Snow Thickness Research Articles

Influence of the Thickness of Freezing of the Soil Surface and Snow Cover on Methane Emissions during Freezing of Seasonal Permafrost

Methane, a type of greenhouse gas, poses considerable concern for humans. This study uses field experiments and satellite measurements to explore methane emission mechanisms during the freezing of seasonal permafrost and the contributing factors. In the transitional seasons of autumn and winter, as soil begins to freeze, methane emissions surge dramatically in a brief period. During this phase, the emissions peak, enabling the soil to accumulate over 9000 mg/m3 of methane rapidly. Snow cover also plays a crucial role in mitigating methane emissions. The porous nature of a sufficiently thick snow cover aids in temporarily trapping methane through a stratified blocking process, effectively matching the inhibitory capability of unfrozen soil. In comparison to unfrozen soil (54–237 mg/m3), snow cover can suppress methane emissions up to 20 times more, reducing emissions by as much as 3399 mg/m3.

Quantifying the influence of snow over sea ice morphology on L-band passive microwave satellite observations in the Southern Ocean

Abstract. Antarctic snow on sea ice can contain slush, snow ice, and stratified layers, complicating satellite retrieval processes for snow depth, ice thickness, and sea ice concentration. The presence of moist and brine-wetted snow alters microwave snow emissions and modifies the energy and mass balance of sea ice. This study assesses the impact of brine-wetted snow and slush layers on L-band surface brightness temperatures (TBs) by synergizing a snow stratigraphy model (SNOWPACK) driven by atmospheric reanalysis data and the RAdiative transfer model Developed for Ice and Snow in the L-band (RADIS-L) v1.0 The updated RADIS-L v1.1 further introduces parameterizations for brine-wetted snow and slush layers over Antarctic sea ice. Our findings highlight the importance of including both brine-wetted snow and slush layers in order to accurately simulate L-band brightness temperatures, laying the groundwork for improved satellite retrievals of snow depth and ice thickness using satellite sensors such as Soil Moisture and Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP). However, biases in modelled and observed L-band brightness temperatures persist, which we attribute to small-scale sea ice heterogeneity and snow stratigraphy. Given the scarcity of comprehensive in situ snow and ice data in the Southern Ocean, ramping up observational initiatives is imperative to not only provide satellite validation datasets but also improve process-level understanding that can scale up to improving the precision of satellite snow and ice thickness retrievals.

Reconstructing Younger Dryas ground temperature and snow thickness from cave deposits

Abstract. The Younger Dryas stadial was characterised by a rapid shift towards cold-climate conditions in the North Atlantic realm during the last deglaciation. While some climate parameters including atmospheric temperature and glacier extent are widely studied, empirical constraints on permafrost temperature and snow thickness are limited. To address this, we present a regional dataset of cryogenic cave carbonates (CCCs) from three caves in Great Britain that formed at temperatures between −2 and 0 °C. Our CCC record indicates that these permafrost temperatures persisted for most of the Younger Dryas. By combining ground temperatures with surface temperatures from high-resolution ground-truthed model simulations, we demonstrate that ground temperatures were approximately 6.6 ± 2.3 °C warmer than the mean annual air temperature. Our results suggest that the observed temperature offset between permafrost and the atmosphere can be explained by an average snow thickness between 0.2 and 0.9 m, which persisted for 233 ± 54 d per year. By identifying modern analogues from climate reanalysis data, we demonstrate that the inferred temperature and snow cover characteristics for the British Isles during the Younger Dryas are best explained by extreme temperature seasonality, comparable to continental parts of today's Arctic Archipelago. Such a climate for the British Isles necessitates a winter sea ice margin at approximately 45° N in the North Atlantic Ocean.

