A new study relying on machine learning methods finds the climate thresholds in the Paris Agreement may be exceeded earlier than anticipated, Andrew writes.
Why it matters: The world is already suffering the impacts of 1.1°C (1.98°F) to 1.2°C (2.16°F) of warming to date, and passing 1.5°C or 2°C above preindustrial levels would dramatically increase the risks to society and ecosystems.
The big picture: The study, published Monday in the Proceedings of the National Academy of Sciences, uses neural networks trained on climate model simulations to predict the time remaining until the Paris temperature targets will be reached.
- In line with previous studies, the researchers found the world has about a decade until the 1.5°C target is breached.
- Notably, it finds that even the lowest emissions scenario, with steep cuts to fossil fuel use, still has a significant chance of exceeding the 2°C target, potentially as soon as 2043.
What they’re saying: “Its always a bit tricky to know how much faith to put in machine learning methods like this given the absence of physical modeling of the systems involved,” Zeke Hausfauther, climate research lead at payments company Stripe, who was not involved in the new study, told Axios via email.
- He said the research offers reason for caution about assuming an emissions pathway will hold warming below a certain level.
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