Snow Pit Research Articles

First discrete iron(II) records from Dome C (Antarctica) and the Holtedahlfonna glacier (Svalbard)

Fe(II) is more soluble and bioavailable than Fe(III) species, therefore the investigation of their relative abundance and redox processes is relevant to better assess the supply of bioavailable iron to the ocean and its impact on marine productivity. In this context, we present a discrete chemiluminescence-based method for the determination of Fe(II) in firn matrices. The method was applied on discrete samples from a snow pit collected at Dome C (DC, Antarctica) and on a shallow firn core from the Holtedahlfonna glacier (HDF, Svalbard), providing the first Fe(II) record from both Antarctica and Svalbard. The method showed low detection limits (0.006 ng g−1 for DC and 0.003 ng g−1 for the HDF) and a precision ranging from 3% to 20% RSD. Fe(II) concentrations ranged between the LoD and 0.077 ng g−1 and between the LoD and 0.300 ng g−1 for the Antarctic and Arctic samples, respectively. The Fe(II) contribution with respect to the total dissolved Fe was comparable in both sites accounting, on average, for 5% and 3%, respectively. We found that Fe(II) correctly identified the Pinatubo/Cerro Hudson eruption in the DC record, demonstrating its reliability as volcanic tracer, while, on the HDF core, we provided the first preliminary insight on the processes that might influence Fe speciation in firn matrices (i.e. organic ligands and pH influences).

Local-scale variability of snow density on Arctic sea ice

Abstract. Local-scale variations in snow density and layering on Arctic sea ice were characterized using a combination of traditional snow pit and SnowMicroPen (SMP) measurements. In total, 14 sites were evaluated within the Canadian Arctic Archipelago and Arctic Ocean on both first-year (FYI) and multi-year (MYI) sea ice. Sites contained multiple snow pits with coincident SMP profiles as well as unidirectional SMP transects. An existing SMP density model was recalibrated using manual density cutter measurements (n=186) to identify best-fit parameters for the observed conditions. Cross-validation of the revised SMP model showed errors comparable to the expected baseline for manual density measurements (RMSE = 34 kg m−3 or 10.9 %) and strong retrieval skill (R2=0.78). The density model was then applied to SMP transect measurements to characterize variations at spatial scales of up to 100 m. A supervised classification trained on snow pit stratigraphy allowed separation of the SMP density estimates by layer type. The resulting dataset contains 58 882 layer-classified estimates of snow density on sea ice representing 147 m of vertical variation and equivalent to more than 600 individual snow pits. An average bulk density of 310 kg m−3 was estimated with clear separation between FYI and MYI environments. Lower densities on MYI (277 kg m−3) corresponded with increased depth hoar composition (49.2 %), in strong contrast to composition of the thin FYI snowpack (19.8 %). Spatial auto-correlation analysis showed layered composition on FYI snowpack to persist over long distances while composition on MYI rapidly decorrelated at distances less than 16 m. Application of the SMP profiles to determine propagation bias in radar altimetry showed the potential errors of 0.5 cm when climatology is used over known snow density.

Records of Inorganic Ions and Dust Particles in Snow at Yushugou Glacier No. 6 in the Desert Belt of Northwestern China

Chemical ions and dust particles deposited in snow can be used as indicators of climatic and environmental processes. Understanding their sources, energy transfer and evolutionary mechanisms is extremely important in tracking regional climate and environmental changes. We collected snow samples from three pits at different altitudes and from the surface of Yushugou Glacier No. 6, Tianshan Mountains, China, in the summers of 2017 and 2018. Sea-salt tracing, correlation analysis and factor analysis were used to determine the characteristics and sources of the major ions and mineral dust particles in the snow. We found obvious seasonal variations, with high concentrations of dust particles and major ions deposited during the dust period, and relatively low concentrations deposited during the non-dust period. The concentrations peaked within two distinct dust layers in the snow pits. There was a significant correlation between the peak values and the dust layer. The ionic concentrations were ranked from highest to lowest as Ca2+ > SO42- > Cl- > Na+ > NO3- > NH4+ > Mg2+ > K+. Therefore, SO42- was the dominate anion and Ca2+ was the dominate cation. The major ions in the snow at Yushugou Glacier No. 6 are mainly derived from terrestrial mineral dust but also include limited inputs from human activities and sea salt.

