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In many settings, data acquisition generates outliers that can obscure inference. Therefore, practitioners often either identify and remove outliers or accommodate outliers using robust models. However, identifying and removing outliers is often an ad hoc process that affects inference, and robust methods are often too simple for some applications. In our motivating application, scientists drill snow cores and measure snow density to infer densification rates that aid in estimating snow water accumulation rates and glacier mass balances. Advanced measurement techniques can measure density at high resolution over depth but are sensitive to core imperfections, making them prone to outliers. Outlier accommodation is challenging in this setting because the distribution of outliers evolves over depth and the data demonstrate natural heteroscedasticity. To address these challenges, we present a two-component mixture model using a physically motivated snow density model and an outlier model, both of which evolve over depth. The physical component of the mixture model has a mean function with normally distributed depth-dependent heteroscedastic errors. The outlier component is specified using a semiparametric prior density process constructed through a normalized process convolution of log-normal random variables. We demonstrate that this model outperforms alternatives and can be used for various inferential tasks.

NASA's Ice, Cloud, and land Elevation Satellite‐2 (ICESat‐2) laser altimeter launched in Fall 2018, providing an invaluable addition to the polar altimetry record generated by ESA's CryoSat‐2 radar altimeter. The simultaneous operation of these two satellite altimeters enables unique comparison studies of sea ice altimetry, utilizing the different frequencies and profiling strategies of the two instruments. Here, we use freeboard data from ICESat‐2 to assess Antarctic snow freeboard retrievals from CryoSat‐2. We first discuss updates made to a previously published CryoSat‐2 retrieval process and show how this Version 2 algorithm improves upon the original method by comparing the new retrievals to ICESat‐2 in specific along‐track profiles as well as on the basin‐scale. In two near‐coincident along‐track profiles, we find mean snow freeboard differences (standard deviations of differences) of 0.3 (9.3) and 7.6 cm (9.6 cm) with 25 km binned correlation coefficients of 0.77 and 0.89. Monthly mean freeboard differences range between −2.9 (10.8) and 6.6 cm (16.8 cm) basin wide, with the largest differences typically occurring in Austral fall months that is hypothesized to be related to new ice growth and the use of static snow backscatter coefficients in the retrieval. Monthly mean correlation coefficients range between 0.57 and 0.80. While coincident data show good agreement between the two sensors, they highlight issues related to geometric and frequency sampling differences that can impact the freeboard distributions.

Precise Antarctic snow accumulation estimates are needed to understand past and future changes in global sea levels, but standard reconstructions using water isotopes suffer from competing isotopic effects external to accumulation. We present here an alternative accumulation proxy based on the post-depositional photolytic fractionation of nitrogen isotopes (d15N) in nitrate. On the high plateau of East Antarctica, sunlight penetrating the uppermost snow layers converts snow-borne nitrate into nitrogen oxide gas that can be lost to the atmosphere. This nitrate loss favors 14NO3- over 15NO3-, and thus the d15N of nitrate remaining in the snow will steadily increase until the nitrate is eventually buried beneath the reach of light. Because the duration of time until burial is dependent upon the rate of net snow accumulation, sites with lower accumulation rates have a longer burial wait and thus higher d15N values. A linear relationship (r2 = 0.86) between d15N and net accumulation-1 is calculated from over 120 samples representing 105 sites spanning East Antarctica. These sites largely encompass the full range of snow accumulation rates observed in East Antarctica, from 25 kg m-2 yr-1 at deep interior sites to >400 kg m-2 yr-1 at near coastal sites. We apply this relationship as a transfer function to an Aurora Basin ice core to produce a 700-year record of accumulation changes. Our nitrate-based estimate compares very well with a parallel reconstruction for Aurora Basin that uses volcanic horizons and ice-penetrating radar. Continued improvements to our database may enable precise independent estimates of millennial-scale accumulation changes using deep ice cores such as EPICA Dome C and Beyond EPICA-Oldest Ice.

