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Understanding the microscopic variability of impurities in glacier ice on a quantitative level has importance for assessing the preservation of paleoclimatic signals and enables the study of macroscopic deformational as well as dielectric ice properties. Two‐dimensional imaging via laser‐ablation‐inductively‐coupled‐plasma‐mass‐spectrometry (LA‐ICP‐MS) can provide key insight into the localization of impurities in the ice. So far, these findings are mostly qualitative and gaining quantitative insights remains challenging. Recent advances in LA‐ICP‐MS high‐resolution imaging now allow ice grains and grain boundaries to be resolved individually. These resolutions require new adequate quantification strategies and, consequently, accurate calibration with matrix‐matched standards. Here, we present three different quantification methods, which provide a high level of homogeneity at the scale of a few tens of microns and are dedicated to imaging applications of ice cores. One of the proposed methods has a second application, offering laboratory experiments to investigate the displacement of impurities by grain growth, with important future potential to study ice‐impurity interactions. Standards were analyzed to enable absolute quantification of impurities in selected ice core samples. Calibrated LA‐ICP‐MS maps indicate similar spatial distributions of impurities in all samples, while impurity levels vary distinctly: Higher concentrations were detected in glacial periods and Greenland, and lower levels in interglacial periods and samples from central Antarctica. These results are consistent with ranges from complementary meltwater analysis. Further comparison with cm‐scale melting techniques calls for a more sophisticated understanding of the ice chemistry across spatial scales, to which calibrated LA‐ICP‐MS maps now contribute quantitatively. Plain Language Summary Compared to the large amount of information relating to paleoclimate signals reconstructed from cm‐scale impurity measurements on ice cores, knowledge about the spatial variability of impurities at the micro‐scale is extremely sparse—and becomes even more rare once quantitative datasets are concerned. However, there is an increasing demand for quantitative data for assessing the preservation of paleoclimatic signals and for the study of macroscopic deformational as well as dielectric ice properties in ice flow modeling and remote sensing. Two‐dimensional imaging via laser‐ablation‐inductively‐coupled‐plasma‐mass‐spectrometry (LA‐ICP‐MS) has shown great potential in this context, but so far, gaining reliable quantitative results for micro‐scale imaging has not been possible. Here, we present new quantification strategies that finally allow accurate calibration using ice standards. We carefully discuss the pros and cons of each method, apply the calibration to different samples from Greenland and Antarctica, and deliver the first calibrated LA‐ICP‐MS impurity maps at 40 μm resolution. Our results are consistent with bulk measurements performed on melted samples. The calibrated LA‐ICP‐MS maps will be essential for further comparison with bulk meltwater analysis, which may ultimately deliver an improved understanding of paleoclimate signals stored in deep ice. Key Points This study presents new quantification strategies for two‐dimensional micro‐scale impurity imaging on ice cores with laser‐ablation‐inductively‐coupled‐plasma‐mass‐spectrometry (LA‐ICP‐MS) Calibrated LA‐ICP‐MS maps reveal similar spatial distributions of impurities in all ice core samples, while concentrations vary distinctly We developed a method to investigate the displacement of impurities by grain growth and to study ice‐impurity interactions in the laboratory