Sea ice mass balance during the MOSAiC drift experiment: Results from manual ice and snow thickness gauges

Precise measurements of Arctic sea ice mass balance are necessary to understand the rapidly changing sea ice cover and its representation in climate models. During the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition, we made repeat point measurements of snow and ice thickness on primarily level first- and second-year ice (FYI, SYI) using ablation stakes and ice thickness gauges. This technique enabled us to distinguish surface and bottom (basal) melt and characterize the importance of oceanic versus atmospheric forcing. We also evaluated the time series of ice growth and melt in the context of other MOSAiC observations and historical mass balance observations from the Surface Heat Budget of the Arctic (SHEBA) campaign and the North Pole Environmental Observatory (NPEO). Despite similar freezing degree days, average ice growth at MOSAiC was greater on FYI (1.67 m) and SYI (1.23 m) than at SHEBA (1.45 m, 0.53 m), due in part to initially thinner ice and snow conditions on MOSAiC. Our estimates of effective snow thermal conductivity, which agree with SHEBA results and other MOSAiC observations, are unlikely to explain the difference. On MOSAiC, FYI grew more and faster than SYI, demonstrating a feedback loop that acts to increase ice production after multi-year ice loss. Surface melt on MOSAiC (mean of 0.50 m) was greater than at NPEO (0.18 m), with considerable spatial variability that correlated with surface albedo variability. Basal melt was relatively small (mean of 0.12 m), and higher than NPEO observations (0.07 m). Finally, we present observations showing that false bottoms reduced basal melt rates in some FYI cases, in agreement with other observations at MOSAiC. These detailed mass balance observations will allow further investigation into connections between the carefully observed surface energy budget, ocean heat fluxes, sea ice, and ecosystem at MOSAiC and during other campaigns.

Estimating snow depth based on dual polarimetric radar index from Sentinel-1 GRD data: A case study in the Scandinavian Mountains

The sensitivity of synthetic aperture radar (SAR) polarization information to snow depth changes provides new opportunities for regional snow depth retrieval in mountains with thick snow cover. However, interference from soil signals can affect the accurate quantification of snow volume scattering signals. The aim of this study was to develop a dual-polarimetric radar snow depth estimation (DpRSE) methodological framework that utilizes Sentinel-1 data for snow depth retrieval in the Scandinavian Mountains. This framework is based on the dual-polarimetric radar vegetation index (DpRVIc), which enhances the snow volume scattering signal and reduces soil interference by integrating soil purity and a conditioning factor to fully exploit the advantages of polarimetric SAR information. The results revealed a strong correlation between the DpRVIc and snow depth, and the DpRVIc significantly outperformed the other polarimetric radar indices. The multitemporal retrieval results clearly reflect the heterogeneity of the snow depth distribution. This method is applicable to areas without tree cover. Meanwhile, the shrub-filled regions also affect the snow depth retrieval accuracy. Under the same environmental conditions and using the same validation dataset, a comparison between the DpRSE method and the cross-polarization ratio method was conducted. The results indicated that the DpRSE method surpasses similar existing methods in terms of snow depth retrieval accuracy. Specifically, the coefficient of determination (R2) for the DpRSE method reached 0.66, which represents a 26.9 % improvement over that of the cross-polarization ratio method. Moreover, the mean absolute error (MAE) decreased by 20 %. This study offers a novel perspective on SAR snow depth retrieval utilizing polarization information.

Modeling the Winter Heat Conduction Through the Sea Ice System During MOSAiC

AbstractModels struggle to accurately simulate observed sea ice thickness changes, which could be partially due to inadequate representation of thermodynamic processes. We analyzed co‐located winter observations of the Arctic sea ice from the Multidisciplinary Drifting Observatory for the Study of the Arctic Climate for evaluating and improving thermodynamic processes in sea ice models, aiming to enable more accurate predictions of the warming climate system. We model the sea ice and snow heat conduction for observed transects forced by realistic boundary conditions to understand the impact of the non‐resolved meter‐scale snow and sea ice thickness heterogeneity on horizontal heat conduction. Neglecting horizontal processes causes underestimating the conductive heat flux of 10% or more. Furthermore, comparing model results to independent temperature observations reveals a ∼5 K surface temperature overestimation over ice thinner than 1 m, attributed to shortcomings in parameterizing surface turbulent and radiative fluxes rather than the conduction. Assessing the model deficiencies and parameterizing these unresolved processes is required for improved sea ice representation.