GrSMBMIP: intercomparison of the modelled 1980–2012 surface mass balance over the Greenland Ice Sheet

Abstract. Observations and models agree that the Greenland Ice Sheet (GrIS) surface mass balance (SMB) has decreased since the end of the 1990s due to an increase in meltwater runoff and that this trend will accelerate in the future. However, large uncertainties remain, partly due to different approaches for modelling the GrIS SMB, which have to weigh physical complexity or low computing time, different spatial and temporal resolutions, different forcing fields, and different ice sheet topographies and extents, which collectively make an inter-comparison difficult. Our GrIS SMB model intercomparison project (GrSMBMIP) aims to refine these uncertainties by intercomparing 13 models of four types which were forced with the same ERA-Interim reanalysis forcing fields, except for two global models. We interpolate all modelled SMB fields onto a common ice sheet mask at 1 km horizontal resolution for the period 1980–2012 and score the outputs against (1) SMB estimates from a combination of gravimetric remote sensing data from GRACE and measured ice discharge; (2) ice cores, snow pits and in situ SMB observations; and (3) remotely sensed bare ice extent from MODerate-resolution Imaging Spectroradiometer (MODIS). Spatially, the largest spread among models can be found around the margins of the ice sheet, highlighting model deficiencies in an accurate representation of the GrIS ablation zone extent and processes related to surface melt and runoff. Overall, polar regional climate models (RCMs) perform the best compared to observations, in particular for simulating precipitation patterns. However, other simpler and faster models have biases of the same order as RCMs compared with observations and therefore remain useful tools for long-term simulations or coupling with ice sheet models. Finally, it is interesting to note that the ensemble mean of the 13 models produces the best estimate of the present-day SMB relative to observations, suggesting that biases are not systematic among models and that this ensemble estimate can be used as a reference for current climate when carrying out future model developments. However, a higher density of in situ SMB observations is required, especially in the south-east accumulation zone, where the model spread can reach 2 m w.e. yr−1 due to large discrepancies in modelled snowfall accumulation.

Assessment of heavy metal contamination in the atmospheric deposition during 1950-2016 A.D. from a snow pit at Dome A, East Antarctica.

Antarctic trace element records could provide important insights into the impact of human activities on the environment over the past few centuries. In this study, we investigated the atmospheric concentrations of 14 representative heavy metals (Al, As, Cd, Co, Cu, Fe, K, Mg, Mn, Pb, Sb, Sr, Tl and V) from 174 samples collected in a 4-m snow pit at Dome Argus (Dome A) on the East Antarctic Plateau, covering the period from 1950 to 2016 A.D. We found great variability in the annual concentration of all metals. The crustal enrichment factors suggest that the concentrations of some heavy metals (Cd, Sb, Cu, As and Pb) were likely influenced by anthropogenic activities in recent decades. An analysis of source regions suggests that heavy metal pollution at Dome A was largely caused by human activities in Australia and South America (e.g. mining production, leaded gasoline). Based on the relationship between the trace elements fluxes and sea ice concentration (SIC), sea surface temperature (SST) and annual mean air temperature at 2m above the ground (T2m), our analysis shows that deposition and transport of atmospheric aerosol at Dome A were influenced by circum-Antarctic atmospheric circulations.