Surface processes alter the water stable isotope signal of the surface snow after deposition. However, it remains an open question to which extent surface post‐depositional processes should be considered when inferring past climate information from ice core records. Here, we present simulations for the Greenland Ice Sheet, combining outputs from two climate models with an isotope‐enabled snowpack model. We show that surface vapor exchange and associated fractionation imprint a climate signal into the firn, resulting in an increase in the annual mean value of δ18O by +2.3‰ and a reduction in d‐excess by −6.3‰. Further, implementing isotopic fractionation during surface vapor exchange improves the representation of the observed seasonal amplitude in δ18O from 65.0% to 100.2%. Our results stress that surface vapor exchange is important in the climate proxy signal formation and needs consideration when interpreting ice core climate records. Plain Language Summary The climate information contained in falling snow is modified by exchange processes with the atmosphere after the snow has fallen to the surface. It is important to understand how this modification affects the interpretation of past climate information from ice core isotope records. In this study, we combined outputs from two climate models to simulate the climate signal in a snow core on the Greenland Ice Sheet. We evaluate the snow core model using snow observations from the Greenland Ice Sheet. By simulating snow cores with and without the modification at the surface, we find a considerable impact of the surface modification on the climate signal in the snow core. Further, considering the surface modification causes an improved representation of the seasonal changes compared to observations. Our findings highlight the importance of surface processes in forming climate information contained in ice cores and underscore the need to include these processes in the ice core interpretation. Key Points Water isotopic fractionation during vapor exchange significantly affects the simulated annual and seasonal isotope climate signal in ice cores The simulated seasonal amplitude of the δ18O signal in the snowpack improves when including surface vapor exchange induced fractionation A phase shift in the simulated seasonal maximum in d‐excess toward early autumn is induced by vapor exchange, consistent with observations

Ice rises hold valuable records revealing the ice dynamics and climatic history of Antarctic coastal areas from the Last Glacial Maximum to today. This history is often reconstructed from isochrone radar stratigraphy and simulations focusing on Raymond arch evolution beneath the divides. However, this relies on complex ice-flow models where many parameters are unconstrained by observations. Our study explores quad-polarimetric, phase-coherent radar data to enhance understanding near ice divides and domes, using Hammarryggen Ice Rise (HIR) as a case study. Analysing a 5 km profile intersecting the dome, we derive vertical strain rates and ice-fabric properties. These align with ice core data near the summit, increasing confidence in tracing signatures from the dome to the flanks. The Raymond effect is evident, correlating with surface strain rates and radar stratigraphy. Stability is inferred over millennia for the saddle connecting HIR to the mainland, but dome ice-fabric appears relatively young compared to 2D model predictions. In a broader context, quad-polarimetric measurements provide valuable insights into ice-flow models, particularly for anisotropic rheology. Including quad-polarimetric data advances our ability to reconstruct past ice flow dynamics and climatic history in ice rises.

Firn simulations are essential for understanding Antarctic ice sheet mass change, as they enable us to convert satellite altimetry observed volume changes to mass changes and column thickness to ice thickness and to quantify the meltwater buffering capacity of firn. Here, we present and evaluate a simulation of the contemporary Antarctic firn layer using the updated semi-empirical IMAU Firn Densification Model (IMAU-FDM) for the period 1979–2020. We have improved previous fresh-snow density and firn compaction parameterizations and used updated atmospheric forcing. In addition, the model has been calibrated and evaluated using 112 firn core density observations across the ice sheet. We found that 62 % of the seasonal and 67 % of the decadal surface height variability are due to variations in firn air content rather than firn mass. Comparison of simulated surface elevation change with a previously published multi-mission altimetry product for the period 2003–2015 shows that performance of the updated model has improved, notably in Dronning Maud Land and Wilkes Land. However, a substantial trend difference (>10 cm yr−1) remains in the Antarctic Peninsula and Ellsworth Land, mainly caused by uncertainties in the spin-up forcing. By estimating previous climatic conditions from ice core data, these trend differences can be reduced by 38 %.

