Dome A is the peak of the East Antarctic Ice Sheet (EAIS), underlain by the rugged Gamburtsev Subglacial Mountains (GSM). The rugged basal topography produces a complex hydrological system featuring basal melt, water transport and storage, and freeze-on. In a companion paper, we used an inverse model to infer the spatial distributions of geothermal flux and accumulation rate that best fit a vareity of observational constraints. Here, we present and analyze the best-fit state of the ice sheet in detail. Our model agrees well with the observed water bodies and freeze-on structures, while also predicting a significant amount of unobserved water and suggesting a change in stratigraphic interpretation that reduces the volume of the freeze-on units. We predict that a weak Raymond effect underneath the ice divide has been mostly masked by the high-amplitude variability in the layers produced by draping over subglacial topography. Our model stratigraphy agrees well with observations, and we predict- assuming that the ice divide has been stable over time- that there will be two distinct patches of ice older than 1 Ma suitable for ice coring underneath the divide. Finally, our geothermal flux estimate is substantially higher than previous estimates for this region. Correcting for the bias induced by unresolved narrow valleys still leaves our result in the high end of past estimates, with substantial local anomalies that are hotter still. Fundamentally, the observational evidence of a complex basal hydrological system is inconsistent with a simple picture of a uniformly cold East Antarctic craton.

Ice-penetrating radar data contain a wealth of information about the bed and internal structure of the ice sheet. While these data have long been used to diagnose the presence of basal water or infer attenuation rates, they have rarely been used in a formal inverse model for the ice sheet temperature structure. Here, we invert a coupled thermomechanical ice sheet and basal hydrology model to infer both geothermal flux and accumulation rate from multiple classes of radar observations in the area around Dome A, East Antarctica. Our forward model solves for a coupled steady state between the ice sheet flow field, temperature, and basal hydrology, including melt, water transport, and freeze-on. We fit radar observations of basal water, freeze-on, and internal layers, along with a geothermal flux prior based on aeromagnetic observations (Martos et al., 2017). We minimize the combined misfit function by first using an evolutionary algorithm to find the approximate answer in parameter space, and then optimizing the fit with localized perturbations. In addition to inferring the spatial distribution of geothermal flux and accumulation rate, we are also able to estimate the uncertainty and skewness of their probability distributions, as well as quantify how our result on each individual data constraint. Our results demonstrate a new method for combining multiple glaciological constraints into a single inverse model of the ice sheet, and give us a more rigorous picture of the information content provided by each dataset. In a companion paper we analyze and interpret the best-fit model.

Stratospheric aerosol injection (SAI) has been shown in climate models to reduce some impacts of global warming in the Arctic, including the loss of sea ice, permafrost thaw, and reduction of Greenland Ice Sheet (GrIS) mass; SAI at high latitudes could preferentially target these impacts. In this study, we use the Community Earth System Model to simulate two Arctic-focused SAI strategies, which inject at 60°N latitude each spring with injection rates adjusted to either maintain September Arctic sea ice at 2030 levels (“Arctic Low”) or restore it to 2010 levels (“Arctic High”). Both simulations maintain or restore September Arctic sea ice to within 10% of their respective targets, reduce permafrost thaw, and increase GrIS surface mass balance by reducing runoff. Arctic High reduces these impacts more effectively than a globally-focused SAI strategy that injects similar quantities of SO2 at lower latitudes. However, Arctic-focused SAI is not merely a “reset button” for the Arctic climate, but brings about a novel climate state, including changes to the seasonal cycles of Northern Hemisphere temperature and sea ice and less high-latitude carbon uptake relative to SSP2-4.5. Additionally, while Arctic-focused SAI predominantly cools the Arctic, its effects are not confined to the Arctic, including detectable cooling throughout most of the northern hemisphere for both simulations, increased mid-latitude sulfur deposition, and a southward shift of the location of the Intertropical Convergence Zone (ITCZ).