Experimental Study on Shear Strength of Roof–Snow Interfaces for Prediction of Roof Snow Sliding

The sliding of roof snow may result in surcharges of snow load on lower roofs or the injury of pedestrians on the ground. It is therefore of great significance to study the mechanism of roof snow sliding, such that prevention or control measures can be developed to manage the risk. Considering four commonly used roofing materials, glass, steel, membrane, and concrete, two types of experiments were carried out in this study to possibly reveal the influence of roofing materials on the shear strength of the roof–snow interface: one is the critical angle tests where the angle at which the snow starts to slide off from the roof is tested, and the other is the shearing tests which aim to test the shear strength of the roof–snow interfaces at specific temperatures. The results showed that the critical angle for roof snow sliding, as well as the shear strength of the roof–snow interface for the four considered roofing materials, show a U-shape trend with the increase in surface roughness and that the shear strength of the roof–snow surface ranges from 0.15 kPa to 2 kPa for the cases considered, while the strength reaches its maximum at certain temperatures near −5 °C for a specific roofing material and snow thickness. These findings could be a useful reference for future experimental or simulation studies on roof snow sliding.

Fluvial Morphology in Different Permafrost Environments—A Review

This review presents a synthesis of the interaction between the hydro-morphological processes on interfluves and channels within fluvial catchments in permafrost regions. Both in modern and ancient permafrost catchments, this integrated landscape is quite diverse because of a variegated extent of frozen ground, density of vegetation cover, snow thickness, and other local factors. Moreover, temporal changes in environmental conditions are expressed in the morphological evolution of catchments. Channel patterns vary between single- and different multi-channel forms while the interfluves show a high diversity ranging from complete stability to intense denudation by surface runoff. It appears that braided channels, despite their high energy, were only significant during short intervals of peak discharge and transported only limited amounts of eroded sediment, while other channel patterns required more subdued annual discharge variability. Further, denudational processes on interfluves were a specific characteristic of landscape evolution during subsequent ice ages, especially in conditions of snow-rich and poorly vegetated, seasonal frost, or discontinuous permafrost resulting in the formation of extended planforms (cryopediments). In contrast, interfluves appeared to be rather stable on continuously frozen soils.

Calculations of Arctic Ice‐Ocean Interface Photosynthetically Active Radiation (PAR) Transmittance Values

AbstractSea ice algae play an important role in the Arctic Ocean ecosystem, driving primary production in the spring and sequestering carbon to the deep ocean. Up to 45% of Arctic Ocean primary production occurs in ice‐covered areas; photosynthetically active radiation (PAR) is fundamental to driving this production. Sea ice, and particularly snow, strongly scatter and reflect light, reducing the amount of PAR transmitted to the ice‐ocean interface. The effect that varying thicknesses of sea ice (0.2–3.5 m) and snow (0.01–1 m) have on the value of PAR transmittance at the ice‐ocean interface are considered for a Winter, Spring, and Summer scenario. When characteristic Arctic Ocean conditions (2 m sea ice and ∼0.2 m snowpack) are modeled, there is roughly a two‐fold difference in PAR transmittance at the ice‐ocean interface between the Winter (0.003) and Spring (0.007) scenarios and an order of magnitude difference with the Summer scenario (0.04). The modeled values correlate within one standard deviation of measured values and show good agreement with extended pan‐Arctic Ocean field campaign measurements. The results also indicate that simple exponential decay methods may lead to inaccurate results, and radiative‐transfer modeling is required to accurately predict PAR transmittance at the ice‐ocean interface. Therefore, this study offers a novel mathematical technique to predict the value of PAR transmittance at the ice‐ocean interface. Coupled with year‐round near‐real‐time sea ice and snow thickness remote sensing data, this technique may improve understanding of primary production and carbon budgets in the changing Arctic Ocean.

Solar radiation transfer in an ice-covered lake at different snow thicknesses

ABSTRACT Field observations were performed in Lake Nanhai, a shallow Chinese lake, to investigate the impact of variations in snow thickness (0–7.0 cm) on solar radiation transfer. As the snow thickness increases from 0 to 7.0 cm, the albedo increases from 0.27 to 0.96. The bulk extinction coefficients of snow, snow-ice, and congelation ice are 9.47, 9.69, and 2.18 m−1, respectively. The peak of the transmission spectrum shifts from the blue to green light waveband compared to the solar radiation spectrum. The proportion of incident radiation at surface penetrating to the under-ice water ranges from 0.5% to 19.7% associated with snow depth from 7 cm to 0 cm. Fresh snow influences the under-ice light condition crucially, and therefore the seasonal evolution of the lake phytoplankton community is affected.

