Verbalising the distinctions between 1 − 5 was something I was struggling with, so thanks for putting it so concisely and comprehensively. I agree with all the points you have made and the clarification at the end, which is what I was trying to say in a jumbled up way.
My impression on tipping point sensitivity was based on specific events happening significantly ahead of projections from modelling. I will have a read through the linked paper suggesting tipping points aren’t as bad as thought and comment on your linked post from March if necessary, but otherwise will update based on that.
I also agree that while the expected temperature trajectory is moderating (as well as the risk of higher trajectories), we may be underestimating the “political climate sensitivity” which is a function of the risks you provided in Figure 4 rather than warming, and which appear to be getting worse. I also don’t think great power conflict is significantly exacerbated by these indirect effects until much higher warming but Israel / Arab world and Pakistan / India are a couple of conflicts I think could be worsened and would still be of global concern, despite not being between Great Powers.
I haven’t done a deep dive on it but my reading has leant towards political instability being very sensitive to increases in risks, risks which are plausible at temperatures expected in the next 30 years. That being said, the frequent example of the Syria drought-conflict could be the wrong narrative in favour of unsustainable agricultural policies. So I think I need to investigate more.
Thanks for the discussion!
I think when considering your estimates for 1. it is important to consider the boundaries given by those sources and to contextualise them.
The WHO is only looking at disease burden but even there they are expecting 250k to 2050 (not even looking to 2100) and they estimate that CC will exacerbate malnutrition by 3% of current values—this seems extremely conservative. They don’t seem to include the range increases for most other insect-transmitted diseases, just malaria, even within the extremely limited subset of causes they consider.
Impactlab’s “big data approach”—they don’t give their assumptions, parameters, or considerations—I think this should largely be discounted as a result. It seems to be based on historic and within-trend correlation data, not accounting for risk of any higher-level causes of mortality such as international conflicts, political destabilisation, famine, ecological collapse, climate migration, infrastructure damage etc. that will have an impact and I am guessing aren’t accounted for in their correlational databank.
Danny Bressler is only looking at extrapolating inter-personal conflicts. It doesn’t include famines, pandemics, increased disease burden, ecosystem collapse, great nation conflicts, etc. etc. etc. that are very likely to be much, much worse than the trends considered in his model. As such his 74 million estimate should be considered an extremely conservative lower bound to the estimated value. He is also showing a significant upwards trend per-year, so the burden should be considered to exacerbate over time.
Overall this seems to cast doubt on 1, 4 and 5. For 2. I have also critiqued John Halstead’s work in a previous post, and the Ozy Brennan post is refuting CC as an extinction risk, not as a global catastrophic risk as you use it. He is saying nothing about the chances of >10% likelihood of >10% population decrease. These combined should cause pause for thought when making statement 7.