Estimates of snow and firn density are required for satellite altimetry based retrievals of ice sheet mass balance that rely on volume to mass conversions. Therefore, biases and errors in presently used density models confound assessments of ice sheet mass balance, and by extension, ice sheet contribution to sea level rise. Despite this importance, most contemporary firn densification models rely on simplified semi-empirical methods, which are partially reflected by significant modeled density errors when compared to observations. In this study, we present a new, wind-driven, drifting snow compaction scheme that we have implemented into SNOWPACK, a physics-based land surface snow model. We demonstrate high-quality simulation of near-surface Antarctic snow firn density at 122 observed density profiles across the Antarctic ice sheet, as indicated by reduced model biases throughout most of the near-surface firn column when compared to two semi-empirical firn densification models. Because SNOWPACK is physics-based, its performance does not degrade when applied to sites without observations used in the calibration of semi-empirical models, and could therefore better represent firn properties in locations without extensive observations and under future climate scenarios, in which firn properties are expected to diverge from their present state.

Interstellar dust and gas that enter the heliosphere provide us with important clues about both the heliosphere and the local interstellar medium (LISM). The picture we have of the Local Interstellar Cloud (LIC) from both \emph{in situ} detections and absorption line data presents questions that have important implications for the origins and evolution of the cloud. New detections of $^{60}$Fe on Earth in deep sea crusts and Antarctic snow cores provide evidence for the role of supernovae in shaping the LISM. We discuss our models for the evolution of the LIC inside the Local Bubble and possible explanations for the source of the supernova produced dust., Comment: 9 pages, 7 figures, contribution to the proceedings of the 19th Annual International Astrophysics Conference "From the Sun's Atmosphere to the Edge of the Galaxy: A Story of Connections" to be published in the Journal of Physics Conference Series

A new procedure for the determination of Al, Ba, Ca, Fe, K, Mg, Na and Sr in snow samples by inductively coupled plasma optical emission spectrometry (ICP-OES) has been developed. The analytes were 100-fold preconcentrated by sample volume reduction and quantified by ICP-OES using the heated torch-integrated sample introduction system (hTISIS). After multivariate optimization of the hTISIS/ICP-OES operating parameters for maximum sensitivity and plasma robustness, fit-for-purpose performances were achieved, requiring only 20 mL of sample (as water equivalent). The analytical recovery was quantitative (except for Ba at low concentration, ≈80%) and the precision of the procedure was better than 5%. The limits of detection (Al: 0.10 ng g−1; Ba: 0.013 ng g−1; Ca: 0.52 ng g−1; Fe: 0.13 ng g−1; K: 0.38 ng g−1; Mg: 0.04 ng g−1; Na: 0.39 ng g−1; Sr: 0.003 ng g−1) were suitable for the analysis of Antarctic snow, with some limitation for Ba. The accuracy of the method was assessed by the analysis of the certified reference water NIST SRM 1640a. The application of the analytical method to sixty snow samples collected at Dome C, on the East Antarctic Plateau, provided self-consistent results, in good agreement with literature data.

Microwave radiometer SSM/I (Special Sensor Microwave Imager) data and scatterometer QuikSCAT (Quick Scatterometer) data have been widely used for near-surface snow melt detection based on their sensitivity to liquid water present in snow. The SSM/I data have high reliability and the QuikSCAT data have high spatial resolution. In order to improve the accuracy of Antarctic near-surface snow melt detection, we propose a new method based on the synergy of SSM/I and QuikSCAT data, i.e. the snow melt physical model incorporates the complementary advantages of both datasets. Based on comparisons with temperature data from three automatic weather stations, the proposed algorithm improved the accuracy of snow melt detection. The algorithm could also be applied to other regions, which would provide further evidence to support its use and additional data to document changes in the Antarctic due to global climate change.

