Snow Surface Research Articles

Environmental distribution of per- and polyfluoroalkyl substances (PFAS) on Svalbard: Local sources and long-range transport to the Arctic

The environmental distribution of per- and polyfluoroalkyl substances (PFAS) in water, snow, sediment and soil samples taken along the west coast of Spitsbergen in the Svalbard archipelago, Norwegian Arctic, was determined. The contribution of potential local primary sources (wastewater, firefighting training site at Svalbard airport, landfill) to PFAS concentrations and long-range transport (atmosphere, ocean currents) were then compared, based on measured PFAS levels and composition profiles. In remote coastal and inland areas of Spitsbergen, meltwater had the highest mean ΣPFAS concentration (6.5 ± 1.3 ng L−1), followed by surface snow (2.5 ± 1.7 ng L−1), freshwater (2.3 ± 1.1 ng L−1), seawater (1.05 ± 0.64 ng L−1), lake sediments (0.084 ± 0.038 ng g−1 dry weight (dw)) and marine sediments (<method detection limit (MDL)–0.46 ng g−1 dw, median 0.015 ng g−1 dw). Perfluoroalkyl sulfonates (PFSA) and 6:2 fluorotelomer sulfonate (FTSA) were predominant in water and soil samples influenced by local sources, while perfluoroalkyl carboxylates (PFCA) were predominant in water and sediment from remote coastal and inland areas of Svalbard. The PFAS composition profiles observed in remote areas indicated that atmospheric transport and oxidation of volatile precursors is an important source of PFCA on Svalbard. Shorter-chain PFAS such as perfluorobutanoate (PFBA) were the predominant PFAS in freshwater, reflecting replacement of C8-chained PFAS with shorter-chained compounds. The comparatively high PFAS (especially PFBA) concentration in meltwater indicated that melting of snow and ice during the Arctic spring is an important diffuse local PFAS source. This source may become even more important with climate warming-induced melting of Arctic glaciers and ice sheets. Further studies of mobilisation and transport of PFAS in the Arctic region are needed to confirm this trend.

Evaluation of Ten Fresh Snow Density Parameterization Schemes for Simulating Snow Depth and Surface Energy Fluxes on the Eastern Tibetan Plateau

Snow cover on the Tibetan Plateau has a shallow depth, plaque distribution, and repeated ablation. The applicability of the snow parameterization scheme in the current land surface process model on the TP needs to be further tested using observational data. In this paper, using the land surface process model CLM4.5 and ten fresh snow density parameterization schemes characterized by temperature, wind speed, and relative humidity, three discontinuous snow processes in Maqu, Madoi, and Yakou and two continuous snow processes in Madoi and Yakou were simulated. By comparing the simulated snow depth with the observed, it was found that this model can clearly describe repeated snow accumulation and ablation processes for the discontinuous snow cover process. The KW scheme, compared with the original Anderson scheme, performed the best regarding snow depth simulation. However, all schemes overestimated the melting rate of snow, and were not able to simulate continuous snow accumulation. The simulation effect of the Schmucki scheme on radiation and energy flux under discontinuous snow cover was significantly improved compared with other scheme. None of schemes performed perfectly, so future studies that focus on the simulations of snow depth, radiation flux, and energy flux under continuous snow cover for accurate and wide applications are recommended.

Evaluating Snow Microwave Radiative Transfer (SMRT) model emissivities with 89 to 243 GHz observations of Arctic tundra snow

Abstract. Improved modelling of snow emissivity is needed to improve the assimilation of surface-sensitive atmospheric sounding observations from satellites in polar regions for numerical weather prediction (NWP). This paper evaluates emissivity simulated with the Snow Microwave Radiative Transfer (SMRT) model using observations of Arctic tundra snow at frequencies between 89 and 243 GHz. Measurements of snow correlation length, density and layer thickness were used as input to SMRT, and an optimisation routine was used to assess the impact of each parameter on simulations of emissivity when compared to a set of Lambertian emissivity spectra, retrieved from observations of tundra snow from three flights of the Facility for Airborne Atmospheric Measurements (FAAM) aircraft. Probability distributions returned by the optimisation routine demonstrate parameter uncertainties and the sensitivity of simulations to the different snow parameters. Results showed that SMRT was capable of reproducing a range of observed emissivities between 89 and 243 GHz. Varying correlation length alone allowed SMRT to capture much of the variability in the emissivity spectra; however, MAE (MAPE) decreased from 0.018 (3.0 %) to 0.0078 (1.2 %) overall when the thickness of the snow layers was also varied. When all three parameters were varied, simulations were similarly sensitive to both correlation length and density, although the influence of density was most evident when comparing spectra from snowpacks with and without surface snow. Simulations were most sensitive to surface snow and wind slab parameters, while sensitivity to depth hoar depended on the thickness and scattering strength of the layers above, demonstrating the importance of representing all three parameters for multi-layer snowpacks when modelling emissivity spectra. This work demonstrates the ability of SMRT to simulate snow emissivity at these frequencies and is a key step in the progress towards modelling emissivity for data assimilation in NWP.

