Snow Thickness Distributions Research Articles

Geophysical Monitoring Shows that Spatial Heterogeneity in Thermohydrological Dynamics Reshapes a Transitional Permafrost System

AbstractClimate change is causing rapid changes of Arctic ecosystems. Yet, data needed to unravel complex subsurface processes are very rare. Using geophysical and in situ sensing, this study closes an observational gap associated with thermohydrological dynamics in discontinuous permafrost systems. It highlights the impact of vegetation and snow thickness distribution on subsurface thermohydrological properties and processes. Large snow accumulation near tall shrubs insulates the ground and allows for rapid and downward heat flow. Thinner snow pack above graminoid results in surficial freezing and prevents water from infiltrating into the subsurface. Analyzing short‐term disturbances, we found that lateral flow could be a driving factor in talik formation. Interannual measurements show that deep permafrost temperatures increased by about 0.2°C over 2 years. The results, which suggest that snow‐vegetation‐subsurface processes are tightly coupled, will be useful for improving predictions of Arctic feedback to climate change, including how subsurface thermohydrology influences CO2 and CH4 fluxes.

Snow Thickness Estimation on First-Year Sea Ice from Late Winter Spaceborne Scatterometer Backscatter Variance

Ku- and C-band spaceborne scatterometer sigma nought (σ°) backscatter data of snow covered landfast first-year sea ice from the Canadian Arctic Archipelago are acquired during the winter season with coincident in situ snow-thickness observations. Our objective is to describe a methodological framework for estimating relative snow thickness on first-year sea ice based on the variance in σ° from daily time series ASCAT and QuikSCAT scatterometer measurements during the late winter season prior to melt onset. We first describe our theoretical basis for this approach, including assumptions and conditions under which the method is ideally suited and then present observational evidence from four independent case studies to support our hypothesis. Results suggest that the approach can provide a relative measure of snow thickness prior to σ° detected melt onset at both Ku- and C-band frequencies. We observe that, during the late winter season, a thinner snow cover displays a larger variance in daily σ° compared to a thicker snow cover on first-year sea ice. This is because for a given increase in air temperature, a thinner snow cover manifests a larger increase in basal snow layer brine volume owing to its higher thermal conductivity, a larger increase in the dielectric constant and a larger increase in σ° at both Ku- and C bands. The approach does not apply when snow thickness distributions on first-year sea ice being compared are statistically similar, indicating that similar late winter σ° variances likely indicate regions of similar snow thickness.

Predicting Melt Pond Fraction on Landfast Snow Covered First Year Sea Ice from Winter C-Band SAR Backscatter Utilizing Linear, Polarimetric and Texture Parameters

Early-summer melt pond fraction is predicted using late-winter C-band backscatter of snow-covered first-year sea ice. Aerial photographs were acquired during an early-summer 2012 field campaign in Resolute Passage, Nunavut, Canada, on smooth first-year sea ice to estimate the melt pond fraction. RADARSAT-2 Synthetic Aperture Radar (SAR) data were acquired over the study area in late winter prior to melt onset. Correlations between the melt pond fractions and late-winter linear and polarimetric SAR parameters and texture measures derived from the SAR parameters are utilized to develop multivariate regression models that predict melt pond fractions. The results demonstrate substantial capability of the regression models to predict melt pond fractions for all SAR incidence angle ranges. The combination of the most significant linear, polarimetric and texture parameters provide the best model at far-range incidence angles, with an R 2 of 0.62 and a pond fraction RMSE of 0.09. Near- and mid- range incidence angle models provide R 2 values of 0.57 and 0.61, respectively, with an RMSE of 0.11. The strength of the regression models improves when SAR parameters are combined with texture parameters. These predictions also serve as a proxy to estimate snow thickness distributions during late winter as higher pond fractions evolve from thinner snow cover.