Impacts of crude oil on Arctic sea-ice diatoms modified by irradiance

Anthropogenic climate change is reducing ice and snow thickness in the Arctic. The loss of summer sea ice has led to increased access to Arctic waters and the development of marine resources, which raises the risk of oil spills. Thinning ice and snow also increases irradiance in the upper ocean which is predicted to increase primary productivity, disfavoring shade-adapted sea-ice algae while benefitting phytoplankton and cryopelagic taxa. Studies have confirmed the lethality of crude oil and its distillates to Arctic phytoplankton; less well-constrained are the sublethal impacts to sea-ice algae in combination with other drivers. This study investigates the combination of two drivers, crude oil exposure and irradiance, on the growth rate and maximum cell concentration of four sea-ice diatoms (Attheya septentrionalis, Fragilariopsis cylindrus, and two strains of Synedropsis hyperborea) isolated from landfast sea ice near Utqiaġvik, Alaska. Crude oil inhibition of growth was complex and dependent on species and irradiance level. A. septentrionalis was generally tolerant to crude oil exposure, but toxicity was enhanced at the highest irradiance. The cryopelagic taxon, F. cylindrus, exhibited strong growth inhibition at TPH concentrations greater than approximately 6 mg L−1. Growth rates of S. hyperborea strains were stimulated at low concentrations of oil at all light levels. A simple numerical model was used to simulate an oil spill under varying snow depths to follow composition of a mock community comprised of these four isolates across a spring season. Results highlight that the reduction of algal biomass accumulation and the community composition change following a crude oil spill are more severe in a simulated low-snow spring, due to the relative sensitivity of F. cylindrus. We show that a brighter Arctic, which is predicted to increase the relative importance of cryopelagic taxa like F. cylindrus, may render the Arctic ecosystem more vulnerable to crude oil spills.

Ground-penetrating radar as a tool for determining the interface between temperate and cold ice, and snow depth: a case study for Hurd-Johnsons glaciers, Livingston Island, Antarctica

Abstract We analyze the internal structure of two polythermal glaciers, Hurd and Johnsons, located on Livingston Island, Antarctica, using 200 and 750 MHz GPR data collected in 2003/04, 2008/09 and 2016/17 field campaigns. Based on the different permittivities of snow and ice, we determined the thickness distribution of the end-of winter snow cover and of the cold ice layer. Their knowledge is fundamental for mass balance and glacier dynamics studies due to the different densities and rheological properties of such media. The average measured thicknesses for the snow and cold ice layers (the latter including the snow layer) were of 1.44 ± 0.09 and 29.1 ± 1.5 m, and their corresponding maxima were of 2.45 ± 0.21 and 80.8 ± 2.5 m. GPR snow profiling allowed for extension of the coverage of the snow thickness survey, but added little information to that supplied by snow pits, stake readings and manual snow probing, because of the multiplicity of reflections within the seasonal snowpack caused by internal ice layers and lenses. The polythermal structure determined for Hurd Glacier fits into the so-called Scandinavian type, seldom reported for the Antarctic region.

Ice and Snow Thickness of the IGAN Glacier in the Polar Urals from Ground-Based Radio-Echo Sounding in 2019 and 2021

Ice and Snow Thickness of the IGAN Glacier in the Polar Urals from Ground-Based Radio-Echo Sounding in 2019 and 2021

Spatial Variability in the Primary Production Rates and Biomasses (Chl a) of Sea Ice Algae in the Canadian Arctic–Greenland Region: A Review

