Snow Surface Research Articles

Importance of source structure on complex organics emission

Context. The protostellar stage is known to be the richest star formation phase in emission from gaseous complex organic molecules. However, some protostellar systems show little or no millimetre (mm) line emission of such species. This can be interpreted as a low abundance of complex organic molecules. Alternatively, complex species could be present in the system, but are not seen in the gas. Aims. The goal is to investigate the second hypothesis for methanol as the most abundant complex organic molecule in protostellar systems. This work aims to determine how effective dust optical depth is in hiding methanol in the gas, and whether methanol can mainly reside in the ice due to the presence of a disk that lowers the temperatures. Hence, we attempt to answer the question whether the presence of a disk and optically thick dust reduce methanol emission even if methanol and other complex species are abundant in the ices and gas. Methods. Using the radiative transfer code RADMC-3D, we calculated methanol emission lines from an envelope-only model and from an envelope-plus-disk model. We compared the results with each other and with the observations. Methanol gas and ice abundances were parametrised inside and outside of the snow surfaces based on values from observations. Both models included either dust grains with low mm opacity or high mm opacity, and their physical parameters such as envelope mass and disk radius were varied. Results. Methanol emission from the envelope-only model is always stronger than from the envelope-plus-disk model by at least a factor ∼2 as long as the disk radius is larger than ∼30 au (for L = 8 L⊙). In most cases, this is due to lower temperatures (disk shadowing), which causes the smaller amount of warm (≳70 K) methanol inside the snow surface of the envelope-plus-disk model. The intensities drop by more than an order of magnitude for models including high mm opacity dust grains and disk radii of at least ∼50 au (for L = 8 L⊙) due to continuum over-subtraction. Conclusions. The line intensities from the envelope-only models match the observations moderately well when methanol emission is strong, but they overproduce the observations of protostars with lower methanol emission even with large dust optical depth effects. The envelope-plus-disk models can explain the bulk of the observations. However, they can only reproduce the observations of sources with high luminosities and very low methanol emission when the dust optical depth is significant in the envelope and continuum over-subtraction becomes effective in the disk (high mm opacity dust grains are used). Therefore, both the effects of disk and dust optical depth should be considered to explain the observations. In conclusion, it is important to take physical structure into account in future chemical studies of low-mass protostars: absence of gas-phase methanol emission does not imply absence of methanol molecules in either gas or ice.

The internal melting of landfast sea ice in Prydz Bay, East Antarctica

Summertime internal melting of Antarctic sea ice is common due to the penetration of solar radiation below the snow and ice surface. We focus on the role of internal melting and heat conduction in generating gap layers within the ice. These often occur approximately 0.1 m below the ice surface. In a small-scale survey over land-fast sea ice in Prydz Bay, East Antarctica, we observed, for the first time, gap layers 0.6–1.0 m below the surface for both first-year ice and multi-year ice. A 1D snow/ice thermodynamic model successfully simulated snow and ice mass balance and the evolution of the gap layers. Their spatial distribution was largely controlled by snow thickness and ice thickness. A C-shaped ice temperature profile with the lowest values in the middle of the ice layer resulted in heat flux convergence causing downward progression of the internal melt layer. Multidecadal (1979–2019) seasonal simulations showed decreasing air temperature favored a postposed internal melting onset, reduced total internal melt, and delayed potential ice breakup, which indicated a higher chance for local coastal ice to be shifted from first-year ice to multi-year ice.

Quantitative assessment of the parameterization sensitivity of the WRF/Noah-MP model of snow dynamics in the Tianshan Mountains, Central Asia

