Models in ASRS-Resilience

/*
Modeling the probability and severity of volcanic cooling events
Like my other model, but uses geomean of odds to calculate final probabilities, rather than geomean of probabilities
*/

// 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 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
*/

// Using the competing Reisner and Toon claims on the soot injection of a regional nuclear exchange as a basis, this model extrapolates to estimate the level of cooling expected from a nuclear war of at least 100 detonations.

// Black carbon (known as BC or soot) in stratosphere from 100x15kT-warhead nuclear exchange (Tg), all strikes countervalue. Use the Toon estimate of 5Tg as the 95th percentile. Reisner estimates 0.2Tg, but claims this is an overestimate since they assume all combustible material is converted to BC, while the true amount would be 10-100 times less. Denkenberger & Pearce (2018) models the soot-emission factor as lognormally-distributed with 90% CI (1%,4%), which has mean value 2.2%. Hence our lower estimate, which we use as the 5th percentile, is 0.2Tg * 0.022 = 0.0044Tg

bc_min_all_countervalue = mx(truncate(0.5 to 5,0.5,5),0.5,5,[0.9,0.05,0.05])

/*
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