Estimates of snow and firn density are required for satellite-altimetry-based retrievals of ice sheet mass balance that rely on volume-to-mass conversions. Therefore, biases and errors in presently used density models confound assessments of ice sheet mass balance and by extension ice sheet contribution to sea level rise. Despite this importance, most contemporary firn densification models rely on simplified semi-empirical methods, which are partially reflected by significant modeled density errors when compared to observations. In this study, we present a new drifting-snow compaction scheme that we have implemented into SNOWPACK, a physics-based land surface snow model. We show that our new scheme improves existing versions of SNOWPACK by increasing simulated near-surface (defined as the top 10 m) density to be more in line with observations (near-surface bias reduction from −44.9 to −5.4 kg m−3). Furthermore, we demonstrate high-quality simulation of near-surface Antarctic snow and firn density at 122 observed density profiles across the Antarctic ice sheet, as indicated by reduced model biases throughout most of the near-surface firn column when compared to two semi-empirical firn densification models (SNOWPACK mean bias=-9.7 kg m−3, IMAU-FDM mean bias=-32.5 kg m−3, GSFC-FDM mean bias=15.5 kg m−3). Notably, our analysis is restricted to the near surface where firn density is most variable due to accumulation and compaction variability driven by synoptic weather and seasonal climate variability. Additionally, the GSFC-FDM exhibits lower mean density bias from 7–10 m (SNOWPACK bias=-22.5 kg m−3, GSFC-FDM bias=10.6 kg m−3) and throughout the entire near surface at high-accumulation sites (SNOWPACK bias=-31.4 kg m−3, GSFC-FDM bias=-4.7 kg m−3). However, we found that the performance of SNOWPACK did not degrade when applied to sites that were not included in the calibration of semi-empirical models. This suggests that SNOWPACK may possibly better represent firn properties in locations without extensive observations and under future climate scenarios, when firn properties are expected to diverge from their present state.

The oceanic scale occurrences of typical neutral poly/per-fluoroalkyl substances (PFASs) in the atmosphere across the Atlantic, as well as their air-snow exchange at the Antarctic Peninsula, were investigated. Total concentrations of the 12 PFASs (∑PFASs) in gas phase ranged from 2.8 to 68.8 pg m(-3) (mean: 23.5 pg m(-3)), and the levels in snow were from 125 to 303 pg L(-1) (mean: 209 pg L(-1)). Fluorotelomer alcohols (FTOHs) were dominant in both air and snow. The differences of specific compounds to ∑PFASs were not significant between air and snow. ∑PFASs were higher above the northern Atlantic compared to the southern Atlantic, and the levels above the southern Atlantic

Snow consists of non-spherical grains of various shapes and sizes. Still, in radiative transfer calculations, snow grains are often treated as spherical. This also applies to the computation of snow albedo in the Snow, Ice, and Aerosol Radiation (SNICAR) model and in the Los Alamos sea ice model, version 4 (CICE4), both of which are employed in the Community Earth System Model and in the Norwegian Earth System Model (NorESM). In this study, we evaluate the effect of snow grain shape on climate simulated by NorESM in a slab ocean configuration of the model. An experiment with spherical snow grains (SPH) is compared with another (NONSPH) in which the snow shortwave single-scattering properties are based on a combination of three non-spherical snow grain shapes optimized using measurements of angular scattering by blowing snow. The key difference between these treatments is that the asymmetry parameter is smaller in the non-spherical case (0.77–0.78 in the visible region) than in the spherical case ( ≈ 0.89). Therefore, for the same effective snow grain size (or equivalently, the same specific projected area), the snow broadband albedo is higher when assuming non-spherical rather than spherical snow grains, typically by 0.02–0.03. Considering the spherical case as the baseline, this results in an instantaneous negative change in net shortwave radiation with a global-mean top-of-the-model value of ca. −0.22 W m−2. Although this global-mean radiative effect is rather modest, the impacts on the climate simulated by NorESM are substantial. The global annual-mean 2 m air temperature in NONSPH is 1.17 K lower than in SPH, with substantially larger differences at high latitudes. The climatic response is amplified by strong snow and sea ice feedbacks. It is further demonstrated that the effect of snow grain shape could be largely offset by adjusting the snow grain size. When assuming non-spherical snow grains with the parameterized grain size increased by ca. 70 %, the climatic differences to the SPH experiment become very small. Finally, the impact of assumed snow grain shape on the radiative effects of absorbing aerosols in snow is discussed.