Bromine, iodine and sodium along the EAIIST traverse: Bulk and surface snow latitudinal variability

During the East Antarctic International Ice Sheet Traverse (Eaiist, december 2019), in an unexplored part of the East Antarctic Plateau, snow samples were collected to expand our knowledge of the latitudinal variability of iodine, bromine and sodium as well as their relation in connection with emission processes and photochemical activation in this unexplored area. A total of 32 surface (0–5 cm) and 32 bulk (average of 1 m depth) samples were taken and analysed by Inductively Coupled Plasma Mass Spectrometry (ICP-MS). Our results show that there is no relevant latitudinal trend for bromine and sodium. For bromine they also show that it has no significant post-depositional mechanisms while its inland surface snow concentration is influenced by spring coastal bromine explosions. Iodine concentrations are several orders of magnitude lower than bromine and sodium and they show a decreasing trend in the surface samples concentration moving southward. This suggests that other processes affect its accumulation in surface snow, probably related to the radial reduction in the ozone layer moving towards central Antarctica. Even though all iodine, bromine and sodium present similar long-range transport from the dominant coastal Antarctic sources, the annual seasonal cycle of the ozone hole over Antarctica increases the amount of UV radiation (in the 280–320 nm range) reaching the surface, thereby affecting the surface snow photoactivation of iodine. A comparison between the bulk and surface samples supports the conclusion that iodine undergoes spring and summer snow recycling that increases its atmospheric lifetime, while it tends to accumulate during the winter months when photochemistry ceases.

Field study on the diffusion and advection effects of vehicle-emitted soot aerosols on snow albedo in the Chilean Andes

Emissions from road traffic are one of the most important sources of soot aerosols and they can affect the surfaces in the area. In the case of snow surfaces, this effect may lead to changes in the radiative forcing and snow melt, also influenced by particle transport such as particle diffusion and advection. An experimental campaign in The Andes, Chile, was carried out measuring the radiance and irradiance of the snow perpendicularly to a road with high traffic load, together with the meteorological conditions (to identify the diffusion and advection phenomena), the aerosol size distribution, the concentration of particles (PM1, PM2.5 and PM10), and the concentration of black carbon (BC) in both, the atmosphere and the snowpack. The aim of the study was to quantify the contribution of four factors affecting the albedo (black carbon -BC- concentration in snow, grain size, cloudiness, and roughness) by comparing the measured albedo of the contaminated snow surface with that of the same surface prior to contamination, considered as a reference. Results showed a trade-off between diffusion and advection. Close to the road, diffusion was predominant, leading to an increase in BC concentration and a reduction in snow albedo. On the contrary, far from the road, where winds are channeled along the centre of the valley, advection of particles became dominant, leading to another increase in particle concentration and another reduction in snow albedo. Among the factors contributing to reduce the snow albedo, BC concentration dominates at all distances from the road, although the effect of the grain size becomes as significant as that of BC in the centre of the valley, with the effects of surface roughness and cloudiness remaining minor. This information can be used in snow models to get a better knowledge of the effect of particle deposition on albedo reductions.

