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Ice sheet numerical modeling is an important tool to estimate the dynamic contribution of the Antarctic ice sheet to sea level rise over the coming centuries. The influence of initial conditions on ice sheet model simulations, however, is still unclear. To better understand this influence, an initial state intercomparison exercise (initMIP) has been developed to compare, evaluate, and improve initialization procedures and estimate their impact on century-scale simulations. initMIP is the first set of experiments of the Ice Sheet Model Intercomparison Project for CMIP6 (ISMIP6), which is the primary Coupled Model Intercomparison Project Phase 6 (CMIP6) activity focusing on the Greenland and Antarctic ice sheets. Following initMIP-Greenland, initMIP-Antarctica has been designed to explore uncertainties associated with model initialization and spin-up and to evaluate the impact of changes in external forcings. Starting from the state of the Antarctic ice sheet at the end of the initialization procedure, three forward experiments are each run for 100 years: a control run, a run with a surface mass balance anomaly, and a run with a basal melting anomaly beneath floating ice. This study presents the results of initMIP-Antarctica from 25 simulations performed by 16 international modeling groups. The submitted results use different initial conditions and initialization methods, as well as ice flow model parameters and reference external forcings. We find a good agreement among model responses to the surface mass balance anomaly but large variations in responses to the basal melting anomaly. These variations can be attributed to differences in the extent of ice shelves and their upstream tributaries, the numerical treatment of grounding line, and the initial ocean conditions applied, suggesting that ongoing efforts to better represent ice shelves in continental-scale models should continue.

Predicting the climate for the future and how it will impact ice sheet evolution requires coupling ice sheet models with climate models. However, before we attempt to develop a realistic coupled setup, we propose, in this study, to first analyse the impact of a model simulated climate on an ice sheet. We undertake this exercise for a set of regional and global climate models. Modelled near surface air temperature and precipitation are provided as upper boundary conditions to the GRISLI (GRenoble Ice Shelf and Land Ice model) hybrid ice sheet model (ISM) in its Greenland configuration. After 20 kyrs of simulation, the resulting ice sheets highlight the differences between the climate models. While modelled ice sheet sizes are generally comparable to the observed one, there are considerable deviations among the ice sheets on regional scales. These deviations can be explained by biases in temperature and precipitation near the coast. This is especially true in the case of global models. But the deviations between the climate models are also due to the differences in the atmospheric general circulation. To account for these differences in the context of coupling ice sheet models with climate models, we conclude that appropriate downscaling methods will be needed. In some cases, systematic corrections of the climatic variables at the interface may be required to obtain realistic results for the Greenland ice sheet (GIS).

Stable isotope ratios δ18O and δD in polar ice provide a wealth of information about past climate evolution. Snow-pit studies allow us to relate observed weather and climate conditions to the measured isotope variations in the snow. They therefore offer the possibility to test our understanding of how isotope signals are formed and stored in firn and ice. As δ18O and δD in the snowfall are strongly correlated to air temperature, isotopes in the near-surface snow are thought to record the seasonal cycle at a given site. Accordingly, the number of seasonal cycles observed over a given depth should depend on the accumulation rate of snow. However, snow-pit studies from different accumulation conditions in East Antarctica reported similar isotopic variability and comparable apparent cycles in the δ18O and δD profiles with typical wavelengths of ∼ 20 cm. These observations are unexpected as the accumulation rates strongly differ between the sites, ranging from 20 to 80 mm w. e. yr−1 ( ∼ 6–21 cm of snow per year). Various mechanisms have been proposed to explain the isotopic variations individually at each site; however, none of these are consistent with the similarity of the different profiles independent of the local accumulation conditions.Here, we systematically analyse the properties and origins of δ18O and δD variations in high-resolution firn profiles from eight East Antarctic sites. First, we confirm the suggested cycle length (mean distance between peaks) of ∼ 20 cm by counting the isotopic maxima. Spectral analysis further shows a strong similarity between the sites but indicates no dominant periodic features. Furthermore, the apparent cycle length increases with depth for most East Antarctic sites, which is inconsistent with burial and compression of a regular seasonal cycle. We show that these results can be explained by isotopic diffusion acting on a noise-dominated isotope signal. The firn diffusion length is rather stable across the Antarctic Plateau and thus leads to similar power spectral densities of the isotopic variations. This in turn implies a similar distance between isotopic maxima in the firn profiles.Our results explain a large set of observations discussed in the literature, providing a simple explanation for the interpretation of apparent cycles in shallow isotope records, without invoking complex mechanisms. Finally, the results underline previous suggestions that isotope signals in single ice cores from low-accumulation regions have a small signal-to-noise ratio and thus likely do not allow the reconstruction of interannual to decadal climate variations.

The basal topography is largely unknown beneath most glaciers and ice caps, and many attempts have been made to estimate a thickness field from other more accessible information at the surface. Here, we present a two-step reconstruction approach for ice thickness that solves mass conservation over single or several connected drainage basins. The approach is applied to a variety of test geometries with abundant thickness measurements including marine- and land-terminating glaciers as well as a 2400 km2 ice cap on Svalbard. The input requirements are kept to a minimum for the first step. In this step, a geometrically controlled, non-local flux solution is converted into thickness values relying on the shallow ice approximation (SIA). In a second step, the thickness field is updated along fast-flowing glacier trunks on the basis of velocity observations. Both steps account for available thickness measurements. Each thickness field is presented together with an error-estimate map based on a formal propagation of input uncertainties. These error estimates point out that the thickness field is least constrained near ice divides or in other stagnant areas. Withholding a share of the thickness measurements, error estimates tend to overestimate mismatch values in a median sense. We also have to accept an aggregate uncertainty of at least 25 % in the reconstructed thickness field for glaciers with very sparse or no observations. For Vestfonna ice cap (VIC), a previous ice volume estimate based on the same measurement record as used here has to be corrected upward by 22 %. We also find that a 13 % area fraction of the ice cap is in fact grounded below sea level. The former 5 % estimate from a direct measurement interpolation exceeds an aggregate maximum range of 6–23 % as inferred from the error estimates here.

We examine some practical aspects of using a mushy-layer Rayleigh number for the interpretation of sea-ice-core data. In principle, such analysis should allow one to determine convectively active regions within the ice core by identifying those regions in which the mush-Rayleigh number is super-critical. In practice, however, a quantitative analysis is complicated by uncertainties regarding the specific formulation of both the mush-Rayleigh number itself and of the sea-ice permeability that is crucial for quantifying the Rayleigh number. Additionally, brine loss from highly permeable sections of the ice core, in particular close to the ice–ocean interface, and typically weekly ice core sampling, limit the practical applicability of the Rayleigh number for ice-core interpretation. We here quantify these uncertainties, suggest a standard method for the computation of the Rayleigh number for sea ice and discuss possibilities and limitations of ice-core interpretation based on the Rayleigh number.