Just a side note. The study you mention as especially rigorous in 1) iii) (https://agupubs.onlinelibrary.wiley.com/doi/full/10.1002/2017JD027331) was made in Los Alamos Labs, an organization who job it is to make sure that the US has a large and working stockpile of nuclear weapons. It is financed by the US military and therefore has a very clear inventive to talk down the dangers of nuclear winter. Due to this reason this study has been mentioned as not to be trusted by several well connected people in the nuclear space I talked to.
Yes, I am aware of this and if this space was closer to my grantmaking, I’d be excited to fund a fully neutral study into these questions.
That said, the extremely obvious bias in the stuff of the Robock and Toon papers should still lead one to heavily discount their work.
As @christian.r who is a nuclear risk expert noted in another thread, the bias of Robock et al is also well-known among experts, yet many EAs still seem to take them quite seriously which I find puzzling and not really justifiable.
Yeah fair enough. I personally, view the Robock et al. papers as the “let’s assume that everything happens according to the absolute worst case” side of things. From this perspective they can be quite helpful in getting an understanding of what might happen. Not in the sense that it is likely, but in the sense of what is even remotely in the cards.
I am still a bit skeptical because I don’t think it would be surprising if the worst case of what can actually happen is actually much less worse than what Robock et al model. I think the search process for that literature was more “worst chain we can imagine and get published”, i.e. I don’t think it is really inherently bound to anything in the real world (different from, say, things that are credibly modeled by different groups and the differences are about plausibility of different parameter estimates).
Yes, since the case for nuclear winter is quite multiplicative, if too many pessimistic assumptions were stacked together, the final result would be super pessimistic. Luísa and Denkenberger 2018 modelled variables as distributions to mitigate this, and did arrive to more optimistic estimates. From Fig. 1 of Toon 2008, the soot ejected into the stratosphere accounting for only the US and Russia is 55.0 Tg (= 28.1 + 26.9). Luísa estimated 55 Tg to be the 92th percentile assuming “the nuclear winter research comes to the right conclusion”:
However, Luísa and Denkenberger 2018 still broadly relied on the nuclear winter literature. Johannes commented he “would not be shocked at all if the risk from nuclear winter would be < 1⁄100 than the estimate of the Robock group”, which would be in agreement with Bean’s BOTEC.
Just a side note. The study you mention as especially rigorous in 1) iii) (https://agupubs.onlinelibrary.wiley.com/doi/full/10.1002/2017JD027331) was made in Los Alamos Labs, an organization who job it is to make sure that the US has a large and working stockpile of nuclear weapons. It is financed by the US military and therefore has a very clear inventive to talk down the dangers of nuclear winter. Due to this reason this study has been mentioned as not to be trusted by several well connected people in the nuclear space I talked to.
An explanation of why it makes sense to talk down the risk of nuclear winter, if you want to have a working deterrence is describe here: https://www.jhuapl.edu/sites/default/files/2023-05/NuclearWinter-Strategy-Risk-WEB.pdf
Yes, I am aware of this and if this space was closer to my grantmaking, I’d be excited to fund a fully neutral study into these questions.
That said, the extremely obvious bias in the stuff of the Robock and Toon papers should still lead one to heavily discount their work.
As @christian.r who is a nuclear risk expert noted in another thread, the bias of Robock et al is also well-known among experts, yet many EAs still seem to take them quite seriously which I find puzzling and not really justifiable.
Here’s hoping that the new set of studies on this funded by FLI (~$4 million) will shed light on the issue within the next few years.
https://futureoflife.org/grant-program/nuclear-war-research/
Yeah fair enough. I personally, view the Robock et al. papers as the “let’s assume that everything happens according to the absolute worst case” side of things. From this perspective they can be quite helpful in getting an understanding of what might happen. Not in the sense that it is likely, but in the sense of what is even remotely in the cards.
Yeah, that seems the best use of these estimates.
I am still a bit skeptical because I don’t think it would be surprising if the worst case of what can actually happen is actually much less worse than what Robock et al model. I think the search process for that literature was more “worst chain we can imagine and get published”, i.e. I don’t think it is really inherently bound to anything in the real world (different from, say, things that are credibly modeled by different groups and the differences are about plausibility of different parameter estimates).
Yes, since the case for nuclear winter is quite multiplicative, if too many pessimistic assumptions were stacked together, the final result would be super pessimistic. Luísa and Denkenberger 2018 modelled variables as distributions to mitigate this, and did arrive to more optimistic estimates. From Fig. 1 of Toon 2008, the soot ejected into the stratosphere accounting for only the US and Russia is 55.0 Tg (= 28.1 + 26.9). Luísa estimated 55 Tg to be the 92th percentile assuming “the nuclear winter research comes to the right conclusion”:
Denkenberger 2018 estimated 55 Tg to be the 80th percentile:
However, Luísa and Denkenberger 2018 still broadly relied on the nuclear winter literature. Johannes commented he “would not be shocked at all if the risk from nuclear winter would be < 1⁄100 than the estimate of the Robock group”, which would be in agreement with Bean’s BOTEC.
Quick updated. I made a comment with estimates for the probability of the amounts of soot injected into the stratosphere studied in Xia 2022.