In this study, the concentrations of total mercury (THg) and ions deposited in the surface snow and snow pits in the eastern Antarctic along the 29th inland route of the Chinese National Antarctic Research Expedition were analysed. The THg concentrations in the surface snow ranged from 0.22 to 8.29 ng/L and elevated concentrations were detected in the inland regions of higher altitudes (3000–4000 m). The spatial distribution of the THg in the snow pits showed greater inland concentrations with mean concentrations of

A rare radioactive iron isotope produced by exploding stars has been detected in Antarctic snow.

Measuring the mercury content in shallow Antarctic snow pits is useful for understanding the mercury dynamics of the Antarctic Plateau and the global mercury cycle and for interpreting ice core data. We determined the total mercury concentration (HgT) in snow samples successively collected at 5 cm intervals from two 4m deep snow pits at Dome Fuji. The measured mercury concentration varied between 0.32 (the detection limit) and 2.93 pg g−1 (n = 160) with depth and was lower than that of summertime surface snow that was sampled simultaneously. This finding is consistent with previous observations that a bidirectional exchange of mercury between the snowpack and the atmosphere led to an increase in HgT in the surface snow during the summer. However, the contribution of the air-snow Hg exchange to the net Hg sequestration was offset by the intense re-emission of deposited mercury over the past ∼50 years. Our results demonstrate that the Antarctic Plateau snowpack is a temporary reservoir of mercury rather than a permanent sink.

Well-defined variations in the enrichments and isotopic compositions of Pb have been observed in snow from Dome Fuji and Dome A in the central East Antarctic Plateau (EAP) over the past few decades. The Pb isotopic fingerprints indicate that the rapid increase in Pb enrichments from the mid-1970s, reaching a peak in ∼1980, is due to the massive use of leaded gasoline in northern South America, especially Brazil. Since then, they show a continuous decline, mostly due to the significant removal of the Pb additives from gasoline in Brazil in the 1980s and, subsequently, in Argentina and Chile in the 1990s. After the phase-out of Pb in gasoline, Cu smelting in Chile has become the major source of Pb, contributing ∼90% to the total Pb emissions in northern South America in 2005. Nevertheless, Pb pollution in the central EAP declined substantially until recently as a result of the regulatory efforts to curb toxic trace metal emissions from the Cu industry in Chile. However, more than 90% of the Pb in the most remote places on Earth are still of anthropogenic origin, highlighting the need for the continuation of environmental regulations for the further reduction of Pb emissions.

In this paper we studied some heavy metals (Cu, Zn, Cd, Pb, As, U) probably associated to high molecular weight organic compounds present in the Antarctic snow. Snow-pit samples were collected and analysed for high molecular weight fraction and heavy metals bound to them by means of ultrafiltration treatment. High molecular weight dissolved organic matter (HMW-DOM) recovered by ultrafiltration showed a dissolved organic carbon concentration (HMW-DOC) of about 18–83% of the total dissolved organic carbon measured in Antarctic snow. The characterisation of HMW-DOM fraction evidenced an ageing of organic compounds going from surface layers to the deepest ones with a shift from aliphatic compounds and proteins/amino sugars to more high unsaturated character and less nitrogen content. The heavy metals associated to HMW-DOM fraction follows the order: Zn > Cu > Pb >> Cd ∼ As ∼ U. The percentage fraction of metals bound to HMW-DOM respect to total metal content follows the order: Cu >> Pb > Zn, Cd in agreement with humic substance binding ability (Irwing-William series). Going down to depth of trench, all metals except arsenic, showed a high concentration peak corresponding to 2.0–2.5 m layer. This result was attributed to particular structural characteristic of organic matter able to form different type of complexes (1:1, 1:2, 1:n) with metals. © 2017 Elsevier Ltd

We performed TOF-SIMS analyses of one UCAMM to investigate pristine organic matter and to determine if UCAMMs are representative of cometary CHON grains.