The study of parameterization schemes is important for land surface models (LSMs) due to the uncertainties existed in simulating snow. However, previous studies have mainly assessed the qualitative sensitivity of parameterization combinations on snow simulations in LSMs. To better understand the parameterization schemes and reduce the model uncertainties in simulating snow depth, 24 ensemble experiments were conducted in this study using the Weather Research and Forecasting (WRF) model coupled with the Noah land surface model with multiparameterization options (WRF/Noah-MP) model based on four physical subprocesses: snow surface albedo (ALB); precipitation partitioning between rain and snowfall (SNF); snow/soil temperature time (STC); surface layer turbulence (SFC) schemes. Additionally, the sensitivities of the four parameterizations in simulating the snow depth were quantitatively assessed. The results showed that the WRF/Noah-MP model underestimated snow depth, with underestimation in the snow accumulation season and overestimation in the early snow accumulation and snow ablation seasons. The Sobol sensitivity revealed the dominant role of the ALB and STC subprocesses in the simulation of the snow depth. The sensitivities of the four physical subprocesses varied in the different snow seasons and at different altitudes. Additionally, all the subprocesses exhibited interactions when simulating the snow depth in the Tianshan Mountains in this study, except for the ALB in the snow ablation season and the STC at >1000 m. Distinct differences existed in the snow depth simulations using the different selected schemes with the ALB, STC, and SFC subprocess parameterization. Comparison of the parameterization schemes of the four subprocesses revealed that the ALB, STC, and SFC subprocess parameterizations mainly affected the snow depth simulation through the heat fluxes, while the SNF affected it through the air temperature.

Land Surface Snow Phenology Based on an Improved Downscaling Method in the Southern Gansu Plateau, China

Snow is involved in and influences water–energy processes at multiple scales. Studies on land surface snow phenology are an important part of cryosphere science and are a hot spot in the hydrological community. In this study, we improved a statistical downscaling method by introducing a spatial probability distribution function to obtain regional snow depth data with higher spatial resolution. Based on this, the southern Gansu Plateau (SGP), an important water source region in the upper reaches of the Yellow River, was taken as a study area to quantify regional land surface snow phenology variation, together with a discussion of their responses to land surface terrain and local climate, during the period from 2003 to 2018. The results revealed that the improved downscaling method was satisfactory for snow depth data reprocessing according to comparisons with gauge-based data. The downscaled snow depth data were used to conduct spatial analysis and it was found that snow depth was on average larger and maintained longer in areas with higher altitudes, varying and decreasing with a shortened persistence time. Snow was also found more on steeper terrain, although it was indistinguishable among various aspects. The former is mostly located at high altitudes in the SGP, where lower temperatures and higher precipitation provide favorable conditions for snow accumulation. Climatically, factors such as precipitation, solar radiation, and air temperature had significantly singular effectiveness on land surface snow phenology. Precipitation was positively correlated with snow accumulation and maintenance, while solar radiation and air temperature functioned negatively. Comparatively, the quantity of snow was more sensitive to solar radiation, while its persistence was more sensitive to air temperature, especially extremely low temperatures. This study presents an example of data and methods to analyze regional land surface snow phenology dynamics, and the results may provide references for better understanding water formation, distribution, and evolution in alpine water source areas.

Sublimation Origin of Negative Deuterium Excess Observed in Snow and Ice Samples From McMurdo Dry Valleys and Allan Hills Blue Ice Areas, East Antarctica

AbstractThe oxygen and hydrogen isotopic composition in snow and ice have long been utilized to reconstruct past temperatures of polar regions, under the assumption that post‐depositional processes such as sublimation do not fractionate snow. In low‐accumulation (<0.01 m yr−1) areas near the McMurdo Dry Valleys in Antarctica, surface snow and ice samples have exceptionally low deuterium excess values (d‐excess ≡ δD – 8*δ18O)—sometimes as negative as −5‰—an uncommon phenomenon that is not fully understood. Here we use both an isotope‐enabled general circulation model and an ice physics model and establish that such exceptionally low d‐excess values can only arise from precipitation if the majority of the moisture is sourced from the Southern Ocean (south of 55°S). However, the model results show that moisture sourced from oceans north of 55°S contributes significantly (>50%) to precipitation in Antarctica today. We thus propose that sublimation must have occurred to yield the low d‐excess values in snow observed in and near the Dry Valleys, and that solid‐phase‐diffusion in ice grains is sufficiently fast to allow Rayleigh‐like isotopic fractionation in similar environments. We calculate that under present‐day conditions at the Allan Hills outside the Dry Valleys, 3%–24% of the surface snow is lost due to sublimation. Because the magnitude of sublimation may be nonstationary (i.e., it could vary in time) during past cold periods, we suggest that sublimation‐induced fractionation can alter the relationship between the snow isotopic composition and polar temperatures.