Summer Mass Balance and Surface Velocity Derived by Unmanned Aerial Vehicle on Debris-Covered Region of Baishui River Glacier No. 1, Yulong Snow Mountain

Glacier retreat is a common phenomenon in the Qinghai-Tibetan Plateau (QTP) with global warming during the past several decades, except for several mountains, such as the glaciers in the Karakoram and the western Kunlun Mountains. The dynamic nature of glaciers significantly influences the hydrologic, geologic, and ecological systems in the mountain regions. The sensitivity and dynamic response to climate change make glaciers excellent indicators of regional and global climate change, such as glacier melting and retreat with the rise of local air temperature. Long-term monitoring of glacier change is important to understand and assess past, current, and possible future climate environments. Some glacier surfaces are safe and accessible by foot, and are monitored using mass balance stakes and snow pits. Meanwhile, some glaciers with inaccessible termini may be surveyed using satellite remote images and Unmanned Aerial Vehicles (UAVs). Those inaccessible glaciers are generally covered by debris in the southeast QTP, which is hardly accessible due to the wide distribution of crevasses and cliffs. In this paper, we used the UAV to monitor the dynamic features of mass balance and velocity of the debris-covered region of Baishui River Glacier No. 1 (BRG1) on the Yulong Snow Mountain (YSM), Southeast QTP. We obtained the Orthomosaic and DEM with a high resolution of 0.10 m on 20 May and 22 September 2018, respectively. The comparison showed that the elevation of the debris-covered region of the BRG1 decreased by 6.58 m ± 3.70 m on average, and the mean mass balance was −5.92 m w.e. ± 3.33 m w.e. during the summer, correspondingly. The mean displacement of debris-covered glacier surface was 18.30 m ± 6.27 m, that is, the mean daily velocity was 0.14 m/d ± 0.05 m/d during the summer. In addition, the UAV images not only revealed the different patterns of glacier melting and displacement but also captured the phenomena of mass loss due to ice avalanches at the glacier front and the development of large crevasses. This study provides a feasible method for understanding the dynamic features of global debris-covered glaciers which are inaccessible and unobservable by other means.

On the Birth of Structural and Crystallographic Fabric Signals in Polar Snow: A Case Study From the EastGRIP Snowpack

The role of near-surface snow processes for the formation of climate signals through densification into deep polar firn is still barely understood. To this end we have analyzed a shallow snow pit (0-3 meters) from EastGRIP (Greenland) and derived high-resolution profiles of different types of mechanically relevant fabric tensors. The structural fabric, which characterizes the anisotropic geometry of ice matrix and pore space, was obtained by X-ray tomography. The crystallographic fabric, which characterizes the anisotropic distribution of the c-axis (or optical axis) orientations of snow crystals, was obtained from automatic analysis of thin sections. The structural fabric profile unambiguously reveals the seasonal cycles at EastGRIP, as a consequence of temperature gradient metamorphism, and in contrast to featureless signals of parameters like density or specific surface area. The crystallographic fabric profile unambiguously reveals a signal of cluster-type texture already at shallow depth. We make use of order of magnitude estimates for the formation time of both fabric signals and discuss potential coupling effects in the context of snow and firn densification.

The atmospheric iron variations during 1950–2016 recorded in snow at Dome Argus, East Antarctica

174 snow samples were collected from a 4.5 m snow pit at Dome Argus (Dome A), East Antarctica, during the 2015–2016 austral summer. They covered a period between 1950 and 2016. These samples were measured for iron (Fe) concentrations by the inductively coupled plasma mass spectrometry (ICP-MS). Both the total dissolvable Fe (TDFe) and dissolved Fe (DFe) were measured in order to evaluate the fractional Fe solubility (FFS), an important variable to determine the Fe availability for biological activities. The results show an average TDFe flux of 0.019 mg m−2 a−1 and DFe flux of 2.254 × 10−3 mg m−2 a−1 at Dome A. The mean FFS of 7.27% is consistent with previous studies on the Antarctic ice sheet. Based on the mean value of the TDFe fluxes from both the current and previous studies, the atmospheric TDFe flux in Antarctic modern snow was estimated at 19–140 × 10−3 mg m−2 a−1, potentially supporting 10.5–76.5 Tg C a−1 of primary production. This accounts about 1.21–8.80% of the annual primary production in the seasonal sea ice zone of Southern Ocean (SO), suggesting that atmospheric DFe is a minor component of Fe supply.