Organic carbon records in Antarctic snow are sparse despite the fact that it is of great significance to global carbon dynamics, snow photochemistry, and air-snow exchange processes. Here, surface snow total organic carbon (TOC) along with sea-salt Na(+), dust, and microbial load of two geographically distinct traverses in East Antarctica are presented, viz. Princess Elizabeth Land (PEL, coast to 180 km inland, Indian Ocean sector) and Dronning Maud Land (DML, ∼110-300 km inland, Atlantic Ocean sector). TOC ranged from 88 ± 4 to 928 ± 21 μg L(-1) in PEL and 13 ± 1 to 345 ± 6 μg L(-1) in DML. TOC exhibited considerable spatial variation with significantly higher values in the coastal samples (p0.001), but regional variation was insignificant within the two transects beyond 100 km (p0.1). Both distance from the sea and elevation influenced TOC concentrations. TOC also showed a strong positive correlation with sea-salt Na(+) (p0.001). In addition to marine contribution, in situ microorganisms accounted for 365 and 320 ng carbon L(-1) in PEL and DML, respectively. Correlation with dust suggests that crustal contribution of organic carbon was marginal. Though TOC was predominantly influenced by marine sources associated with sea-spray aerosols, local microbial contributions were significant in distant locations having minimal sea-spray input.

Antarctic snow preserves an atmospheric archive that enables the study of global atmospheric changes and anthropogenic disturbances from the past. We report atmospheric deposition rates of platinum group elements (PGEs) in Antarctica during the last ∼ 50 years based on determinations of Pt, Ir, and Rh in snow samples collected from Queen Maud Land, East Antarctica to evaluate changes in the global atmospheric budget of these noble metals. The 50-year average PGE concentrations in Antarctic snow were 17 fg g(-1) (4.7-76 fg g(-1)) for Pt, 0.12 fg g(-1) (0.05-0.34 fg g(-1)) for Ir, and 0.71 fg g(-1) (0.12-8.8 fg g(-1)) for Rh. The concentration peaks for Pt, Ir, and Rh were observed at depths corresponding to volcanic eruption periods, indicating that PGEs can be used as a good tracer of volcanic activity in the past. A significant increase in concentrations and crustal enrichment factors for Pt and a slight enhancement in enrichment factors for Rh were observed after the 1980s. This suggests that there has been large-scale atmospheric pollution for Pt and probably for Rh since the 1980s, which may be attributed to the increasing emissions of these metals from anthropogenic sources such as automobile catalysts and metal production processes.

Interannual ice-mass variations along the Antarctic Peninsula (AP) and in the Amundsen Sea Sector (AS) are obtained for the years 2002 until 2009 using satellite data of the Gravity Recovery and Climate Experiment, that correlate well (r ≈ 0.7) with accumulation variations based on the net precipitation from the European Centre for Medium Range Weather Forecasts. Moreover, mass signals for AP and AS are anti-correlated in time (r ≈ − 0.4) and contain El Nino Southern Oscillation signatures related to the strength of the Amundsen Sea Low pressure system, that has a dominant influence on West Antarctic atmospheric moisture transports. The GRACE interannual mass variations exhibit root-mean squared amplitudes of: 16.4 ± 4.1 Gt (AP) and 28.6 ± 10.5 Gt (AS), which are significant compared to the mean annual mass loss of − 110.2 ± 6.7 Gt/a in coastal West Antarctica.

We recovered micrometeorites from surface snow layers near the French-Italian station CONCORDIA. The unique weather and isolation conditions of Dome C allowed us to recover micrometeorites that are much better preserved than those extracted from blue ice fields. We have identified a new population of friable fine-grained micrometeorites; the absence of such particles in previous collections can be explained by their destruction by mechanical processes. In contrast to previous collections of micrometeorites, the particles from CONCORDIA Collection are characterized by a high content of Fe-sulfides and an undepleted CI elemental abundance pattern of their fine-grained matrix. These features suggest that micrometeorites from Dome C snow have endured much lower alteration from terrestrial weathering, unlike the micrometeorites recovered from near the margin of the Antarctic ice sheet (Adelie Land). The CONCORDIA particles have well constrained terrestrial ages and, given the low Dome C precipitation rate, the central regions of Antarctica provide a unique opportunity to search for particles from historical meteor showers.