Surface melting of snow-firn-ice structures and estimation of extended transient energy and mass balances using a liquid solid phase-change model

Parameterized energy and mass balance models are often applied to estimate energy fluxes at the surface that are available for melting and sublimation of snow and ice surfaces. In this study we evaluate the suitability of quantifying transient energy and mass fluxes on frozen surface using the finite volume method in comparison with the traditional glaciological energy balance approach. To assess the model application, we apply the methods to two datasets: a glacier in the semiarid Andes, and an Antarctic ice shelf, estimating the effect of time varying surface irradiation, wind velocity, air temperature and humidity on the history of temperature, liquid water and heat fluxes during 30 months. Results of energy and mass balances are validated with previously published results of global balances and meteorological datasets.

FlakeOut: A geometric approach to remove wind-blown snow from terrestrial laser scans

Wind-blown snow particles often contaminate Terrestrial Laser Scanning (TLS) data of snow covered terrain. However, common filtering techniques fail to filter wind-blown snow and incorrectly filter data from the true surface due to the spatial distribution of wind-blown snow and the TLS scanning geometry. We present FlakeOut, a filter designed specifically to filter wind-blown snowflakes from TLS data. A key aspect of FlakeOut is a low false positive rate of 2.8x10-4—an order of magnitude lower than standard filtering techniques—which greatly reduces the number of true ground points that are incorrectly removed. This low false positive rate makes FlakeOut appropriate for applications requiring quantitative measurements of the snow surface in light to moderate blowing snow conditions. Additionally, we provide mathematical and software tools to efficiently estimate the false positive rate of filters applied for the purpose of removing erroneous data points that occur very infrequently in a dataset.

Molecular compositions, optical properties, and implications of dissolved brown carbon in snow/ice on the Tibetan Plateau glaciers.

Brown carbon (BrC)/water-soluble organic carbon (WSOC) plays a crucial role in glacier melting. A quantitative evaluation of the light absorption characteristics of WSOC on glacier melting is urgently needed, as the WSOC release from glaciers potentially affects the hydrological cycle, downstream ecological balance, and the global carbon cycle. In this work, the optical properties and composition of WSOC in surface snow/ice on four Tibetan Plateau (TP) glaciers were investigated using a three-dimensional fluorescence spectrometer and electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry. The total light-absorption of WSOC in snow/ice at 250-400nm (ultraviolet region) and 400-600nm (visible region) accounted for about 60.42% and 27.17% of the light absorption by the total organics, respectively. Two protein-like substances (PRLIS), one humic-like substance (HULIS), and one undefined species of chromophores in snow/ice on the TP glacier surfaces were identified. The lignins and lipids were the main compounds in the TP glaciers and were presented as CHO and CHNO molecules, while CHNOS molecules were only observed in the southeast TP glacier. The light absorption capacity of WSOC in snow/ice was mainly affected by their oxidizing properties. PRLIS and undefined species were closely linked to microbial sources and the local environment of the glaciers (lignins and lipids), while HULIS was significantly affected by anthropogenic emissions (protein/amino sugars). Radiative forcing (RF)-induced by WSOC relative to black carbon were accounted for about 11.62±12.07% and 8.40±10.37% in surface snow and granular ice, respectively. The RF was estimated to be 1.14 and 6.36Wm-2 in surface snow and granular ice, respectively, during the melt season in the central TP glacier. These findings contribute to our understanding of WSOC's impact on glaciers and could serve as a baseline for WSOC research in cryospheric science.

