[1] High-resolution density profiles of 16 firn cores from Greenland and Antarctica are investigated in order to improve our understanding of the densification of layered polar firn. A vertical resolution of 1-5 mm enables us to study the detailed densification processes and the evolution of the layering and the resulting variability in density with increasing depth. The densification of layered firn is important for the process of air enclosure in ice and is connected with the observed formation of a nondiffusive zone. Our findings show the following. (1) Mean density profiles, obtained from high-resolution measurements, only partly show clear transitions in densification rate at densities of 550, 730, or 820-840 kg/m 3 , as they are commonly used in literature. (2) The density variability, induced by the layering, shows a similar pattern at all sites: high variabilities at the surface, a rapid drop to a relative minimum in variability at mean density of 600-650 kg/m 3 , followed by a second relative maximum. (3) This leads to increased variability at densities of the firn-ice transition for most of the sites. (4) The variability at the surface decreases with increasing mean annual temperature and accumulation rate, whereas the variability at the firn-ice transition increases. We can exclude a change in local climate conditions as an explanation for the density variability since the firn cores in this study cover a broad range in mean annual temperature, accumulation rate, and age. Overall, high-resolution density profiles deliver a more complex picture of compaction of polar firn as a layered granular medium than has been obtained from mean density profiles in the past.

Editor: P. DeMenocalKeywords: polar firn density densification impurity density variability Understanding polar firn densification is crucial for reconstructing the age of greenhouse gas concentrations extracted from ice cores, and for the interpretation of air in ice as a dating tool or as a climate proxy. Firn densification is generally modeled as a steady burial and sintering process of defined layers, where the structure of the layering is maintained along the whole firn and ice column. However, available high-resolution density data, as well as firn air samples, question this picture and point to a lack of understanding of firn densification. Based on analysis of high-resolution density and calcium concentration records from Antarctic and Greenland ice cores, we show for the first time that also impurities may have a significant impact on the densification. Analysis of firn cores shows a correlation between density and the calcium ion (Ca++) concentration, and this correlation increases with depth. The existence of this relationship is independent of the local climatic conditions at the core sites analyzed. The strong positive correlation between the density and the logarithm of Ca++ concentration indicates that impurities induce softening and lead to faster densification over a wide range of concentrations. In one core, the impurity effect manifests itself so strongly that the density develops a seasonal cycle closely following the seasonal cycle of Ca++. Our results clearly show that the structure of the firn layering changes with depth and suggest that the increased variability in density observed in deep firn, recently described as a universal feature of polar firn, may arise from the influence of Ca++ and/or other impurities. The impurity effect is likely to have direct implications on our understanding of glacial firn densification and on glacial gas age estimates.

The Sentinel Application Platform (SNAP) architecture facilitates Earth Observation data processing. In this work, we present results from a new Snow Processor for SNAP. We also describe physical principles behind the developed snow property retrieval technique based on the analysis of Ocean and Land Colour Instrument (OLCI) onboard Sentinel-3A/B measurements over clean and polluted snow fields. Using OLCI spectral reflectance measurements in the range 400–1020 nm, we derived important snow properties such as spectral and broadband albedo, snow specific surface area, snow extent and grain size on a spatial grid of 300 m. The algorithm also incorporated cloud screening and atmospheric correction procedures over snow surfaces. We present validation results using ground measurements from Antarctica, the Greenland ice sheet and the French Alps. We find the spectral albedo retrieved with accuracy of better than 3% on average, making our retrievals sufficient for a variety of applications. Broadband albedo is retrieved with the average accuracy of about 5% over snow. Therefore, the uncertainties of satellite retrievals are close to experimental errors of ground measurements. The retrieved surface grain size shows good agreement with ground observations. Snow specific surface area observations are also consistent with our OLCI retrievals. We present snow albedo and grain size mapping over the inland ice sheet of Greenland for areas including dry snow, melted/melting snow and impurity rich bare ice. The algorithm can be applied to OLCI Sentinel-3 measurements providing an opportunity for creation of long-term snow property records essential for climate monitoring and data assimilation studies—especially in the Arctic region, where we face rapid environmental changes including reduction of snow/ice extent and, therefore, planetary albedo.

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Several recent studies from both Greenland and Antarctica have reported significant changes in the water isotopic composition of near‐surface snow between precipitation events. These changes have been linked to isotopic exchange with atmospheric water vapor and sublimation‐induced fractionation, but the processes are poorly constrained by observations. Understanding and quantifying these processes are crucial to both the interpretation of ice core climate proxies and the formulation of isotope‐enabled general circulation models. Here, we present continuous measurements of the water isotopic composition in surface snow and atmospheric vapor together with near‐surface atmospheric turbulence and snow‐air latent and sensible heat fluxes, obtained at the East Greenland Ice‐Core Project drilling site in summer 2016. For two 4‐day‐long time periods, significant diurnal variations in atmospheric water isotopologues are observed. A model is developed to explore the impact of this variability on the surface snow isotopic composition. Our model suggests that the snow isotopic composition in the upper subcentimeter of the snow exhibits a diurnal variation with amplitudes in δ 18 O and δD of ~2.5‰ and ~13‰, respectively. As comparison, such changes correspond to 10–20% of the magnitude of seasonal changes in interior Greenland snow pack isotopes and of the change across a glacial‐interglacial transition. Importantly, our observation and model results suggest, that sublimation‐induced fractionation needs to be included in simulations of exchanges between the vapor and the snow surface on diurnal timescales during summer cloud‐free conditions in northeast Greenland.