Effects of subgrid‐scale snow thickness variability on radiative transfer in sea ice

AbstractSnow is a principal factor in controlling heat and light fluxes through sea ice. With the goal of improving radiative and heat flux estimates through sea ice in regional and global models without the need of detailed snow property descriptions, a new parameterization including subgrid‐scale snow thickness variability is presented. One‐parameter snow thickness distributions depending only on the gridbox‐mean snow thickness are introduced resulting in analytical solutions for the fluxes of heat and light through the snow layer. As the snowpack melts, these snow thickness distributions ensure a smooth seasonal transition of the light field under sea ice. Spatially homogenous melting applied to an inhomogeneous distribution of snow thicknesses allows the appearance of bare sea ice areas and melt ponds before all snow has melted. In comparison to uniform‐thickness snow used in previous models, the bias in the under sea‐ice light field is halved with this parameterization. Model results from a one‐dimensional ocean turbulence model coupled with a thermodynamic sea ice model are compared to observations near Resolute in the Canadian High Arctic. The simulations show substantial improvements not only to the light field at the sea ice base which will affect ice algal growth but also to the sea ice and seasonal snowpack evolution. During melting periods, the snowpack can survive longer while sea ice thickness starts to reduce earlier.

Regional-scale sea-ice and snow thickness distributions from in situ and satellite measurements over East Antarctica during SIPEX 2007

The Sea Ice Physics and Ecosystem eXperiment (SIPEX) was conducted in the East Antarctic pack ice zone between 115-130°E from 9 September – 11 October, 2007. In situ measurements of sea-ice and snow properties were conducted at 15 ice stations, together with ship-based ASPeCt observations. The ice and snow thickness varied considerably in different regions of the pack ice, with particularly thick ice associated with deformation and a strong slope jet in the southwest of the study region. The mean ice thickness was 0.99 m (1.57 m excluding the northern marginal ice zones), but varied from 0.61 m along the southern leg to 1.80 m along the western leg, with pockets of considerably thicker ice in some regions. Swell was observed on two occasions penetrating more than 330 km south of the ice edge into regions with 80-100% ice concentration. Ice thicknesses calculated from near coincident ICESat laser altimetry (1.74 m) are similar to the in-situ observations in the central pack (1.57 m).

Reproduction of the large-scale state of water and sea ice in the Arctic Ocean in 1948–2002: Part I. Numerical model

This paper completes a series of studies conducted with a numerical model of low spatial resolution for the area of the North Atlantic and Arctic Ocean north of 65° N without including Hudson Bay to reproduce the monthly mean state in 1948–2002. The paper gives a detailed description of the physical formulation of the problem, the approximations and parametrizations that were employed, and the parameters of atmospheric and oceanic external forcings. Generally, the author follows the requirements of the protocol of the Arctic Ocean Model Intercomparison Project (AOMIP). The paper analyzes the main monthly mean characteristics: ice thickness, ice-drift velocity, snow thickness, velocity of currents, and temperature and salinity, which were derived as multiyear averages over 1958–2002. A good reproduction of the following sea-ice characteristics is noted: ice thickness, propagation area, ice concentration, and drift velocity. For example, the annual mean ice-drift velocity is about 3.33 cm/s, which is consistent with the data obtained from drifting buoys, which yield an annual mean ice-drift velocity of 3.65 cm/s. At the same time, there are problems of reproducing the observed snow-thickness distribution. The use of parametrizations of horizontal turbulence of the Neptune-Effect type and eddy transfer for a scalar makes it possible to conserve the cyclonic circulation in the Atlantic water layer although the low spatial resolution gives no way of explicitly reproducing the narrow topographic jet. In conclusion, we briefly discuss the main unsolved problems and, primarily, the problem of reproducing the freshwater content. The model and further versions of it will be used in the European Commission project DAMOCLES (Developing Arctic Modeling and Observing Capabilities for Long-Term Environmental Studies) to assess the sensitivity of the Arctic Ocean to the parameters of external forcing and to evaluate the role of tides in the formation of the Arctic Ocean’s climate.

Modeled impacts of changes in tundra snow thickness on ground thermal regime and heat flow to the atmosphere in Northernmost Alaska

