• European Marine Science
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The thermokarst lakes of permafrost regions play a major role in the global carbon cycle. These lakes are sources of methane to the atmosphere but the methane flux is restricted by an ice cover for most of the year. We provide insights into the methane pathways in the winter ice cover on three different water bodies in a continuous permafrost region in Siberia. The first is a bay underlain by submarine permafrost (Tiksi Bay, TB), the second a shallow thermokarst lagoon (Polar Fox, PF) and the third a land-locked, freshwater thermokarst lake (Goltsovoye Lake, GL). In total, 11 ice cores were analyzed as records of the freezing process and methane pathways during the winter season. In TB, the hydrochemical parameters indicate an open system freezing. In contrast, PF was classified as a semi-closed system, where ice growth eventually cuts off exchange between the lagoon and the ocean. The GL is a closed system without connections to other water bodies. Ice on all water bodies was mostly methane-supersaturated with respect to the atmospheric equilibrium concentration, except of three cores from the lake. Generally, the TB ice had low methane concentrations (3.48–8.44 nM) compared to maximum concentrations of the PF ice (2.59–539 nM) and widely varying concentrations in the GL ice (0.02–14817 nM). Stable delta13CCH4 isotope signatures indicate that methane above the ice-water interface was oxidized to concentrations close to or below the calculated atmospheric equilibrium concentration in the ice of PF. We conclude that methane oxidation in ice may decrease methane concentrations during winter. Therefore, understanding seasonal effects to methane pathways in Arctic saline influenced or freshwater systems is critical to anticipate permafrost carbon feedbacks in course of global warming.

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.

Permafrost is a sensitive element of the cryosphere, but operational monitoring of the ground thermal conditions on large spatial scales is still lacking. Here, we demonstrate a remote-sensing-based scheme that is capable of estimating the transient evolution of ground temperatures and active layer thickness by means of the ground thermal model CryoGrid 2. The scheme is applied to an area of approximately 16 000 km2 in the Lena River delta (LRD) in NE Siberia for a period of 14 years. The forcing data sets at 1 km spatial and weekly temporal resolution are synthesized from satellite products and fields of meteorological variables from the ERA-Interim reanalysis. To assign spatially distributed ground thermal properties, a stratigraphic classification based on geomorphological observations and mapping is constructed, which accounts for the large-scale patterns of sediment types, ground ice and surface properties in the Lena River delta. A comparison of the model forcing to in situ measurements on Samoylov Island in the southern part of the study area yields an acceptable agreement for the purpose of ground thermal modeling, for surface temperature, snow depth, and timing of the onset and termination of the winter snow cover. The model results are compared to observations of ground temperatures and thaw depths at nine sites in the Lena River delta, suggesting that thaw depths are in most cases reproduced to within 0.1 m or less and multi-year averages of ground temperatures within 1–2 °C. Comparison of monthly average temperatures at depths of 2–3 m in five boreholes yielded an RMSE of 1.1 °C and a bias of −0.9 °C for the model results. The highest ground temperatures are calculated for grid cells close to the main river channels in the south as well as areas with sandy sediments and low organic and ice contents in the central delta, where also the largest thaw depths occur. On the other hand, the lowest temperatures are modeled for the eastern part, which is an area with low surface temperatures and snow depths. The lowest thaw depths are modeled for Yedoma permafrost featuring very high ground ice and soil organic contents in the southern parts of the delta. The comparison to in situ observations indicates that transient ground temperature modeling forced by remote-sensing data is generally capable of estimating the thermal state of permafrost (TSP) and its time evolution in the Lena River delta. The approach could hence be a first step towards remote detection of ground thermal conditions and active layer thickness in permafrost areas.

A simple analytical equation for the snow albedo as the function of snow grain size, soot concentration, and soot mass absorption coefficient is presented. This simple equation can be used in climate models to assess the influence of snow pollution on snow albedo. It is shown that the squared logarithm of the albedo (in the visible) is directly proportional to the soot concentration. A new method of the determination of the soot mass absorption coefficient in snow is proposed. The equations derived are applied to a dusty snow layer as well.

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.

Combined records of snow accumulation rate, δ18O and deuterium excess were produced from several shallow ice cores and snow pits at NEEM (North Greenland Eemian Ice Drilling), covering the period from 1724 to 2007. They are used to investigate recent climate variability and characterise the isotope–temperature relationship. We find that NEEM records are only weakly affected by inter-annual changes in the North Atlantic Oscillation. Decadal δ18O and accumulation variability is related to North Atlantic sea surface temperature and is enhanced at the beginning of the 19th century. No long-term trend is observed in the accumulation record. By contrast, NEEM δ18O shows multidecadal increasing trends in the late 19th century and since the 1980s. The strongest annual positive δ18O values are recorded at NEEM in 1928 and 2010, while maximum accumulation occurs in 1933. The last decade is the most enriched in δ18O (warmest), while the 11-year periods with the strongest depletion (coldest) are depicted at NEEM in 1815–1825 and 1836–1846, which are also the driest 11-year periods. The NEEM accumulation and δ18O records are strongly correlated with outputs from atmospheric models, nudged to atmospheric reanalyses. Best performance is observed for ERA reanalyses. Gridded temperature reconstructions, instrumental data and model outputs at NEEM are used to estimate the multidecadal accumulation–temperature and δ18O–temperature relationships for the strong warming period in 1979–2007. The accumulation sensitivity to temperature is estimated at 11 ± 2 % °C−1 and the δ18O–temperature slope at 1.1 ± 0.2 ‰ °C−1, about twice as large as previously used to estimate last interglacial temperature change from the bottom part of the NEEM deep ice core.