Stratigraphic noise and its potential drivers across the plateau of Dronning Maud Land, East Antarctica

Abstract. Stable water isotopologues of snow, firn and ice cores provide valuable information on past climate variations. Yet single profiles are generally not suitable for robust climate reconstructions. Stratigraphic noise, introduced by the irregular deposition, wind-driven erosion and redistribution of snow, impacts the utility of high-resolution isotope records, especially in low-accumulation areas. However, it is currently unknown how stratigraphic noise differs across the East Antarctic Plateau and how it is affected by local environmental conditions. Here, we assess the amount and structure of stratigraphic noise at seven sites along a 120 km transect on the plateau of Dronning Maud Land, East Antarctica. Replicated oxygen isotope records of 1 m length were used to estimate signal-to-noise ratios as a measure of stratigraphic noise at sites characterised by different accumulation rates (43–64 mm w.e. a−1), snow surface roughnesses and slope inclinations. While we found a high level of stratigraphic noise at all sites, there was also considerable variation between sites. At sastrugi-dominated sites, greater stratigraphic noise coincided with stronger surface roughnesses, steeper slopes and lower accumulation rates, probably related to increased wind speeds. These results provide a first step to modelling stratigraphic noise and might guide site selection and sampling strategies for future expeditions to improve high-resolution climate reconstructions from low-accumulation regions.

INFLUENCE OF AGRICULTURAL PRACTICES ON THE PROCESS OF SOIL FREEZING

Only the change in soil temperature with time has been systematically studied on different types of soils. At the same time, many agricultural practices aim to regulate the soil’s temperature regime. Thus, snow retention and mulching with plant residues are effective measures aimed at increasing the temperature of the surface layers of the earth. In the article, the authors investigated the process of world freezing with a mulched surface under a layer of snow covered with an ice crust. Methods of theoretical analysis (structuralfunctional, systemic approach) and mathematical statistics are used. The authors conducted field studies in two versions at LLC “Plemsovkhoz” Kenzhe “of the Kabardino-Balkarian Republic. The first option is bare soil, and the second option is mulched soil with the creation of an ice crust on the snow surface in winter. Studies were carried out on the influence of the mulching layer of vegetation and the ice crust on the snow surface on the annual variation in soil surface temperature and soil temperature. These study results indicate that mulching the soil surface with plant residues and creating an ice crust on the snow surface contributes to the “smoothing” of the soil temperature. So, when using the proposed technological methods, the temperature of the soil with a change in depth from 0 to 100 cm changes from 0°С to +2.5 °С, while without their use - from -3 °С to +2 °С. The authors proved that the temperature of the soil at a depth of 30 cm, when using the proposed technological methods, reaches above 0 °C. This confirms the effectiveness of these techniques in preventing dirt freezing.

A Surface Radiation Balance Dataset from Siple Dome in West Antarctica for Atmospheric and Climate Model Evaluation

Abstract A field campaign at Siple Dome in West Antarctica during the austral summer 2019/20 offers an opportunity to evaluate climate model performance, particularly cloud microphysical simulation. Over Antarctic ice sheets and ice shelves, clouds are a major regulator of the surface energy balance, and in the warm season their presence occasionally induces surface melt that can gradually weaken an ice shelf structure. This dataset from Siple Dome, obtained using transportable and solar-powered equipment, includes surface energy balance measurements, meteorology, and cloud remote sensing. To demonstrate how these data can be used to evaluate model performance, comparisons are made with meteorological reanalysis known to give generally good performance over Antarctica (ERA5). Surface albedo measurements show expected variability with observed cloud amount, and can be used to evaluate a model’s snowpack parameterization. One case study discussed involves a squall with northerly winds, during which ERA5 fails to produce cloud cover throughout one of the days. A second case study illustrates how shortwave spectroradiometer measurements that encompass the 1.6-μm atmospheric window reveal cloud phase transitions associated with cloud life cycle. Here, continuously precipitating mixed-phase clouds become mainly liquid water clouds from local morning through the afternoon, not reproduced by ERA5. We challenge researchers to run their various regional or global models in a manner that has the large-scale meteorology follow the conditions of this field campaign, compare cloud and radiation simulations with this Siple Dome dataset, and potentially investigate why cloud microphysical simulations or other model components might produce discrepancies with these observations. significance statement Antarctica is a critical region for understanding climate change and sea level rise, as the great ice sheets and the ice shelves are subject to increasing risk as global climate warms. Climate models have difficulties over Antarctica, particularly with simulation of cloud properties that regulate snow surface melting or refreezing. Atmospheric and climate-related field work has significant challenges in the Antarctic, due to the small number of research stations that can support state-of-the-art equipment. Here we present new data from a suite of transportable and solar-powered instruments that can be deployed to remote Antarctic sites, including regions where ice shelves are most at risk, and we demonstrate how key components of climate model simulations can be evaluated against these data.