Can Weather Radars Be Used to Estimate Snow Accumulation on Alpine Glaciers? An Evaluation Based on Glaciological Surveys

AbstractThe snow water equivalent (SWE) is a key component for understanding changes in the cryosphere in high mountain regions. Yet, a reliable quantification at a high spatiotemporal resolution remains challenging in such environments. In this study, we investigate the potential of an operational weather radar–rain gauge composite (CombiPrecip) to infer the daily evolution of SWE on seven Swiss glaciers. To this end, we validate cumulative CombiPrecip estimates with glacier-wide manual SWE observations (snow probing, snow pits) obtained around the time of the seasonal peak during four winter seasons (2015–19). CombiPrecip underestimates the end-of-season snow accumulation by factors of 2.2 up to 3.7, depending on the glacier site. These factors are consistent over the four winter seasons. The regional variability can be mainly attributed to the empirical visibility of the Swiss radar network within the Alps. To account for the underestimation, we investigate three approaches to adjust CombiPrecip for the applicability to glacier sites. Thereby, we combine the factor of underestimation with a precipitation-phase parameterization. For further comparison, we apply a rain gauge catch-efficiency function based on wind speed. We validate these approaches with 14 manual point observations of SWE obtained on two glaciers during three winter seasons. All approaches show a similar improvement of CombiPrecip estimates. We conclude that CombiPrecip has great potential to estimate SWE on glaciers at a high temporal resolution, but further investigations are necessary to understand the regional variability of the bias throughout the Swiss Alps.

Regional Geography of Glacier Mass Balance Variability Over Seven Decades 1946–2015

Despite much progress with remote sensing, on–site measurements of glacier mass balance (with stakes and snow pits) still have advantages for resolution of interannual and seasonal changes of mass balance. Understanding these changes may help to identify the types of glaciers most sensitive to climate change. The standard deviation of mass balance data series for a few years describes the interannual variability, and balance amplitude, defined as half the difference between winter and summer balances, describes the seasonal variability. Interannual variability increases with seasonal variability, and seasonal variability increases with annual precipitation and summer temperature available from a half–degree gridded climatology. Measured glaciers have higher mean and median precipitation than average for all glaciers in the Randolph Glacier Inventory (version 6). High balance amplitudes are associated with warm/wet (maritime) environments and low amplitudes with cold/dry (continental) environments, as shown in previous studies of climate at the equilibrium line altitude. Balance amplitude can be modelled for half–degree grid squares in the glacier inventory using multiple regression of measured balance amplitude on the climate data. The resulting modelled balance amplitude is relatively low for Arctic Islands and Central Asia, but high for Western North America, Iceland, Scandinavia, Alps and Caucasus.

Studies on the variability of the Greenland Ice Sheet and climate

We review major scientific results from Subtheme (1) "Variability of the Greenland Ice Sheet and climate" under Research Theme 2 "Variations in the ice sheet, glaciers, and the environment in the Greenland region" of the Arctic Challenge for Sustainability (ArCS) project. We participated in the international East Greenland Ice Core Project (EGRIP) led by Denmark, conducted snow pit observations near the coring site and reconstructed the surface mass balance over the past 10 years. Analyses of an ice core from Northwest Greenland revealed temporal variability in black carbon concentration over the past 350 years and in mineral dust over the past 100 years. To understand the mechanisms of ice-sheet flow, which is necessary for accurate predictions of sea level rise, we conducted laboratory experiments using artificial ice and derived an improved flow law for ice containing impurities. Ice sheet modeling was improved by including effects of impurities and ice stream dynamics. As part of the Ice Sheet Model Intercomparison Project for the Coupled Model Intercomparison Project Phase 6 (ISMIP6), we simulated ice sheet mass loss and contribution to sea level rise over the 21st century and beyond. Furthermore, we developed a Glacial Isostatic Adjustment model to better constrain ice sheet models.

