Snow Physics Research Articles

Model experiments on snow and ice thermodynamics in the Arctic Ocean with CHINARE 2003 data

Snow and ice thermodynamics over the Arctic Ocean were simulated applying a one‐dimensional model. A number of numerical experiments in synoptic (10 days in early autumn) and seasonal (May–September) scales were carried out to investigate the impact of external forcing, snow physics, and the model resolution: the number of layers in both snow and ice ranged from 3 to 40. The model forcing was based on in situ observations carried out in 2003 during the Chinese National Arctic Research Expedition (CHINARE) as well as on forecasts and analyses of the European Centre for Medium‐Range Weather Forecasts (ECMWF) and the National Centers for Environmental Prediction (NCEP)/National Center for Atmospheric Research (NCAR). The model results were compared against the results of the ECMWF and NCEP/NCAR sea ice schemes. The ECMWF operational precipitation forecasts yielded realistic seasonal snowfall, while the precipitation in NCEP/NCAR reanalysis was unrealistically large. A good result on snow thickness evolution also strongly depended on the accuracy of modeled snowmelt. A time‐dependent surface albedo parameterization was critical for the seasonal evolution of snow and ice thickness. Application of 15–20 model levels in snow and ice is recommended as it (1) ensured good reproduction of the vertical snow/ice temperature profile also when solar radiation was large, (2) decreased the sensitivity of snow and ice mass balance to changes in surface albedo, (3) enabled the calculation of subsurface melting of snow and ice, and (4) reasonably reproduced the superimposed ice formation and onset of ice melt. In autumn, however, the accuracy of atmospheric forcing was more important than the model resolution.

Boundary layer physics over snow and ice

Abstract. Observations of the unique chemical environment over snow and ice in recent decades, particularly in the polar regions, have stimulated increasing interest in the boundary layer processes that mediate exchanges between the ice/snow interface and the atmosphere. This paper provides a review of the underlying concepts and examples from recent field studies in polar boundary layer meteorology, which will generally apply to atmospheric flow over snow and ice surfaces. It forms a companion paper to the chemistry review papers in this special issue of ACP that focus on processes linking halogens to the depletion of boundary layer ozone in coastal environments, mercury transport and deposition, snow photochemistry, and related snow physics. In this context, observational approaches, stable boundary layer behavior, the effects of a weak or absent diurnal cycle, and transport and mixing over the heterogeneous surfaces characteristic of coastal ocean environments are of particular relevance.

Snow physics as relevant to snow photochemistry

Abstract. Snow on the ground is a complex multiphase photochemical reactor that dramatically modifies the chemical composition of the overlying atmosphere. A quantitative description of the emissions of reactive gases by snow requires knowledge of snow physical properties. This overview details our current understanding of how those physical properties relevant to snow photochemistry vary during snow metamorphism. Properties discussed are density, specific surface area, thermal conductivity, permeability, gas diffusivity and optical properties. Inasmuch as possible, equations to parameterize these properties as functions of climatic variables are proposed, based on field measurements, laboratory experiments and theory. The potential of remote sensing methods to obtain information on some snow physical variables such as grain size, liquid water content and snow depth are discussed. The possibilities for and difficulties of building a snow photochemistry model by adapting current snow physics models are explored. Elaborate snow physics models already exist, and including variables of particular interest to snow photochemistry such as light fluxes and specific surface area appears possible. On the other hand, understanding the nature and location of reactive molecules in snow seems to be the greatest difficulty modelers will have to face for lack of experimental data, and progress on this aspect will require the detailed study of natural snow samples.