The Young Embedded Disk L1527 IRS: Constraints on the Water Snowline and Cosmic-Ray Ionization Rate from HCO+ Observations

The water snowline in circumstellar disks is a crucial component in planet formation, but direct observational constraints on its location remain sparse owing to the difficulty of observing water in both young embedded and mature protoplanetary disks. Chemical imaging provides an alternative route to locate the snowline, and HCO+ isotopologues have been shown to be good tracers in protostellar envelopes and Herbig disks. Here we present ∼0.″5 resolution (∼35 au radius) Atacama Large Millimeter/submillimeter Array (ALMA) observations of HCO+ J = 4 − 3 and H13CO+ J = 3 − 2 toward the young (Class 0/I) disk L1527 IRS. Using a source-specific physical model with the midplane snowline at 3.4 au and a small chemical network, we are able to reproduce the HCO+ and H13CO+ emission, but for HCO+ only when the cosmic-ray ionization rate is lowered to 10−18 s−1. Even though the observations are not sensitive to the expected HCO+ abundance drop across the snowline, the reduction in HCO+ above the snow surface and the global temperature structure allow us to constrain a snowline location between 1.8 and 4.1 au. Deep observations are required to eliminate the envelope contribution to the emission and to derive more stringent constraints on the snowline location. Locating the snowline in young disks directly with observations of H2O isotopologues may therefore still be an alternative option. With a direct snowline measurement, HCO+ will be able to provide constraints on the ionization rate.

Black carbon, organic carbon, and mineral dust in South American tropical glaciers: A review

Tropical glaciers are extremely sensitive to changes of climate variables. Their response to climate change is complex and depends on multiple mechanisms affecting their mass and energy balance, including deposition of light absorbing particles (LAPs) from the atmosphere on snow and ice. Such particles can reduce glaciers surface albedo, thus enhancing the melting process. LAPs include carbonaceous particles (black carbon - BC and organic carbon - OC) and mineral dust aerosol (MDA). Although their relevance in global cryosphere, LAPs observations in the Andes tropical glacier areas are limited and sparse. This review aims at providing a critical evaluation of available data on LAPs in South America tropical glaciers, and highlights research gaps that will help to improve our understanding of natural processes and anthropogenic emissions impacts on the cryosphere of the region. In South American tropical glaciers, LAPs measurements in surface snow are mainly focused in the Cordillera Blanca and limited information are available about their chemical composition (carbonaceous or mineral components), while dust ice core records have been investigated in several sectors of the Andes, including in the Cordillera Blanca, Cordillera Oriental, and Cordillera Real. Remote and field observations in South American tropical glaciers indicate that LAPs might explain a significant fraction of snow albedo variability, however snow albedo reduction from modelling studies varies significantly depending on LAPs concentration and composition. Carbonaceous LAPs sources in South America are dominated by BC emissions from open fires, linked to agricultural and land clearing activities, peaking in the southern hemisphere dry season (August–October). Natural and anthropogenic dust emissions are potentially relevant contributors of LAPs on the Andes glaciers, as well. Satellite and in-situ measurements were deployed to investigate transport episodes of carbonaceous and mineral particles from lower altitudes towards the Andean glaciers. Nevertheless, the small number of atmospheric records of BC, OC, and MDA does not allow a systematic understanding of transport and deposition processes of such species in the region. • LAPs could account for up to 22% of albedo reduction in the Andes. • Knowledge of LAP composition is needed to understand snow albedo change. • LAPs atmospheric and cryosphere data in the Andes are extremely limited. • Relative contribution of natural and anthropogenic dust to snow LAPs is unclear. • Accurate LAP source definition requires understanding of transport and deposition.

Ведущая роль турбулентной диффузии в процессах атмосферного рассеяния трития в зоне влияния ядерного реактора

Previously carried out measurements of tritium activity in surface waters or snow with a 10–1000x excess over the background away from industrial sites of nuclear industry enterprises cannot be associated with technological accidents. They fully comply with the standard technological regime peculiar to a specific design of a nuclear reactor. It is shown that the intensity of dispersion of tritium compounds is mainly responsible for turbulent diffusion in “the flare” of the exhaust pipe, even during calm. This fact can be used to organize quantitative control of emissions to atmosphere during the year.

