/* Modeling the annual probability of cooling events from volcanic eruptions */ // See the sister model which focuses on severity of volcanic cooling events here: https://squigglehub.org/models/ASRS-Resilience/Volcanic-Cooling-Events // Method 1 uses modeled temperature change data from Stoffel et al. (2015) https://dendrolab.ch/wp-content/uploads/2018/10/Stoffel_etal_NGEO_2015.pdf // The paper models non-tropical cooling over land. This is often more extreme than overall land cooling, which is what we are modeling, so a discount is applied to account for the increased sensitivity
/* Modeling the probability and severity of volcanic cooling events */ // Method 1: Based on the assumption that (A) 1+ degree cooling events happen with a period of 150 years, (B) 1.5+ degree cooling events happen with a period of 500 years, and (C) 2+ degree cooling events happen with a period of 3000 years [Source: Fig. 1d from Stoffel et al. (2015): https://dendrolab.ch/wp-content/uploads/2018/10/Stoffel_etal_NGEO_2015.pdf] // Construct four models, two exponential and two power-law, and use a mixture of all four models. // Incorporate uncertainty into the relative frequency of 1, 1.5 and 2-degree cooling events. 1.5-degree cooling events represent approximately 30% of 1-degree cooling events, and 2-degree cooling events represent approximately 5% of 1-degree cooling events. I intruduce a subjective amount of uncertainty to these figures such that the 95th percentile is approximately 2x the mean:
/* Modeling the global cooling rate expected from a large-scale nuclear exchange, assuming atmospheric BC levels are 0.1x-1x those estimated in Reisner */ // Using the competing Robock claims 5Tg of stratospheric soot in a 100x15kT conflict between India and Pakistan. This is likely to be a pessimistic estimate, so we use it as a 95th percentile and place the 5th percentile 10x lower. bc_min_all_countervalue = 0.5 to 5 // Proportion of strikes that are countervalue: Nuclear cooling effects are considered to be far greater for nuclear strikes in fuel-rich urban areas, which are more likely to create firestorms that loft BC high into the atmosphere. Metaculus has a question on the proportion of detonations that are expected to be countervalue. Many of the responses are clustered around 0% and 100%, probably because a very small number of strikes is most likely. Around 12% of responses are under 1% and 10% are above 99%. I subjectively remove the top and bottom 10% of Metaculus estimates, so that the 25th and 75th pecentiles become 15th and 85th percentiles. I use the Beta distribution with these percentiles to model the proportion of strikes that are countervalue (urban) and not counterforce (military capabilities). I assume that the BC generated by counterforce strikes is small but not negligible: one tenth of the amount generated by countervalue strikes.