• @bbuez@lemmy.world
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    94 months ago

    We’ll call these hot models, since they obviously are too pessimistic, so we’ll make some biased models

    1 decade later, “hot models” more accurately predicted our current state

    Huh maybe these new models are too pessimistic

    • @silence7@slrpnk.netOPM
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      34 months ago

      It’s worth noting that the quotes above are not from the article.

      I recommend reading the article.

      • @bbuez@lemmy.world
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        14 months ago

        Sorry! I don’t mean to appropriate the article, I did read and agree with what it has to say.

        But at the risk of sounding reductionary, the people who care and have influence over climatological matters don’t give a shit about what Trump has to spout on the matter, and the people listening to him will not have their minds changed.

        And again to be reductionary, we know our effect on the climate, nuance only blurs picture for average people. This is partially talked about in the article as for the planetary/regional temperature difference, but personally I think this is something general science communication could work on, which we’ve seen as climate change vs global warming, though both describe the same thing.

        Models blur the laymans picture and feeds into denial when predictions aren’t correct, and as their value lies in future predictions that past trends also corroborate, more emphasis should be put on said measureable effects.

        Just my 2¢, no disagreement with the article intended

        • @futatorius@lemm.ee
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          4 months ago

          Models blur the laymans picture and feeds into denial when predictions aren’t correct, and as their value lies in future predictions that past trends also corroborate, more emphasis should be put on said measureable effects.

          No models, no chance of reliable forecasting. What the layman (or the oil-company shill) has to say about errors is irrelevant. All they have are baseless opinions and vested interests. Everyone who works on developing models is constantly bringing in new theory, responding to new kinds of observations as instrumentation and coverage improve, correcting the models based on observations, doing backcasting and improving skill scores.