The aims of this review are to elucidate the spatial variation in the primary production rates and biomasses (Chl a) of sea ice algae in the Canadian Arctic–Greenland region, characterized by its comparable physical settings. A database was compiled from 30 studies of the production rates and biomasses (Chl a) of sea ice algae, the snow and ice thicknesses, ice types, nutrients (Si(OH)4, PO4, (NO3 + NO2)), and NH4 concentrations in the ice and below the ice from the region. Production rates were significantly higher (463 mg C m−2 d−1) in Resolute Bay and Northern Baffin Bay (317 mg C m−2 d−1), both in the Canadian Arctic, compared to a rate of 0.2 mg C m−2 d−1 in northeast Greenland. The biomasses reached 340 mg Chl a m−2 in Resolute Bay in comparison to 0.02 mg Chl a m−2 in southwest Greenland. Primary production at other Canadian and Greenland sites was comparable, but sea ice Chl a was higher (15.0 ± 13.4 mg Chl a m−2) at Canadian sites compared to Greenland ones (0.8 ± 0.5 mg Chl a m−2). Resolute and Northern Baffin Bay production rates were significantly higher when compared to other Arctic Ocean sites outside the studied region. The review concludes that the high production rates and biomasses in Resolute and Northern Baffin Bay are related to the inflow and mixing of nutrient-rich waters of Pacific origin. A conceptual model with drivers and inhibitors of the primary production of sea ice algae is proposed, and the database is compiled into a dataset of published data for further studies.

Characterization of road surfaces using three near-infrared diode lasers

Rapid road network expansion has heightened the importance of surface condition information for traffic accident prevention and route optimization. This article introduces a laser diode-based sensor that identifies seven surface conditions and accurately measure ice, water, and snow film thicknesses on roads. An optical module was developed to detect weak optical signals based on the characteristic absorption spectrum of the target surface. The module used three laser diodes (1310, 1440, and 1550 nm wavelengths) as light sources. Additionally, a road classification algorithm that is adaptable to foggy weather was developed using a multi-wavelength processing protocol. The sensor was subjected to numerous calibration and performance verification experiments. During thick foggy measurements, the processed spectra displayed a maximum variation of 2.372% across a 600 to 25,000 m visibility range with a relative standard deviation of only 0.328%. This demonstrated effective weakening of the effects of visibility variations. During winter field testing, the sensor classified road conditions effectively and accurately measured ice, snow, and water film thicknesses, with a correlation coefficient of 0.97444. The accuracy of the measurements was less than 0.5 mm. The sensor’s effectiveness for long-term field-based road testing has been verified.

Thermal Regime of Permafrost on the Western Yamal Under Climate Warming

Climate change observed in the Arctic affects all components of the natural environment, including the state of permafrost. The purpose of this study is to quantify the response of permafrost in various landscapes to changing climatic parameters. The results of long-term field observations (1978-2021) of the thermal regime of permafrost on the Western Yamal are presented. Along with the increase in mean annual air temperatures, the mean annual ground temperature over the past 43 years has increased by 1.5-2.2°C. The maximum increase of permafrost temperature values is observed on flat and polygonal tundra, the minimum increase is typical for flooded lake basins. A decrease in the annual permafrost temperature amplitude was revealed. That is caused by a rapid increase in the air temperature of the cold period, an increase in the snow thickness and an increase in soil moisture in the active layer. The shrinking in ground temperature amplitude at a depth of 5 m is 0.5-3.6°C. A trend of reducing depth of zero annual amplitude from 12-18 m (1980) to 13-16 m (2021) has been revealed.

Models for thermal boundary layer in level ice growth and brash ice consolidation

It is important to understand the properties and parameters of ice growth models, to enable reliable assessment of the impact ice may have on facilities or to ship navigation. To improve the understanding of the different models, the theoretical formulations for ice growth are investigated and calculated results compared with laboratory and full-scale measurement data. The paper describes the ice growth models for level sea ice and how these are applied in brash ice consolidation modelling. In particular, analysis is made to account for modelling of snow cover in level ice growth models, and subsequently also salinity, porosity and the atmospheric boundary including wind effect in brash ice models. The paper presents an overview of laboratory tests and results for both level ice and brash ice. Also models for level ice growth for the case of snow cover are derived and compared with thetest results. Specifically, inclusion of snow thickness in the growth model presents some practical difficulties, as the thickness of snow cover is often not known a priori, and comparison between calculated level ice thickness and measurements suggests that a good assumption in predictive models is to assume the snow cover thickness to be proportional to level ice thickness. Further, it was observed that the wind influences much the heat transfer to atmosphere, which is not zero at the zero wind speed, a value for the heat transfer coefficient to atmosphere is derived based on laboratory tests. The findings from these analyses provide an improved understanding of the ice growth and consolidation process which can be incorporated into modelling techniques for marine design and operations.