Snow Depth Measurements by GNSS-IR at an Automatic Weather Station, NUK-K

Studies have shown that geodetic Global Navigation Satellite System (GNSS) stations can be used to measure snow depths using GNSS interferometric reflectometry (GNSS-IR). Here, we study the results from a customized GNSS setup installed in March through August 2020 at the Programme for Monitoring of the Greenland Ice Sheet (PROMICE) automatic weather station NUK-K located on a small glacier outside Nuuk, Greenland. The setup is not optimized for reflectometry purposes. The site is obstructed between 85 and 215 degrees, and as the power supply is limited due to the remote location, the logging time is limited to 3 h per day. We estimate reflector heights using GNSS-IR and compare the results to a sonic ranger also placed on the weather station. We find that the snow melt measured by GNSS-IR is comparable to the melt measured by the sonic ranger. We expect that a period of up to 45 cm difference between the two is likely related to the much larger footprint GNSS-IR and the topography of the area. The uncertainty on the GNSS-IR reflector heights increase from approximately 2 cm for a snow surface to approximately 5 cm for an ice surface. If reflector height during snow free periods are part of the objective of a similar setup, we suggest increasing the logging time to reduce the uncertainty on the daily estimates.

A Time Series of Snow Density and Snow Water Equivalent Observations Derived From the Integration of GPR and UAV SfM Observations

Snow depth can be mapped from airborne platforms and measured in situ rapidly, but manual snow density and snow water equivalent (SWE) measurements are time consuming to obtain using traditional survey methods. As a result, the limited number of point observations are likely insufficient to capture the true spatial complexity of snow density and SWE in many settings, highlighting the value of distributed observations. Here, we combine measured two-way travel time from repeat ground-penetrating radar (GPR) surveys along a ∼150 m transect with snow depth estimates from UAV-based Structure from Motion Multi-View Stereo (SfM-MVS) surveys to estimate snow density and SWE. These estimates were successfully calculated on eleven dates between January and May during the NASA SnowEx21 campaign at Cameron Pass, CO. GPR measurements were made with a surface-coupled Sensors and Software PulseEkko Pro 1 GHz system, while UAV flights were completed using a DJI Mavic 2 Pro platform and consisted of two orthogonal flights at ∼60 m elevation above ground level. SfM-MVS derived dense point clouds (DPCs) were georeferenced using eight ground control points and evaluated using three checkpoints, which were distributed across the ∼3.5 ha study plot containing the GPR transect. The DPCs were classified to identify the snow surface and then rasterized to produce snow-on digital surface models (DSMs) at 1 m resolution. Snow depths on each survey date were calculated by differencing these snow-on DSMs from a nearly snow-off DSM collected near the end of the melt season. SfM-derived snow depths were evaluated with independent snow depth measurements from manual probing (mean r2 = 0.67, NMAD = 0.11 m and RMSE = 0.12 m). The GPR-SfM derived snow densities were compared to snow density measurements made in snowpits (r2 = 0.42, NMAD = 39 kg m−3 and RMSE = 68 kg m−3). The integration of SfM and GPR observations provides an accurate, efficient, and a relatively non-destructive approach for measuring snow density and SWE at intermediate spatial scales and over seasonal timescales. Ongoing developments in snow depth retrieval technologies could be leveraged in the future to extend the spatial extent of this method.

Recent hydrological response of glaciers in the Canadian Rockies to changing climate and glacier configuration