Snow algal blooms in Antarctic King George Island in 2017–2022 and their future trend based on CMIP6 projection

Snow algal blooms have a remarkable climatic or environmental effect through influencing the snow–albedo feedback, accelerating the melting of surface snow, and amplifying global warming. Snow algal blooms occurred frequently on King George Island, Antarctic, during the recent six austral summers (December to next February) through 2017–2022. Based on an assessment of satellite images, this study found that the range and amount of snow algal blooms in the summers of 2018, 2020, 2021 and 2022 are relatively larger than in the summers of 2017 and 2019. Whether meteorological conditions have shaped the year-to-year variation of algal bloom intensities is analyzed through observational composite. The results suggest that during the strong bloom summers there exist prevailing northerly or northwesterly wind anomalies which advect warm and humid airmass from the southern ocean into the island, increasing surface air temperature and humidity; the warmer and more humid surface favors melting of snow and an increase of low cloud cover, subsequently enhancing the atmospheric downward long-wave radiation and amplifying surface warmth; the increased low cloud cover reflects more ultraviolet rays back to space and weakens the short-wave radiation reaching the surface. All these factors together favor to a stronger bloom. In comparison, during 2017 and 2019 there exist weak southerly wind anomalies which induce the northward advection of cold and dry air from the Antarctic Continent and favor the cooler surface. Consequently, it is unfavorable for the snow algal bloom. Based on these results, a snow algal bloom potential index (API) integrating the meteorological conditions is constructed, and its future trend is projected based on the EC-Earth3 run attending the CMIP6 under SSP245 and SSP585. A significant increasing trend is projected especially under SSP585. Thus snow algal bloom on King George Island will become more frequent and stronger in future. This implies a potential accelerate melting of ice shelf over Antarctic Peninsula.

Changes in Snow Surface Albedo and Radiative Forcing in the Chilean Central Andes Measured by In Situ and Remote Sensing Data

Snow-covered regions are the main source of reflection of incident shortwave radiation on the Earth’s surface. The deposition of light-absorbing particles on these regions increases the capacity of snow to absorb radiation and decreases surface snow albedo, which intensifies the radiative forcing, leading to accelerated snowmelt and modifications of the hydrologic cycle. In this work, the changes in surface snow albedo and radiative forcing were investigated, induced by light-absorbing particles in the Upper Aconcagua River Basin (Chilean Central Andes) using remote sensing satellite data (MODIS), in situ spectral snow albedo measurements, and the incident shortwave radiation during the austral winter months (May to August) for the 2004–2016 period. To estimate the changes in snow albedo and radiative forcing, two spectral ranges were defined: (i) an enclosed range between 841 and 876 nm, which isolates the effects of black carbon, an important light-absorbing particle derived from anthropogenic activities, and (ii) a broadband range between 300 and 2500 nm. The results indicate that percent variations in snow albedo in the enclosed range are higher than in the broadband range, regardless of the total amount of radiation received, which may be attributed to the presence of light-absorbing particles, as these particles have a greater impact on surface snow albedo at wavelengths in the enclosed band than in the broadband band.

Development of an Autonomous Measurement System for Estimation of Snow Profile on Road Surfaces

This paper presents the development of a novel prototype system to measure the profile of snow and detect ice on road surfaces. While researchers have previously developed methods to estimate the tire-road friction coefficient, methods to create a high resolution map of snow cover and ice on roads have not been developed. The prototype and data processing methods presented in this study provide a potential solution that would greatly benefit winter road maintenance teams. Having a device capable of creating a detailed map of snow and ice cover on roads would allow for more efficient plowing and salt deployment, better informing of the public about current road conditions, as well as better analysis of current plowing techniques to improve winter road maintenance operations. The measurement of the snow profile is based on the use of two types of inexpensive ranging sensors mounted on a rotationally controlled stepper motor platform. The technical challenges addressed in the development include analysis of the scan path over which the system scans the road, differentiation between asphalt, concrete, and snow surfaces using reflection amplitudes, accurate transformation of raw distance measurements to inertial coordinates, and identification of the Euler angles of the sensors using parameters associated with the scanned surface profile. Extensive experimental results and test data are presented, which show that the system is capable of measuring the snow profile on a road with an accuracy of ±1 cm when a reasonable portion of bare road is visible, and ±2 cm when only small portions of bare road are visible.

