4 Comments

  1. I’ve linked to the press release in the post above. In this comment, for those interested, here’s the link to the peer reviewed journal article:

    https://iopscience.iop.org/article/10.1088/1748-9326/ad91ca

    From the linked article:

    AI predicts that most of the world will see temperatures rise to 3C much faster than previously expected

    Three leading climate scientists have combined insights from 10 global climate models and, with the help of artificial intelligence (AI), conclude that regional warming thresholds are likely to be reached faster than previously estimated.

    The study, published in Environmental Research Letters by IOP Publishing, projects that most land regions as defined by the Intergovernmental Panel on Climate Change (IPCC) will likely surpass the critical 1.5°C threshold by 2040 or earlier. Similarly, several regions are on track to exceed the 3.0°C threshold by 2060—sooner than anticipated in earlier studies.

    Regions including South Asia, the Mediterranean, Central Europe and parts of sub-Saharan Africa are expected to reach these thresholds faster, compounding risks for vulnerable ecosystems and communities.

  2. Hypno--Toad on

    We’ve always known Australia will be one of the first, and we also know mass migrations are inevitable.

    Our governments are sliding towards a more authoritarian party and leader, due to economic instability, and we will not adjust fast enough to avoid this horrible eventuality.

  3. I don’t get it, why don’t we just move our industry into an ice biome and set up a cool air SPOM?

  4. SonofMakuta on

    Worth noting that this is assuming the “SSP3-7.0” climate future scenario, aka we don’t do particularly well at limiting warming, leading to ~3.6C by 2100. I believe this model is already something we’ve avoided (recent projections have us at ~2.4 if nothing else improves, to my knowledge) and so the headline of this post is somewhat misleading IMO.

    That said, the paper’s general conclusion that regional warming in some areas is faster than expected (setting aside exact numbers), and the specific reasons they’ve identified, may well still apply and can hopefully be used to refine and improve policy in the coming years.

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