Abstract. Mountain snow and ice greatly influence the hydrological cycle of alpine regions by regulating both the quantity of and seasonal variations in water availability downstream. This study considers the combined impacts of climate and glacier changes due to recession on the hydrology and water balance of two high-elevation basins in the Canadian Rockies. A distributed, physically based, uncalibrated glacier hydrology model developed in the Cold Regions Hydrological Modelling platform (CRHM) was used to simulate the glacier mass balance and basin hydrology of the Peyto and Athabasca glacier basins in Alberta, Canada. Bias-corrected reanalysis data were used to drive the model. The model calculates the water balance of glacierized basins, influenced by the surface energy and mass balance, and considers the redistribution of snow by wind and avalanches. It was set up using hydrological response units based on elevation bands, surface slope, and aspect, as well as changing land cover. Aerial photos, satellite images and digital elevation models (DEMs) were assimilated to represent the changing configurations of glacier area and the exposure of ice and firn. Observations of glacier mass balance, snow, and glacier ice surface elevation changes at glacier and alpine tundra meteorological stations and streamflow discharge at the glacier outlets were used to evaluate the model performance. Basin hydrology was simulated over two periods, 1965–1975 and 2008–2018, using the observed glacier configurations for those time periods. Both basins have undergone continuous glacier loss over the last 3 to 5 decades, leading to a 6 %–31 % reduction in glacierized area, a 78 %–109 % increase in ice exposure, and changes to the elevation and slope of the glacier surfaces. Air temperatures are increasing, mainly due to increasing winter maximum and summer minimum daily temperatures. Annual precipitation has increased by less than 11 %, but rainfall ratios have increased by 29 %–44 %. The results show that changes in both climate and glacier configuration have influenced the melt rates and runoff and a shift of peak flows in the Peyto Glacier basin from August to July. Glacier melt contributions increased/decreased from 27 %–61 % to 43 %–59 % of the annual discharges. Recent discharges were 3 %–19 % higher than in the 1960s and 1970s. The results suggest that increased exposure of glacier ice and lower surface elevation due to glacier thinning were less influential than climate warming in increasing streamflow. Streamflow from these glaciers continues to increase.

Seasonality of Glacial Snow and Ice Microbial Communities.

Blooms of microalgae on glaciers and ice sheets are amplifying surface ice melting rates, which are already affected by climate change. Most studies on glacial microorganisms (including snow and glacier ice algae) have so far focused on the spring and summer melt season, leading to a temporal bias, and a knowledge gap in our understanding of the variations in microbial diversity, productivity, and physiology on glacier surfaces year-round. Here, we investigated the microbial communities from Icelandic glacier surface snow and bare ice habitats, with sampling spanning two consecutive years and carried out in both winter and two summer seasons. We evaluated the seasonal differences in microbial community composition using Illumina sequencing of the 16S rRNA, 18S rRNA, and ITS marker genes and correlating them with geochemical signals in the snow and ice. During summer, Chloromonas, Chlainomonas, Raphidonema, and Hydrurus dominated surface snow algal communities, while Ancylonema and Mesotaenium dominated the surface bare ice habitats. In winter, algae could not be detected, and the community composition was dominated by bacteria and fungi. The dominant bacterial taxa found in both winter and summer samples were Bacteriodetes, Actinobacteria, Alphaproteobacteria, and Gammaproteobacteria. The winter bacterial communities showed high similarities to airborne and fresh snow bacteria reported in other studies. This points toward the importance of dry and wet deposition as a wintertime source of microorganisms to the glacier surface. Winter samples were also richer in nutrients than summer samples, except for dissolved organic carbon—which was highest in summer snow and ice samples with blooming microalgae, suggesting that nutrients are accumulated during winter but primarily used by the microbial communities in the summer. Overall, our study shows that glacial snow and ice microbial communities are highly variable on a seasonal basis.

A comprehensive dataset of microbial abundance, dissolved organic carbon, and nitrogen in Tibetan Plateau glaciers

Abstract. Glaciers are recognized as a biome dominated by microorganisms and a reservoir of organic carbon and nutrients. Global warming remarkably increases glacier melting rate and runoff volume, which have significant impacts on the carbon and nitrogen cycles in downstream ecosystems. The Tibetan Plateau (TP), dubbed “the water tower of Asia”, owns the largest mountain glacial area at mid- and low-latitudes. However, limited data on the microbial abundance, organic carbon, and nitrogen in TP glaciers are available in the literature, which severely hinders our understanding of the regional carbon and nitrogen cycles. This work presents a new dataset on microbial abundance, dissolved organic carbon (DOC), and total nitrogen (TN) for TP glaciers. In this dataset, there are 5409 records from 12 glaciers for microbial abundance in ice cores and snow pits, and 2532 records from 38 glaciers for DOC and TN in the ice core, snow pit, surface ice, surface snow, and proglacial runoff. These glaciers are located across diverse geographic and climatic regions, where the multiyear average air temperature ranges from −13.4 to 2.9 ∘C and the multiyear average precipitation ranges from 76.9 to 927.8 mm. This makes the constructed dataset qualified for large-scale studies across the TP. To the best of our knowledge, this is the first dataset of microbial abundance and TN in TP glaciers and also the first dataset of DOC in ice cores of the TP. This new dataset provides important information for studies on carbon and nitrogen cycles in glacial ecosystems, and is especially valuable for the assessment of potential impacts of glacier retreat on downstream ecosystems under global warming. The dataset is available from the National Tibetan Plateau/Third Pole Environment Data Center (https://doi.org/10.11888/Cryos.tpdc.271841; Liu, 2021).