Atmospheric greenhouse gas (GHG) concentrations are at unprecedented, record-high levels compared to the last 800 000 years. Those elevated GHG concentrations warm the planet and – partially offset by net cooling effects by aerosols – are largely responsible for the observed warming over the past 150 years. An accurate representation of GHG concentrations is hence important to understand and model recent climate change. So far, community efforts to create composite datasets of GHG concentrations with seasonal and latitudinal information have focused on marine boundary layer conditions and recent trends since the 1980s. Here, we provide consolidated datasets of historical atmospheric concentrations (mole fractions) of 43 GHGs to be used in the Climate Model Intercomparison Project – Phase 6 (CMIP6) experiments. The presented datasets are based on AGAGE and NOAA networks, firn and ice core data, and archived air data, and a large set of published studies. In contrast to previous intercomparisons, the new datasets are latitudinally resolved and include seasonality. We focus on the period 1850–2014 for historical CMIP6 runs, but data are also provided for the last 2000 years. We provide consolidated datasets in various spatiotemporal resolutions for carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O), as well as 40 other GHGs, namely 17 ozone-depleting substances, 11 hydrofluorocarbons (HFCs), 9 perfluorocarbons (PFCs), sulfur hexafluoride (SF6), nitrogen trifluoride (NF3) and sulfuryl fluoride (SO2F2). In addition, we provide three equivalence species that aggregate concentrations of GHGs other than CO2, CH4 and N2O, weighted by their radiative forcing efficiencies. For the year 1850, which is used for pre-industrial control runs, we estimate annual global-mean surface concentrations of CO2 at 284.3 ppm, CH4 at 808.2 ppb and N2O at 273.0 ppb. The data are available at https://esgf-node.llnl.gov/search/input4mips/ and http://www.climatecollege.unimelb.edu.au/cmip6 . While the minimum CMIP6 recommendation is to use the global- and annual-mean time series, modelling groups can also choose our monthly and latitudinally resolved concentrations, which imply a stronger radiative forcing in the Northern Hemisphere winter (due to the latitudinal gradient and seasonality).

Global warming has caused widespread surface lowering of mountain glaciers. By comparing two firn cores collected in 2018 and 2020 from Corbassière glacier in Switzerland, we demonstrate how vulnerable these precious archives of past environmental conditions have become. Within two years, the soluble impurity records were destroyed by melting. The glacier is now irrevocably lost as an archive for reconstructing major atmospheric aerosol components. Information on past environmental conditions stored within high-altitude glaciers is being lost due to accelerated melting associated with climate change, according to ice core analysis from a Swiss glacier.

Antarctic ice cores can help determine ice mass loss from the Antarctic Ice Sheet (AIS) during past warm periods. We compile Last Interglacial (LIG) δ18O${\\delta }^{18}O$measurements from eight Antarctic cores and compare these to new isotope‐enabled LIG simulations, which explore three plausible LIG AIS elevation and extent scenarios. We find that these simulations capture less than 10% of East Antarctic core‐mean δ18O${\\delta }^{18}O$changes. Although our simulations do not fully explain the changes, they capture some inter‐core geographical δ18O${\\delta }^{18}O$variations. Some LIG AIS configurations show higher skill than PI AIS configurations in simulating the inter‐core differences. The remaining discrepancies between the simulated and observed core‐mean water isotope changes suggest that LIG simulations also need to include the influences of reduced Antarctic sea ice, a warmer Southern Ocean, and resultant shifts in vapor source regions to produce a more satisfactory match to δ18O${\\delta }^{18}O$observed at ice core sites. Plain Language Summary Reconstructions of Antarctic Ice Sheet (AIS) retreat during past warm periods provide important constraints for projections of future ice mass loss and sea level rise. The Last Interglacial (LIG) is a particularly useful example, when global temperatures were 1±1oC$\\pm {1}^{o}C$warmer than preindustrial (PI) conditions, to explore future sea level rise projections associated with the successful implementation of the Paris Agreement. Here, we use data from six East Antarctic ice cores and two new, unpublished records from West Antarctica that capture LIG conditions. Water isotopes in ice cores are sensitive to changes in temperature, AIS elevation, atmospheric circulation pattern, sea ice area, and ocean conditions. We compare model simulations of the LIG with ice core data and find that elevation changes, an important indicator of ice mass loss, explain only around 9% of the isotope change captured in East Antarctic ice cores. Due to the limitation of our simulations in the coastal regions, our West Antarctic coastal sites are more challenging. In summary, we find that while the range of our simulations does not fully explain average East Antarctic PI‐to‐LIG isotope changes, they do capture some of the geographical variations in isotope change patterns. Key Points A compilation of Last Interglacial δ18O${\\delta }^{18}O$ice core records shows anomalies of +${+}$ 1.5‰ and +${+}$ 3.3‰ for 127 kyr BP and LIG‐peak core‐mean Simulations run with plausible LIG Antarctic Ice Sheet (AIS)configurations, alongside greenhouse gas and orbital changes, capture <${< } $10% of core‐mean differences Two LIG AIS configurations yield lower geographical errors at 127 kyr, compared to their PI configurations