Impacts of snow surface aerodynamic resistance on snow water equivalent simulations in forested regions

AbstractThe aerodynamic resistance at the snow surface (ras) has an influence on the snowpack energy balance. However, there are no widely accepted approaches for parameterizing ras in forested regions. In this study, we derived ras under the influence of forest vegetation for five cases that depend on the canopy height and structure. Three parameterization schemes for ras were then integrated into a distributed hydrologic model: (1) the aerodynamic resistance above the canopy, ignoring the canopy structure effects on ras, (2) the full aerodynamic resistance formulation for the different canopy height cases, and (3) a simplified formulation that only represented the lower trunk layer. Model simulations were conducted at six snow telemetry (SNOTEL) sites in the Verde River Watershed, Arizona, and evaluated with respect to snow water equivalent (SWE) product from the SNOTEL sites and a gridded product. Results revealed the importance of accurately parameterizing vegetation canopy structure when calculating ras in forested regions. Cases where ras included the vertical structure effects showed improved simulations of SWE across all sites. Finally, ras is mostly determined by trunk layer aerodynamic resistance such that the simplified formulation is sufficient for representing forest canopy effects on ras.

Rewilding Risks for Peatland Permafrost

Permafrost thaw is projected to reinforce climate warming by releasing large stocks of stored carbon. Rewilding northern high latitude regions with large herbivores has been proposed as a climate mitigation strategy to protect frozen soils and increase ecosystem resilience to climate warming. We explored the impact of summer reindeer density on subarctic peatlands by comparing 17 peatlands differing in reindeer density in Fennoscandia. We used a combination of high-resolution image analyses and field assessments along 50 transects to assess microtopography, surface water cover, vegetation, summer albedo, permafrost presence, soil temperature, soil nutrients and snow depth. Our results show that high summer reindeer densities fragment the characteristic bumpy topography of the peatlands, reducing the insulating soil properties and the probability of keeping permafrost in elevated hummocks. As a result, waterlogged lawns with surface water increase in size and reduce summer albedo. Furthermore, high reindeer density peatlands were associated with an increase in tall inedible shrubs and thicker snow layers. These changes may favor summer warming and reduce winter cooling of the soil thus accelerating permafrost loss. Our results suggest that high reindeer densities may reduce resilience of the peatland permafrost to climate warming. High densities of large herbivores will likely have different effects in well-drained uplands, but in the lowlands we studied, the complex cascading effects of summer trampling may well offset any climate-protection gained by browsing. Optimal use of wildlife management to mitigate global warming will thus require tuning herbivore densities to different ecosystem types across high northern landscapes.

Seasonality Is the Main Determinant of Microbial Diversity Associated to Snow/Ice around Concordia Station on the Antarctic Polar Plateau.

The French-Italian Concordia Research Station, situated on the Antarctic Polar Plateau at an elevation of 3233 m above sea level, offers a unique opportunity to study the presence and variation of microbes introduced by abiotic or biotic vectors and, consequently, appraise the amplitude of human impact in such a pristine environment. This research built upon a previous work, which explored microbial diversity in the surface snow surrounding the Concordia Research Station. While that study successfully characterized the bacterial assemblage, detecting fungal diversity was hampered by the low DNA content. To address this knowledge gap, in the present study, we optimized the sampling by increasing ice/snow collected to leverage the final DNA yield. The V4 variable region of the 16S rDNA and Internal Transcribed Spacer (ITS1) rDNA was used to evaluate bacterial and fungal diversity. From the sequencing, we obtained 3,352,661 and 4,433,595 reads clustered in 930 and 3182 amplicon sequence variants (ASVs) for fungi and bacteria, respectively. Amplicon sequencing revealed a predominance of Basidiomycota (49%) and Ascomycota (42%) in the fungal component; Bacteroidota (65.8%) is the main representative among the bacterial phyla. Basidiomycetes are almost exclusively represented by yeast-like fungi. Our findings provide the first comprehensive overview of both fungal and bacterial diversity in the Antarctic Polar Plateau's surface snow/ice near Concordia Station and to identify seasonality as the main driver of microbial diversity; we also detected the most sensitive microorganisms to these factors, which could serve as indicators of human impact in this pristine environment and aid in planetary protection for future exploration missions.