Spatial and temporal variations of refractory black carbon along the transect from Zhongshan Station to Dome A, eastern Antarctica

Abstract Refractory black carbon (rBC) aerosols emitted by biomass burning and fossil fuel combustion can cause significant climatic forcing when it deposited on the snow. The Southern Hemisphere (SH) biomass burning emissions represent a significant part of rBC in and around Antarctica. Here we present the spatial and temporal variations of rBC from the surface snow and snow pits samples along the coastal Zhongshan Station (ZSS) to inland Dome A transect in Lambert Glacier region of eastern Antarctica. The geometric mean concentrations of surface snow rBC was 0.017 ± 0.018 ng g−1 and showed higher values in the inland plateau region (900–1248 km, 0.031 ± 0.024 ng g−1) than the coastal region (0–400 km, 0.011 ± 0.005 ng g−1) and there exist similar spatial results for the inland snowpit (0.021 ± 0.017 ng g−1) and coastal snowpit (0.018 ± 0.013 ng g−1). The records from the coastal snowpit (SP-A) show that the rBC from 2009 to 2016 displays weak seasonal variations, while in the inland snowpit (SP–C) the records spans from 1950 to 2015 and showed the rBC concentrations vary and relate with the open biomass burning emission in the Southern Hemisphere.

The fallout from Fukushima Daiichi nuclear accident profiles a new dating reference in ice and comparison with the Chernobyl accident

Absolute-age dating horizons play a pillar role in the reconstruction of an ice core chronology. In the modern era, these have included the global fallout from massive volcanic eruptions, atmospheric and marine thermonuclear weapons testing and nuclear accidents. After the occurrence of the Fukushima Daiichi nuclear accident (FDNA) on March 11 2011, the simulation of the radioactivity from the FDNA by a dispersion model (HYSPLIT) shows that the nuclides reached the study area in late March, consistent with the ground measurements in Xi’an, Lanzhou and Urumqi. To investigate the deposition of radioactivity resulting from the FDNA, we collected snowpack samples from four glaciers (i.e. Glacier No. 1, Glacier No. 72, Qiyi and Shiyi glaciers, respectively) in northwestern China and analysed them for total β activity (TBA). The measured TBA in the FDNA layers were increased by two to four times, compared with the averages in the non-FDNA layers. We revisited Glacier No. 1 in 2018 and studied a much deeper snow-pit profile for the TBA, seven years after the first-time investigation into a relatively shallow snow pit in 2011. The TBA concentrated in a dust layer and became more significant in 2018 compared to that in 2011. We compared the TBA in Glacier No. 1 with that in the Muztagata glacier from the Chernobyl accident in 1986, and the depositions of radioactivity in the two High-Asian glaciers were comparable. We conclude that the FDNA formed a distinctly new lasting reference in the snow, which could help date the snow and ice in the Northern Hemisphere.

On snow stability interpretation of extended column test results

Abstract. Snow instability tests provide valuable information regarding the stability of the snowpack. Test results are key data used to prepare public avalanche forecasts. However, to include them into operational procedures, a quantitative interpretation scheme is needed. Whereas the interpretation of the rutschblock test (RB) is well established, a similar detailed classification for the extended column test (ECT) is lacking. Therefore, we develop a four-class stability interpretation scheme. Exploring a large data set of 1719 ECTs observed at 1226 sites, often performed together with a RB in the same snow pit, and corresponding slope stability information, we revisit the existing stability interpretations and suggest a more detailed classification. In addition, we consider the interpretation of cases when two ECTs were performed in the same snow pit. Our findings confirm previous research, namely that the crack propagation propensity is the most relevant ECT result and that the loading step required to initiate a crack is of secondary importance for stability assessment. The comparison with the RB showed that the ECT classifies slope stability less reliably than the RB. In some situations, performing a second ECT may be helpful when the first test did not indicate rather unstable or stable conditions. Finally, the data clearly show that false-unstable predictions of stability tests outnumber the correct-unstable predictions in an environment where overall unstable locations are rare.

