Comment on ‘A feedback loop with no brake’: how an AI doomsday report shook US markets

• TropicalDingdong@lemmy.world ⁨2⁩ ⁨days⁩ ago

  Gimme some coordinates.

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  • LincolnsDogFido@lemmy.zip ⁨2⁩ ⁨days⁩ ago

    57.4228475, -113.8340952

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    • TropicalDingdong@lemmy.world ⁨2⁩ ⁨days⁩ ago

      Well for one, that area already burned pretty recently. So its pretty unlikely to burn again any time soon.

      But as part of a larger picture:

      The area does experience fire-weather conditions for some portion of the year:

      Image

      Image

      Here we’re looking at HDWI (hot dry windy index), where a “loose” definition of fire weather is if HDWI is above 200. HDWI is based on a few factors, namely, how hot it is, how dry it is, and how fast the air is moving. Hot dry air moving quickly = fire weather.

      The number of fire weather days per year has been increasing, and in very recent years (the past decade) the rate of change has increased, and become statistically signficant:

      Image

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      So its not a particularly fire prone area, but its getting worse, and its getting worse at a faster rate.

      That would be the first part of the analysis I would run. After that, we’d look for historically “anomalous” periods. Its not enough to look at averages; that will wash over important features in the data. We need to look for specific periods where fire weather manifests.

      Image

      This is another way of thinking about fire risk. Here we’re going to count the amount of time, after 12 hours, that an area is in sustained fire-weather conditions. Basically, a bit of time in bad conditions isn’t the end of the world, but as you stay in fire weather conditions, fire risk increases exponentially (as plants/ fuels continue to dry out).

      If I were writing an insurance product for you, I would count the number of events in a given magnitude bucket and give you a risk rating. Here, licking my thumb and sticking it in the air, I would say… “not that bad”.

      Much of my work is around modeling in the wilderness urban interface. You picked an almost all wilderness area. Since there are no structures, I cant do the next analysis, but it would looks something like this:

      Image

      Most of my work is about figuring out what the impacts of wildfire on the built environment are going to be. Also, the free structure dataset I have access to doesn’t cover Canada and I’m not going to spend money buying the structures for you (unless you REALLY want me to).

      Those first figures are all specific to the coordinates you provided. The final figure is just an example.

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      • teslekova@sh.itjust.works ⁨1⁩ ⁨day⁩ ago

        Phwoar.

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