Exploring snow distribution dynamics in steep forested slopes with UAV-borne LiDAR

Mapping snow in forests is important for understanding the snow cover dynamics in these environments in view of hydrological applications and water resources management. Today, Uncrewed Aerial Vehicles (UAVs) are widely used for snow studies due to their rather cheap and flexible operation. UAV-borne Light detection and ranging (LiDAR) systems are a promising technology for sub-canopy snow mapping at high temporal resolutions, concurrently providing information on both the canopy and the below-canopy snow surface. In this pilot study, we used a UAV-LiDAR system to investigate the snow cover dynamics within two steep forested slopes of opposing aspects in the Swiss Alps at both high spatial resolution and unprecedented temporal resolution. Using a Distance to Canopy Edge (DCE) algorithm to characterize local forest structure, snow depth was analyzed in terms of relative position within variable forest cover. The north-exposed site had higher mean snow depths throughout the season compared to the south-exposed site, especially in canopy gaps. Whereas snow depletion rate was consistent throughout the north-exposed site, snow depletion was much faster in the gaps at the south-exposed slope. Correlation coefficients between snow depths and local canopy closure were weaker at the south-exposed (between −0.5 and − 0.7) than at the north-exposed site (between −0.7 and − 0.9), and rapidly deteriorated right after the peak of winter at the south-exposed slope. This indicates shortwave radiation dominates snowmelt processes at this site, which was thought to be spatially uncorrelated to local canopy cover, unlike accumulation and melt processes on the north-exposed slope that generated snow patterns with a high spatial correlation to local canopy cover throughout the entire season. Calculations of incoming sub-canopy shortwave radiation (SWR) for both sites confirmed this assumption. While our findings encourage the use of UAV-borne LiDAR for further investigations of snow cover dynamics in steep forested slopes, we also outline and discuss technical challenges specific to this application. Our insights allow deriving useful recommendations for future studies using UAV-borne LiDAR over a similar environment.

Divergence of apparent and intrinsic snow albedo over a season at a sub-alpine site with implications for remote sensing

Abstract. Intrinsic albedo is the bihemispherical reflectance independent of effects of topography or surface roughness. Conversely, the apparent albedo is the reflected radiation divided by the incident and may be affected by topography or roughness. For snow, the surface is often rough, and these two optical quantities have different uses: intrinsic albedo is used in scattering equations whereas apparent albedo should be used in energy balance models. Complementing numerous studies devoted to surface roughness and its effect on snow reflectance, this work analyzes a time series of intrinsic and apparent snow albedos over a season at a sub-alpine site using an automated terrestrial laser scanner to map the snow surface topography. An updated albedo model accounts for shade, and in situ albedo measurements from a field spectrometer are compared to those from a spaceborne multispectral sensor. A spectral unmixing approach using a shade endmember (to address the common problem of unknown surface topography) produces grain size and impurity solutions; the modeled shade fraction is compared to the intrinsic and apparent albedo difference. As expected and consistent with other studies, the results show that intrinsic albedo is consistently greater than apparent albedo. Both albedos decrease rapidly as ablation hollows form during melt, combining effects of impurities on the surface and increasing roughness. Intrinsic broadband albedos average 0.056 greater than apparent albedos, with the difference being 0.052 in the near infrared or 0.022 if the average (planar) topography is known and corrected. Field measurements of spectral surface reflectance confirm that multispectral sensors see the apparent albedo but lack the spectral resolution to distinguish between darkening from ablation hollows versus low concentrations of impurities. In contrast, measurements from the field spectrometer have sufficient resolution to discern darkening from the two sources. Based on these results, conclusions are as follows: (1) impurity estimates from multispectral sensors are only reliable for relatively dirty snow with high snow fraction; (2) a shade endmember must be used in spectral mixture models, even for in situ spectroscopic measurements; and (3) snow albedo models should produce apparent albedos by accounting for the shade fraction. The conclusion re-iterates that albedo is the most practical snow reflectance quantity for remote sensing.