Frozen ground and snow cover monitoring in Livingston and Deception islands, Antarctica: preliminary results of the 2015-2019 PERMASNOW project

Since 2006, our research team has been establishing in the islands of Livingston and Deception, (South Shetland archipelago, Antarctica) several monitoring stations of the active layer thickness within the international network Circumpolar Active Layer Monitoring (CALM), and the ground thermal regime for the Ground Terrestrial Network-Permafrost (GTN-P). Both networks were developed within the International Permafrost Association (IPA). In the GTN-P stations, in addition to the temperature of the air, soil, and terrain at different depths, the snow thickness is also monitored by snow poles. Since 2006, a delay in the disappearance of the snow layer has been observed, which could explain the variations we observed in the active layer thickness and permafrost temperatures. Therefore, in late 2015 our research group started the PERMASNOW project (2015-2019) to pay attention to the effect of snow cover on ground thermal This project had two different ways to study the snow cover. On the first hand, in early 2017 we deployed new instrumentation, including new time lapse cameras, snow poles with high number of sensors and a complete and complex set of instruments and sensors to configure a snow pack analyzer station providing 32 environmental and snow parameters. We used the data acquired along 2017 and 2018 years with the new instruments, together with the available from all our already existing sensors, to study in detail the snow cover. On the other hand, remote sensing data were used to try to map the snow cover, not only at our monitoring stations but the entire islands in order to map and study the snow cover distribution, as well as to start the way for future permafrost mapping in the entire islands. MODIS-derived surface temperatures and albedo products were used to detect the snow cover and to test the surface temperature. Since cloud presence limited the acquisition of valid observations of MODIS sensor, we also analyzed Terrasar X data to overcome this limitation. Remote sensing data validation required the acquirement of in situ ground-true data, consisting on data from our permanent instruments, as well as ad hoc measurements in the field (snow cover mapping, snow pits, albedo characterization, etc.). Although the project is finished, the data analysis is still ongoing. We present here the different research tasks we are developing as well as the most important results we already obtained about the snow cover. These results confirm how the snow cover duration has been changing in the last years, affecting the ground thermal behavior.

Acquisition of Post-Depositional Effects on Stable Isotopes (δ18O and δD) of Snow and Firn at Dome A, East Antarctica

Water stable isotopes (δ18O and δD) in Antarctic snow pits and ice cores are extensively applied in paleoclimate reconstruction. However, their interpretation varies over some climate change processes that can alter isotope signals after deposition, especially at sites with a low snow accumulation rate (<30 mm w.e. year−1). To investigate post-depositional effects during the archival processes of snow isotopes, we first analyzed δ18O and δD variations in summer precipitation, surface snow and snow pit samples collected at Dome A. Then, the effects of individual post-depositional processes were evaluated from the results of field experiments, spectral analysis and modeling simulations. It was found that the sublimation–condensation cycle and isotopic diffusion were likely the dominant processes that modified the δ18O at and under the snow–air interface, respectively. The sublimation–condensation cycle can cause no significant isotopic modification of δ18O from field experiments with ~3 cm snow. The diffusion process can significantly erase the original seasonal variation of δ18O driven by atmospheric temperature, leading to an apparent cycle of ~20 cm average wavelength present in the δ18O profile. Through the comparison with the artificial isotopic profile, the noise input from the diffusion process was the dominant component in the δ18O signal. Although some other processes (such as drifting, ventilation and metamorphism) were not fully considered, the quantitative understanding for the sublimation–condensation and diffusion processes will contribute to the paleoclimate construction using the ice core water isotope records at Dome A.