Efforts to extract a Greenland ice core with a complete record of the Eemian interglacial (130,000 to 115,000 years ago) have until now been unsuccessful. The response of the Greenland ice sheet to the warmer-than-present climate of the Eemian has thus remained unclear. Here we present the new North Greenland Eemian Ice Drilling (‘NEEM’) ice core and show only a modest ice-sheet response to the strong warming in the early Eemian. We reconstructed the Eemian record from folded ice using globally homogeneous parameters known from dated Greenland and Antarctic ice-core records. On the basis of water stable isotopes, NEEM surface temperatures after the onset of the Eemian (126,000 years ago) peaked at 8 ± 4 degrees Celsius above the mean of the past millennium, followed by a gradual cooling that was probably driven by the decreasing summer insolation. Between 128,000 and 122,000 years ago, the thickness of the northwest Greenland ice sheet decreased by 400 ± 250 metres, reaching surface elevations 122,000 years ago of 130 ± 300 metres lower than the present. Extensive surface melt occurred at the NEEM site during the Eemian, a phenomenon witnessed when melt layers formed again at NEEM during the exceptional heat of July 2012. With additional warming, surface melt might become more common in the future. Reconstruction of the Eemian interglacial from the new NEEM ice core shows that in spite of a climate warmer by eight degrees Celsius in Northern Greenland than that of the past millennium, the ice here was only a few hundred metres lower than its present level. A detailed record of Eemian climate The Greenland ice sheet is losing mass and contributing to ongoing sea level rise, but an incomplete understanding of its changes during the last interglacial 130,000–115,000 years ago, termed the Eemian, have hampered firm predictions. Now an international team has successfully reconstructed the Eemian climate record from the new NEEM ice core. The record shows that in spite of a climate 8 °C warmer than that of the past millennium, the thickness of the ice sheet decreased by only a few hundred metres. In addition, the ice core shows that there was significant surface melt in the north-central parts of the ice sheet during the Eemian, conditions we might soon see again, as demonstrated by melt layers formed at NEEM by the warm temperatures observed over Greenland in July 2012.

Peru hosts a significant portion of the world’s tropical glaciers, which are undergoing rapid mass loss due to climate change. Knowledge of the ice volume and bedrock topography of these glaciers is important for predicting changes in glacier dynamics, runoff, and interpreting ice-core records. This study presents results from glaciological and geophysical surveys conducted during a 2019 expedition to Nevado Huascarán, Peru’s highest mountain when four ice cores were extracted from the col and summit. Ground-penetrating radar measurements provided detailed ice thickness and snow accumulation data, highlighting complex internal glacier structure and indicated that the climatic records obtained from ice cores recovered in 2019 were continuous and extended past the Holocene. Ice flow modeling enabled investigation of glacier dynamics. It was shown that the upstream effect on ice-core record is minimal. Comparison with ice thickness modeling data for Huascarán from various sources revealed significant discrepancies with measured ice thicknesses, suggesting that the inversion methods underestimate ice thickness for the accumulation zones of mountain glaciers. This research contributes data for understanding glacier behavior in the context of climate change and for modeling efforts for better assessments of water resources, potential geohazards and paleoclimatic interpretations.