Seasonal snow covers the tundra surface for up to nine months of each year on the Alaskan North Slope. Variations in the snow thickness could strongly influence the thermal regime of the underlying soil and permafrost, and the surface energy balance. The impacts of increases and decreases in the tundra snow thickness on the thermal regime of snow surface, active layer, and permafrost, and on the conductive heat flow to the atmosphere were investigated numerically, by using an improved surface energy balance approach based one-dimensional heat transfer model. The baseline inputs for the numerical model are mean daily meteorological data and surface albedos collected at Barrow, Alaska from 1995 through 1999. Based on a study for the long-term mean daily maximum and minimum snow thickness distributions at Barrow in the snow season of 1948 through 1997, a snow thickness factor was defined and five simulation cases were run for the snow season of 1997–1998 by changing the snow thickness factor. The modeled results indicate that changes in snow thickness have significant impacts on ground thermal regimes and conductive heat flow to the atmosphere. Decreasing the snow thickness by 50% led to the maximum ground temperature decrease of 1.48 °C at 0.29 m depth, and 0.72 °C at 3.0 m depth; the magnitude of the mean conductive heat flow to the atmosphere for December increase of 4.3 Wm − 2 . Increasing the snow thickness by 50% resulted in the maximum ground temperature increase of 1.44 °C at 0.29 m depth, and 0.66 °C at 3.0 m depth; the magnitude of the mean conductive heat flow to the atmosphere for December decrease of 1.57 W m − 2 . On an annual basis, variation in the snow thickness by 50%, the ground temperature variations of more than 0.25 °C occurred as deep as 8.0 m below the ground surface. The modeled results also show that changes in snow thickness have a relatively small influence on the snow surface temperature.

The role of snow on the thermal dependence of microwave backscatter over sea ice

Our understanding of snow distribution in the polar regions is severely restricted owing to the heterogeneity, both in space and time, of this solid precipitate. Processes such as vapor and mass fluxes across the interface are, to a large extent, controlled by the presence and geophysical state of the snow cover on sea ice. Numerous studies have shown the importance of snow cover in ecosystem processes and particularly in photosynthetically active radiation extinction. Researchers are currently exploiting developments in electromagnetic interaction theory in an attempt to measure snow thickness distributions remotely. In this paper, we investigate the dependence of radar backscatter on snow thickness over smooth first‐year ice. We use data from the Seasonal Sea Ice Monitoring and Modeling Site located in the Canadian Archipelago. Results show that the thermodynamics of the snow cover affect wave propagation, attenuation, and scattering through the control that brine volume exerts on interfacial characteristics of the snow and ice layers. The effect is subtle and specific to certain ranges of salinity, surface roughness and thickness of sea ice. We describe the phenomenon responsible for this effect using a microwave model consistently for both complex effective permittivities and backscatter coefficients coupled to a one‐dimensional model. We validate the physical principles using in situ field data. We then discuss the potential of synthetic aperture radar in estimating snow thickness distributions under these specific conditions using both observed and modeled microwave scattering.

Winter snow cover variability on East Antarctic sea ice

Analysis of the first detailed data set of snow characteristics collected over East Antarctic sea ice in winter confirms that on small scales, snow on Antarctic sea ice is highly variable in both thickness and properties. High‐amplitude cyclical variability in atmospheric forcing related to the passage of storms is responsible for the high degree of textural heterogeneity observed. Changes in snow properties were examined over a 3‐week period, during which a largely icy snow cover, formed at near‐freezing temperatures, metamorphosed to snow in which facetted crystals and depth hoar dominated, as the air temperature plummeted. Even on flat ice, significant localized thickening of snow occurs in the form of barchan dunes. Although we observed great variability in snow thickness and properties on local scales, overall snow thickness distribution and the complex textural assemblage of snow types are similar from region to region. Similar observations were made by Sturm et al. [1998] in West Antarctica. Large‐scale similarities are also apparent in mean snow density, grain size, and bulk snow salinity, although high variability is again found across individual floes. Rapid depth hoar formation is a ubiquitous process that greatly affects the density, texture, grain size, and effective thermal conductivity of the snow cover. The observed heterogeneity results in varying snow effective thermal conductivities. The mean bulk effective thermal conductivity, computed from the proportion of observed snow types, is 0.164 W m−1 K−1, significantly lower than values typically used in large‐scale sea ice modeling but similar to that derived by Sturm et al. [1998] in a near‐simultaneous experiment in the Bellingshausen and Ross Seas. It varies from 0.097 to 0.383 W m−1 K−1 in different snow pits. The findings support those of Sturm et al. [1998] that periodic flooding and subsequent snow ice formation, which are also ubiquitous processes, effectively diminish the degree to which basal snow processes create inhomogeneities in the snow pack.