A critical analysis on the uncertainty computation in ground-penetrating radar-retrieved dry snow parameters

The use of the ground-penetrating-radar (GPR) technique to estimate snow parameters such as thickness, density, and snow water equivalent (SWE) is particularly promising because it allows for surveying a large area in a relatively short amount of time. However, this application requires an accurate evaluation of the physical parameters retrieved from the radar measurements, which requires estimating each quantity involved in the computation along with its associated uncertainty. Conversely, the uncertainties are rarely reported in GPR snow studies, even if they represent essential information for data comparisons with other techniques such as the snow rod or snow pit methods. Snow parameters can be estimated from radar data as follows: The snow thickness can be computed from two-way traveltime if the snow average wave velocity is known; the snow density can be estimated from wave velocity using an appropriate mixing formula, and SWE can be computed once these two parameters have been calculated. Starting from published data, we have estimated the accuracy achievable by computing the overall uncertainty for each GPR-retrieved snow parameter and evaluated the influence of the different sources of uncertainties. The computation was made for three antenna frequencies (250, 500, and 1000 MHz) and various snow depths (0–5 m). We find that for snow thicknesses of less than 3 m, the main contribution to the uncertainties associated with snow parameters is given by the uncertainty on two-way traveltime estimation, especially for low antenna frequencies. However, for thicker snow depths, other factors such as the uncertainty on the antenna separation affect the overall accuracy and cannot be neglected. Our studies highlight the importance of the uncertaintiy assessment and suggest a rigorous way for their computation in the field of quantitative geophysics.

The RHOSSA campaign: multi-resolution monitoring of the seasonal evolution of the structure and mechanical stability of an alpine snowpack

Abstract. The necessity of characterizing snow through objective, physically motivated parameters has led to new model formulations and new measurement techniques. Consequently, essential structural parameters such as density and specific surface area (for basic characterization) or mechanical parameters such as the critical crack length (for avalanche stability characterization) gradually replace the semiempirical indices acquired from traditional stratigraphy. These advances come along with new demands and potentials for validation. To this end, we conducted the RHOSSA field campaign, in reference to density (ρ) and specific surface area (SSA), at the Weissfluhjoch research site in the Swiss Alps to provide a multi-instrument, multi-resolution dataset of density, SSA and critical crack length over the complete winter season of 2015–2016. In this paper, we present the design of the campaign and a basic analysis of the measurements alongside predictions from the model SNOWPACK. To bridge between traditional and new methods, the campaign comprises traditional profiles, density cutter, IceCube, SnowMicroPen (SMP), micro-computed-tomography, propagation saw tests and compression tests. To bridge between different temporal resolutions, the traditional weekly to biweekly (every 2 weeks, used in this sense throughout the paper) snow pits were complemented by daily SMP measurements. From the latter, we derived a recalibration of the statistical retrieval of density and SSA for SMP version 4 that yields an unprecedented spatiotemporal picture of the seasonal evolution of density and SSA in a snowpack. Finally, we provide an intercomparison of measured and modeled estimates of density and SSA for four characteristic layers over the entire season to demonstrate the potential of high-temporal-resolution monitoring for snowpack model validation.

Intercomparison of measurements of bulk snow density and water equivalent of snow cover with snow core samplers: Instrumental bias and variability induced by observers

AbstractManually collected snow data are often considered as ground truth for many applications such as climatological or hydrological studies. However, there are many sources of uncertainty that are not quantified in detail. For the determination of water equivalent of snow cover (SWE), different snow core samplers and scales are used, but they are all based on the same measurement principle. We conducted two field campaigns with 9 samplers commonly used in observational measurements and research in Europe and northern America to better quantify uncertainties when measuring depth, density and SWE with core samplers. During the first campaign, as a first approach to distinguish snow variability measured at the plot and at the point scale, repeated measurements were taken along two 20 m long snow pits. The results revealed a much higher variability of SWE at the plot scale (resulting from both natural variability and instrumental bias) compared to repeated measurements at the same spot (resulting mostly from error induced by observers or very small scale variability of snow depth). The exceptionally homogeneous snowpack found in the second campaign permitted to almost neglect the natural variability of the snowpack properties and focus on the separation between instrumental bias and error induced by observers. Reported uncertainties refer to a shallow, homogeneous tundra‐taiga snowpack less than 1 m deep (loose, mostly recrystallised snow and no wind impact). Under such measurement conditions, the uncertainty in bulk snow density estimation is about 5% for an individual instrument and is close to 10% among different instruments. Results confirmed that instrumental bias exceeded both the natural variability and the error induced by observers, even in the case when observers were not familiar with a given snow core sampler.