Snow accretion on a model train: Climate wind tunnel experiments

Snow and ice accumulation on the main parts of rolling stock can lead to malfunctions and safety issues. This paper presents the results of snow accretion tests conducted in a climate wind tunnel to investigate the icing process on a model train at various ambient temperatures. A simplified 2/3-scale EMU-320 high-speed Korean train model was used without electrical power or heat sources. Before testing, the snow flux and liquid water content of snow were measured to enable their use as input conditions in future simulations and to inform further analysis of the icing process. Both qualitative and quantitative data from the tests were analyzed, including photographs and snow density and thickness measurements. Snow accretion was broader at higher ambient temperatures, and snow accretion on the nose tended to be thicker further away from the stagnation point at higher temperatures. Snow accreted on all components of the bogie, and the thickest snow accretion on the wheels occurred at arc angles of 15–40° for cases of lower temperature while occurring at a larger angle at the highest temperature. The comprehensive data from these experiments is expected to support future analysis and development of anti-icing systems.

Effective Improvement of the Accuracy of Snow Cover Discrimination Using a Random Forests Algorithm Considering Multiple Factors: A Case Study of the Three-Rivers Headwater Region, Tibet Plateau

Accurate information on snow cover extent plays a crucial role in understanding regional and global climate change, as well as the water cycle, and supports the sustainable development of socioeconomic systems. Remote sensing technology is a vital tool for monitoring snow cover’ extent, but accurate identification of shallow snow cover on the Tibetan Plateau has remained challenging. Focusing on the Three-Rivers Headwater Region (THR), this study addressed this issue by developing a snow cover discrimination model (SCDM) using a random forests (RF) algorithm. Using daily observed snow depth (SD) data from 15 stations in the THR during the period 2001–2013, a comprehensive analysis was conducted, considering various factors influencing regional snow cover distribution, such as land surface reflectance, land surface temperature (LST), Normalized Difference Snow Index (NDSI), Normalized Difference Vegetation Index (NDVI), and Normalized Difference Forest Snow Index (NDFSI). The key results were as follows: (1) Optimal model performance was achieved with the parameters Ntree, Mtry, and ratio set to 1000, 2, and 19, respectively. The SCDM outperformed other snow cover products in both pixel-scale and local spatial-scale discrimination. (2) Spectral information of snow cover proved to be the most influential auxiliary variable in discrimination, and the combined inclusion of NDVI and LST improved model performance. (3) The SCDM achieved accuracy of 99.04% for thick snow cover (SD > 4 cm) and 98.54% for shallow snow cover (SD ≤ 4 cm), significantly (p < 0.01) surpassing the traditional dynamic threshold method. This study can offer valuable reference for monitoring snow cover dynamics in regions with limited data availability.

Response of the Snowball Earth Climate to Orbital Forcing at a High CO2 Level

Abstract How the climate responded to orbital forcing during the Neoproterozoic snowball Earth events, the most extreme glaciations on Earth, is still unclear. Here, we investigate this problem using a climate model. To simplify the analysis, continents are removed. The results show that even in this simplified situation, the snowball Earth climate is sensitive to orbital configurations. The globally averaged annual surface temperature can differ by 2.4°C, and the maximum monthly mean temperature can differ by 3.7°C under different orbital configurations. Therefore, a snowball Earth could be deglaciated more easily in some orbital configurations than in others. The climatic effect of a particular orbital parameter is highly dependent on the values of other parameters. For example, the effect of obliquity on tropical surface temperature is generally small (<1°C), but it can become large (3.8°C) when eccentricity is large and the northern autumn occurs at perihelion (precession = 180°). Surprisingly, the global temperature is generally lower at high eccentricity than at near-zero eccentricity, even though the total insolation received by Earth is higher in the former than in the latter. Moreover, we find that the Milankovitch hypothesis is valid not only in the extratropical region, but also in the tropics; the snow thickness in the tropical region is inversely proportional to the maximum monthly insolation received in this region.