Supervolcanic eruptions induced abrupt global cooling (roughly at a rate of ~1ºC/year lasting for years to decades), such as the prehistoric Yellowstone eruption released, by some estimates, SO2 about 100 times higher than the 1991 Mt. Pinatubo eruption. An abrupt global cooling of several ºC, even if only lasting a few years, would present immediate and drastic stress on biodiversity and food production - posing a global catastrophic risk to human society. Using a simple climate model, this paper discusses the possibility of counteracting supervolcanic cooling with the intentional release of greenhouse gases. Although well-known longer-lived compounds such as CO2 and CH₄ are found to be unsuitable for this purpose, select fluorinated gases (F-gases), either individually or in combinations, may be released at gigaton scale to offset most of the supervolcanic cooling. We identify candidate F-gases (viz. C4F6 and CH3F) and derive radiative and chemical properties of ‘ideal’ compounds matching specific cooling events. Geophysical constraints on manufacturing and stockpiling due to mineral availability are considered alongside technical and economic implications based on present-day market assumptions. The consequences of F-gas release in perturbing atmospheric chemistry are discussed in the context of those due to the supervolcanic eruption itself. The conceptual analysis here suggests the possibility of mitigating certain global catastrophic risks via intentional intervention.

This study evaluates a lightning parameterization that utilizes only large-scale environmental variables (i.e., convective available potential energy (CAPE), column moisture, and lifting condensation level (LCL)) for present-day (2017-19) and end-of-century (2098-2100) RCP8.5 climate scenarios in the Community Atmosphere Model version 5 (CAM5). Using a single equation, the present-day prediction can produce a reasonable land/ocean ratio in lightning occurrence. The end-of-century prediction shows relative increases of about 50% over higher-latitude land, but much more variable increases and decreases across mid-latitude ocean and the tropics such that the overall global lightning occurrence is expected to slightly decrease. Lightning occurrence over land predicted from present-day CAM5 is less than that using MERRA-2 reanalysis because of differences in the basic-state variables used as predictors. In addition, the choice of dilute or undilute CAPE will impact future lightning predictions over land, but the environment-only parameterization results are more consistent than a CAPE x precipitation parameterization.

Risk assessments of air pollution impacts on human health and ecosystems would ideally consider a broad set of climate and emission scenarios and the role of natural internal climate variability within a single scenario. We analyze initial condition chemistry-climate ensembles to gauge the significance of greenhouse-gas-induced air pollution changes relative to internal climate variability, and response differences in two models. To quantify the effects of climate change on the frequency and duration of summertime regional-scale pollution episodes over the Eastern United States (EUS), we apply an Empirical Orthogonal Function (EOF) analysis to a 3-member GFDL-CM3 ensemble with prognostic ozone and aerosols and a 12-member NCAR-CESM1 ensemble with prognostic aerosols under a 21st century RCP8.5 scenario with air pollutant emissions frozen in 2005. Correlations between GFDL-CM3 principal components for ozone, PM2.5 and temperature represent spatiotemporal relationships discerned previously from observational analysis. Over the Northeast region, both models simulate summertime surface temperature increases of over 5 °C from 2006-2025 to 2081-2100 and PM2.5 of up to 1-4 μg m-3. The ensemble average decadal incidence of upper quartile Northeast PM2.5 events lasting at least five days doubles in GFDL-CM3 and increases >50% in NCAR-CESM1. In other EUS regions, inter-model differences in PM2.5 responses to climate change cannot be explained by internal climate variability. Our EOF-based approach anticipates future opportunities to data-mine initial condition chemistry-climate model ensembles for probabilistic assessments of changing frequency and duration of regional-scale pollution and heat events while obviating the need to bias-correct concentration-based thresholds separately in individual models.