Climate change now detectable in daily weather, say scientists

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A new study has revealed that the effects of climate change are now detectable in daily global weather.

The study, which was carried out by researchers at the ETH university in Zurich, deployed a computer-based technique called statistical learning to examine worldwide weather.

Using data from measuring stations the technique compared and contrasted daily global weather with the yearly global average temperature and with Earth’s energy imbalance – the amount of solar energy retained by Earth’s atmosphere.

The results of the analysis, which were published in Nature Climate Change, showed that for every single day for almost a decade there have been locations where the above and below average temperature and moisture have been out of sync with natural variations.

The study, which disrupts the long-held paradigm that weather-is-not-climate, also upends the arguments of climate change deniers who often point to cold weather spells as proof that global warming is not happening.

But according to the researchers the impact of localized cooler-than-average weather is canceled out when weather for the entire globe is taken into account.

For example, a colder-than-average autumn for parts of the USA in 2019 was paired with one of the warmest Octobers and Novembers on record for much of the rest of the globe.

“Uncovering the climate change signal in daily weather conditions calls for a global perspective, not a regional one,” said Sebastian Sippel, part of the ETH research team.

For the study ETH collaborated with the Swiss Data Science Center (SDSC). According to the researchers data science methods not only allow them to demonstrate the clear impact of climate change on daily weather, they also help reveal where in the world climate change is recognizable at an early stage.

“In future, we should therefore be able to pick out human-induced patterns and trends in other more complex measurement parameters, such as precipitation, that are hard to detect using traditional statistics,” said lead researcher Reto Knutti.

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