The edge-on protoplanetary disk HH 48 NE

Context. The abundance and distribution of ice in protoplanetary disks is critical for an understanding of the link between the composition of circumstellar matter and the composition of exoplanets. Edge-on protoplanetary disks are a useful tool for constraining this ice composition and its location in the disk because the spectral signatures of the ice can be observed in absorption against the continuum emission that arises from the warmer regions in the central disk. Aims. The aim of this work is to model ice absorption features in protoplanetary disks and to determine how well the abundance of the main ice species throughout the disk can be determined within the uncertainty of the physical parameter space. The edge-on proto-planetary disk around HH 48 NE, a target of the James Webb Space Telescope Early Release program Ice Age, is used as a reference system. Methods. We used the full anisotropic scattering capabilities of the radiative transfer code RADMC-3D to ray-trace the mid-infrared continuum. Using a constant parameterized ice abundance, we added ice opacities to the dust opacity in regions in which the disk was cold enough for the main carbon, oxygen, and nitrogen carriers to freeze out. Results. The global abundance relative to the dust content of the main ice carriers in HH 48 NE can be determined within a factor of 3 when the uncertainty of the physical parameters is taken into account. Ice features in protoplanetary disks can be saturated at an optical depth of ≲1 due to local saturation. Ices are observed at various heights in the disk model, but in this model, spatial information is lost for features at wavelengths &gt;7 µm when observing with James Webb Space Telescope because the angular resolution decreases towards longer wavelengths. Spatially observed ice optical depths cannot be directly related to column densities, as would be the case for direct absorption against a bright continuum source, because of radiative transfer effects. Vertical snowlines will not be a clear transition because the height of the snow surface increases radially, but their location may be constrained from observations using radiative transfer modeling. Radial snowlines are not really accessible. Not only the ice abundance, but also the inclination, the settling, the grain size distribution, and the disk mass have a strong impact on the observed ice absorption features in disks. Relative changes in the ice abundance can only be inferred from observations if the source structure is well constrained.

Characterization of hollow glass microspheres with potential for regional climate intervention to preserve snow and ice surfaces

Cold regions including the Arctic are warming fast, resulting in increased losses of snow and ice cover. A climate intervention approach, where hollow glass microspheres (HGMs) are applied on snow and ice surfaces such as Artic sea ice has been suggested for ice preservation. HGMs are commercial materials, typically in the 10–200 μm diameter size range. They are very lightweight, highly reflective materials with a high crush strength. It is suggested that through that reflectivity, their application onto snow and ice surfaces can increase the albedo, and thus stabilize snow and ice covers, for example aid the formation of multiyear sea ice. In this study we tested the stability and behaviour of different HGMs under stress conditions to gain knowledge on their potential environmental fate. Stability tests, measured as maintenance of positive buoyancy, during sediment interaction, repeated freezing and thawing and prolonged exposure in seawater showed differences in environmental stability of the tested materials with stability depending on wall thickness and surface integrity. None of the tested materials seemed to be very susceptible to biofouling under the conditions tested. However, leaching of elements, especially Si was observed for some materials, potentially indicating dissolution of the HGMs in seawater over time. Further studies are needed to determine the element dissolution from HGMs and other potential environmental implications such as impacts on organisms. Although this paper is directed towards using HGMs in a local climate intervention application the findings may be of general interest for other uses of HGM materials.

Diagnosis of Antarctic Blowing Snow Properties Using MERRA-2 Reanalysis with a Machine Learning Model

Abstract This paper presents work using a machine learning model to diagnose Antarctic blowing snow (BLSN) properties with the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), data. We adopt the random forest classifier for BLSN identification and the random forest regressor for BLSN optical depth and height diagnosis. BLSN properties observed from the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) are used as the truth for training the model. Using MERRA-2 fields such as snow age, surface elevation and pressure, temperature, specific humidity, and temperature gradient at the 2-m level, and wind speed at the 10-m level as input, reasonable results are achieved. Hourly blowing snow property diagnostics are generated with the trained model. Using 2010 as an example, it is shown that the Antarctic BLSN frequency is much higher over East than West Antarctica. High-frequency months are from April to September, during which BLSN frequency exceeds 20% over East Antarctica. For May 2010, the BLSN snow frequency in the region is as high as 37%. Due to the suppression by strong surface-based inversions, larger values of BLSN height and optical depth are usually limited to the coastal regions, wherein the strength of surface-based inversions is weaker.

