to global heating caused primarily by burning fossil fuels," Dr. Peter Kalmus, a NASA climate scientist who emphasized his opinions are his own, told Salon in June. "We see intensifying extreme heat in all observational datasets and model hindcasts."

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