Intercomparison Experiment of Water-Insoluble Carbonaceous Particles in Snow in a High-Mountain Environment (1598 m a.s.l.)

The harmonization of sampling, sample preparation and laboratory analysis methods to detect carbon compounds in snow requires detailed documentation of those methods and their uncertainties. Moreover, intercomparison experiments are needed to reveal differences and quantify the uncertainties further. Here, we document our sampling, filtering, and analysis protocols used in the intercomparison experiment from three laboratories to detect water-insoluble carbon in seasonal surface snow in the high-mountain environment at Kolm Saigurn (47.067842° N, 12.98394° E, alt 1598 m a.s.l.), Austria. The participating laboratories were TU Wien (Austria), the University of Florence (Italy), and the Finnish Meteorological Institute (Finland). For the carbon analysis, the NIOSH5040 and EUSAAR2 protocols of the OCEC thermal-optical method were used. The median of the measured concentrations of total carbon (TC) was 323 ppb, organic carbon (OC) 308 ppb, and elemental carbon (EC) 16 ppb. The methods and protocols used in this experiment did not reveal large differences between the laboratories, and the TC, OC, and EC values of four inter-comparison locations, five meters apart, did not show meter-scale horizontal variability in surface snow. The results suggest that the presented methods are applicable for future research and monitoring of carbonaceous particles in snow. Moreover, a recommendation on the key parameters that an intercomparison experiment participant should be asked for is presented to help future investigations on carbonaceous particles in snow. The work contributes to the harmonization of the methods for measuring the snow chemistry of seasonal snow deposited on the ground.

Host-Associated Phages Disperse across the Extraterrestrial Analogue Antarctica.

Extreme Antarctic conditions provide one of the closest analogues of extraterrestrial environments. Since air and snow samples, especially from polar regions, yield DNA amounts in the lower picogram range, binning of prokaryotic genomes is challenging and renders studying the dispersal of biological entities across these environments difficult. Here, we hypothesized that dispersal of host-associated bacteriophages (adsorbed, replicating, or prophages) across the Antarctic continent can be tracked via their genetic signatures, aiding our understanding of virus and host dispersal across long distances. Phage genome fragments (PGFs) reconstructed from surface snow metagenomes of three Antarctic stations were assigned to four host genomes, mainly Betaproteobacteria, including Ralstonia spp. We reconstructed the complete genome of a temperate phage with nearly complete alignment to a prophage in the reference genome of Ralstonia pickettii 12D. PGFs from different stations were related to each other at the genus level and matched similar hosts. Metagenomic read mapping and nucleotide polymorphism analysis revealed a wide dispersal of highly identical PGFs, 13 of which were detected in seawater from the Western Antarctic Peninsula at a distance of 5,338 km from the snow sampling stations. Our results suggest that host-associated phages, especially of Ralstonia sp., disperse over long distances despite the harsh conditions of the Antarctic continent. Given that 14 phages associated with two R. pickettii draft genomes isolated from space equipment were identified, we conclude that Ralstonia phages are ideal mobile genetic elements to track dispersal and contamination in ecosystems relevant for astrobiology. IMPORTANCE Host-associated phages of the bacterium Ralstonia identified in snow samples can be used to track microbial dispersal over thousands of kilometers across the Antarctic continent, which functions as an extraterrestrial analogue because of its harsh environmental conditions. Due to the presence of these bacteria carrying genome-integrated prophages on space-related equipment and the potential for dispersal of host-associated phages demonstrated here, our work has implications for planetary protection, a discipline in astrobiology interested in preventing contamination of celestial bodies with alien biomolecules or forms of life.