A Submonthly Scale Causal Relation between Snow Cover and Surface Air Temperature over the Autumnal Eurasian Continent

Abstract Snow cover (SC) is an important contributor to atmospheric predictability on subseasonal to seasonal time scales. This paper evaluates the submonthly scale cause-and-effect relationship between SC and surface air temperature (SAT) in Eurasia, which has been typically overlooked in previous statistical analyses of subseasonal to seasonal atmospheric predictability. We focus on the November east–west dipolar SC pattern, a dominant large-scale SC phenomenon. We use an information flow analysis, based on information theory, to infer causal relations not revealed by conventional correlation analysis. This analysis indicates a one-way causality from SAT to SC around the west pole (Europe) in boreal autumn (November), implying that SC has little influence on the time evolution of SAT. In contrast, causality from SC to SAT is significant around the east pole (the Mongolian Plateau). An atmospheric model experiment suggests that the SAT response to SC can persist for a month via snow–albedo feedback, although the response of the upper atmosphere in the model is small. Furthermore, the subseasonal hindcasts show that the contribution of SC may affect the predictability of SAT for up to four weeks around the east pole. We suggest that the geographical and climatological atmospheric conditions are favorable for generating a positive albedo feedback as a “hotspot” of SC–SAT coupling around the east pole in autumn. The agreement of our causality analysis with other analytical and modeling approaches underscores the cause-and-effect relationship between SC and SAT and its contribution to the subseasonal predictability over autumnal Eurasia.

Evaluation of snow depth retrievals from ICESat-2 using airborne laser-scanning data

Abstract. The unprecedented precision of satellite laser altimetry data from the NASA ICESat-2 mission and the increasing availability of high-resolution elevation datasets open new opportunities to measure snow depth in mountains, a critical variable for ecosystem and water resource monitoring. We retrieved snow depth over the upper Tuolumne basin (California, USA) for 3 years by differencing ICESat-2 ATL06 snow-on elevations and various snow-off digital elevation models. Snow depth derived from ATL06 data only (snow-on and snow-off) offers a poor temporal and spatial coverage, limiting its potential utility. However, using a digital terrain model from airborne lidar surveys as the snow-off elevation source yielded a snow depth accuracy of ∼ 0.2 m (bias) and precision of ∼ 1 m (random error) across the basin, with an improved precision of 0.5 m for low slopes (&lt; 10∘), compared to eight reference airborne lidar snow depth maps. Snow depths derived from ICESat-2 ATL06 and a satellite photogrammetry digital elevation model have a larger bias and reduced precision, partly induced by increased errors in forested areas. These various combinations of repeated ICESat-2 snow surface elevation measurements with satellite or airborne products will enable tailored approaches to map snow depth and estimate water resource availability in mountainous areas with limited snow depth observations.

Improving modelled albedo over the Greenland ice sheet through parameter optimisation and MODIS snow albedo retrievals

Abstract. Greenland ice sheet mass loss continues to accelerate as global temperatures increase. The surface albedo of the ice sheet determines the amount of absorbed solar energy, which is a key factor in driving surface snow and ice melting. Satellite-retrieved snow albedo allows us to compare and optimise modelled albedo over the entirety of the ice sheet. We optimise the parameters of the albedo scheme in the ORCHIDEE (Organizing Carbon and Hydrology in Dynamic Ecosystems) land surface model for 3 random years taken over the 2000–2017 period and validate over the remaining years. In particular, we want to improve the albedo at the edges of the ice sheet, since they correspond to ablation areas and show the greatest variations in runoff and surface mass balance. By giving a larger weight to points at the ice sheet's edge, we improve the model–data fit by reducing the root-mean-square deviation by over 25 % for the whole ice sheet for the summer months. This improvement is consistent for all years, even those not used in the calibration step. We also show the optimisation successfully improves the model–data fit at 87.5 % of in situ sites from the PROMICE (Programme for Monitoring of the Greenland Ice Sheet) network. We conclude by showing which additional model outputs are impacted by changes to the albedo parameters, encouraging future work using multiple data streams when optimising these parameters.