Deposition, recycling, and archival of nitrate stable isotopes between the air–snow interface: comparison between Dronning Maud Land and Dome C, Antarctica

Abstract. The nitrogen stable isotopic composition in nitrate (δ15N-NO3-) measured in ice cores from low-snow-accumulation regions in East Antarctica has the potential to provide constraints on past ultraviolet (UV) radiation and thereby total column ozone (TCO) due to the sensitivity of nitrate (NO3-) photolysis to UV radiation. However, understanding the transfer of reactive nitrogen at the air–snow interface in polar regions is paramount for the interpretation of ice core records of δ15N-NO3- and NO3- mass concentrations. As NO3- undergoes a number of post-depositional processes before it is archived in ice cores, site-specific observations of δ15N-NO3- and air–snow transfer modelling are necessary to understand and quantify the complex photochemical processes at play. As part of the Isotopic Constraints on Past Ozone Layer Thickness in Polar Ice (ISOL-ICE) project, we report new measurements of NO3- mass concentration and δ15N-NO3- in the atmosphere, skin layer (operationally defined as the top 5 mm of the snowpack), and snow pit depth profiles at Kohnen Station, Dronning Maud Land (DML), Antarctica. We compare the results to previous studies and new data, presented here, from Dome C on the East Antarctic Plateau. Additionally, we apply the conceptual 1D model of TRansfer of Atmospheric Nitrate Stable Isotopes To the Snow (TRANSITS) to assess the impact of NO3- recycling on δ15N-NO3- and NO3- mass concentrations archived in snow and firn. We find clear evidence of NO3- photolysis at DML and confirmation of previous theoretical, field, and laboratory studies that UV photolysis is driving NO3- recycling and redistribution at DML. Firstly, strong denitrification of the snowpack is observed through the δ15N-NO3- signature, which evolves from the enriched snowpack (−3 ‰ to 100 ‰), to the skin layer (−20 ‰ to 3 ‰), to the depleted atmosphere (−50 ‰ to −20 ‰), corresponding to mass loss of NO3- from the snowpack. Based on the TRANSITS model, we find that NO3- is recycled two times, on average, before it is archived in the snowpack below 15 cm and within 0.75 years (i.e. below the photic zone). Mean annual archived δ15N-NO3- and NO3- mass concentration values are 50 ‰ and 60 ng g−1, respectively, at the DML site. We report an e-folding depth (light attenuation) of 2–5 cm for the DML site, which is considerably lower than Dome C. A reduced photolytic loss of NO3- at DML results in less enrichment of δ15N-NO3- than at Dome C mainly due to the shallower e-folding depth but also due to the higher snow accumulation rate based on TRANSITS-modelled sensitivities. Even at a relatively low snow accumulation rate of 6 cm yr−1 (water equivalent; w.e.), the snow accumulation rate at DML is great enough to preserve the seasonal cycle of NO3- mass concentration and δ15N-NO3-, in contrast to Dome C where the depth profiles are smoothed due to longer exposure of surface snow layers to incoming UV radiation before burial. TRANSITS sensitivity analysis of δ15N-NO3- at DML highlights that the dominant factors controlling the archived δ15N-NO3- signature are the e-folding depth and snow accumulation rate, with a smaller role from changes in the snowfall timing and TCO. Mean TRANSITS model sensitivities of archived δ15N-NO3- at the DML site are 100 ‰ for an e-folding depth change of 8 cm, 110 ‰ for an annual snow accumulation rate change of 8.5 cm yr−1 w.e., 10 ‰ for a change in the dominant snow deposition season between winter and summer, and 10 ‰ for a TCO change of 100 DU (Dobson units). Here we set the framework for the interpretation of a 1000-year ice core record of δ15N-NO3- from DML. Ice core δ15N-NO3- records at DML will be less sensitive to changes in UV than at Dome C; however the higher snow accumulation rate and more accurate dating at DML allows for higher-resolution δ15N-NO3- records.