Early winter ice and snow thickness distribution, ice structure and development of the western Ross Sea pack ice between the ice edge and the Ross Ice Shelf

A study of early winter first-year sea ice conditions and development in the western Ross Sea in May and June 1995 included measurements of snow and ice thickness, freeboard, ice core structure and stable isotopic composition. These variables showed strong spatial variability between the Ross Ice Shelf and the ice edge 1400 km to the north, and indicate that the development of the Ross Sea pack ice is quite different from that observed in other Antarctic sea ice zones. The thinnest snow and ice occurred in a 200 km wide coastal zone. The thickest snow and ice were observed in a continental shelf zone 200–600 km from the coast where the average ice thickness (0.8 m) determined by drilling is as thick as first-year sea ice later in winter elsewhere in Antarctica. A zone of moderate snow and ice thickness occurred on the deep ocean from 600 km to the ice edge at 1400 km. Thermodynamic thickening of the ice in the inner pack ice, <800 km from the coast, was dominated by congelation ice growth, which occurred in a greater amount (65%) and in thicker layers (mean: 20 cm) than was observed in the outer pack ice >800 km from the coast (amount: 22%; mean layer thickness: 12 cm) and elsewhere in the Antarctic pack ice. The preponderance of congelation ice in the inner pack ice might be due to a low oceanic heat flux on the Ross Sea continental shelf, and a colder, less stormy environment which favours the more frequent and prolonged calm conditions necessary for significant congelation ice growth. In the outer pack ice, thermodynamic thickening occurred mainly by snow ice formation (mean layer thickness: 20 cm) while dynamic processes, i.e., rafting and ridging, caused the thickening of frazil ice and columnar ice (mean layer thickness: 14 cm and 12 cm respectively). A greater amount of snow ice (37%) occurred in the outer pack ice than in the inner pack ice (15%), and both values indicate that in the Ross Sea, unlike other Antarctic sea ice zones, there can be significant seawater flooding of the snow/ice interface and snow ice formation before midwinter.

Winter snow cover on sea ice in the Weddell Sea

Measurements of snow thickness, temperature, salinity, density, and stratigraphy acquired during the 1992 Winter Weddell Gyre Study are presented. Results indicate that the winter snow cover on sea ice in the Weddell Sea is extremely variable. Extreme fluctuations in Antarctic synoptic conditions (air temperature, precipitation, humidity, and wind speed) occur during the austral winter. They result in unique modifications and additions to the snow layer during the aging process and act to stabilize an otherwise easily wind‐redistributed shallow snow cover and develop well‐packed drift features. The latter occur even over relatively undeformed areas of sea ice and have a significant localized effect on the snow thickness distribution. Significant variability in snow grain size (mean 2.73±3.12 mm) and density (0.32±0.09 g cm−3) is observed as a result of cyclical switches between high‐ and low‐temperature gradient metamorphism. Multiple icy layers indicate multiple thaw‐freeze events. One such event occurred during a 3‐day station, during which the air temperature rose by 22°C in 12 hours (to approximately 0°C). This paper also examines mechanisms for flooding of the snow‐ice interface, including snow loading. Even where the latter is not a factor, the layer of snow immediately above the snow‐ice interface is commonly damp and saline (>10‰). Limitations in the data set are discussed, and comparisons are drawn with other experiments.

Development of a Sea Ice Model for Use in Zonally Averaged Energy Balance Climate Models

A sea ice model for use in zonally averaged energy balance climate models is presented which includes the following processes: surface melting, basal freezing and melting, lateral melting from ice-flee water or growth of new ice in leads, snowfall and the formation of white ice, ice advection, and a parameterized ice and snow thickness distribution which represents the effects of small-scale dynamics. The ice growth equations of Hibler are solved analytically, thereby permitting a gradual increase in zonal ice fraction in fall and winter. Both lateral and vertical melting lead to a continuous decrease of ice fraction during ice decay. The correlation between ice thickness and ice thickness sensitivity to the upward heat flux at the ice base is of opposite sign seasonally and latitudinally. The parameterized feedback between ice thickness and the minimum permitted lead fraction is found to be very important to the ice simulation, and is a process which needs to be studied using higher resolution, dynamic-thermodynamic sea ice models. The interaction between lateral melting and advection is crucial to the simulated rapid retreat of Southern Hemisphere ice area in spring. With uniform snow on ice, the introduction of an ice-thickness distribution increases mean annual ice thickness by up to 20%, but simultaneously introducing an ice and snow thickness distribution such that the ratio of snow to ice thickness is constant for each ice thickness category leads to increase of mean ice thickness of up to 90%. The effect on mean annual sea ice thickness of the parameterized surface albedo temperature dependence tends to increase with increasing latitude, even though the length of the melt season and incident solar radiation decrease with latitude. Model sensitivity to variation of time-step length from 1 to 6 days is insignificant.