Impact of parameterizations in snow physics and interface processes on the simulation of snow cover and runoff at several cold region sites

A series of numerical experiments have been designed to understand the physics at the soil‐vegetation‐snow‐atmosphere interface and to find the major parameterizations/parameters, which are crucial to simulate cold season processes. Observational data sets from Col de Porte of France, Ovre Lansjarv of Sweden, and Gander of Canada were used to help interpret the results. This study shows that snow layering and compaction are among the most important factors affecting proper simulations of snow depth, snow water equivalent (SWE), surface temperature, and surface runoff. Fixed snow density could produce as high as 100 percent error in estimating snow depth and could cause significant biases in SWE simulation during the melting period. Furthermore, with a bulk snow/soil layer, the simulated surface temperature would persistently be close to the freezing point with substantially hampered variability, and the variability and the amplitude of the runoff during the snow‐melting season could also be severely underestimated. The experiments also show that proper snow albedo is crucial during the ablation period and affects the magnitude and timing in both SWE and runoff simulations. Furthermore, this study indicates that the parameterizations in the surface aerodynamic resistance in the stable regime play an important role in determining the sensible and latent heat fluxes during the winter season in the Arctic region and then affect the snow depth simulations and prediction of snow melting as well as runoff timing. Although the snow may fully cover the ground in cold regions during the winter, numerical experiments in this study show the vegetation still exerts a substantial influence in the snow depth and runoff simulations. Numerical experimentation shows that less downward sensible heat on the bare ground produces thick snow cover and extremely high peak runoff, which leads to a typical deforestation scenario in cold regions.

Effects of Frozen Soil on Soil Temperature, Spring Infiltration, and Runoff: Results from the PILPS 2(d) Experiment at Valdai, Russia

The Project for Intercomparison of Land-Surface Parameterization Schemes phase 2(d) experiment at Valdai, Russia, offers a unique opportunity to evaluate land surface schemes, especially snow and frozen soil parameterizations. Here, the ability of the 21 schemes that participated in the experiment to correctly simulate the thermal and hydrological properties of the soil on several different timescales was examined. Using observed vertical profiles of soil temperature and soil moisture, the impact of frozen soil schemes in the land surface models on the soil temperature and soil moisture simulations was evaluated. It was found that when soil-water freezing is explicitly included in a model, it improves the simulation of soil temperature and its variability at seasonal and interannual scales. Although change of thermal conductivity of the soil also affects soil temperature simulation, this effect is rather weak. The impact of frozen soil on soil moisture is inconclusive in this experiment due to the particular climate at Valdai, where the top 1 m of soil is very close to saturation during winter and the range for soil moisture changes at the time of snowmelt is very limited. The results also imply that inclusion of explicit snow processes in the models would contribute to substantially improved simulations. More sophisticated snow models based on snow physics tend to produce better snow simulations, especially of snow ablation. Hysteresis of snow-cover fraction as a function of snow depth is observed at the catchment but not in any of the models.

Atmospheric contributions to the surface mass balance of Greenland in the HadAM3 atmospheric model

Atmospheric climate models now present powerful tools for studying atmospheric parameters relevant to the mass balance of the Greenland ice sheet, a significant uncertainty in global sea level. This study evaluates the simulations of the UK Hadley Centre atmospheric model (HadAM3) against observational data and reanalyses. HadAM3 reproduces the main precipitation patterns, but a positive bias exists in autumn over southern Greenland. The modeled North Atlantic storm track is well placed, but it and the polar vortex and hemispheric‐scale wave activity are weaker than observed, which may impact on moisture flux over Greenland. Surface temperatures are 2°–3°C too warm in summer and up to 5°C too cold in winter, probably owing to the snow albedo varying too little throughout the year, and excess summer downward short‐wave radiation flux and winter long‐wave loss, related to insufficient cloud cover. The summer warm bias and the too coarsely represented ice sheet area lead to Greenland‐mean melting being overestimated, and a negative surface mass balance is simulated. A higher‐resolution ice sheet mask improves these quantities significantly. Increasing resolution is expected to remove most errors when orography and the ice sheet, particularly around the coastal margins where gradients are large, are better defined, as orographic dynamical deficiencies are minimized. A high‐resolution version of the model is seen to improve the simulation of precipitation. Minor ice and snow physics improvements are needed, but the large‐scale simulation produces good‐quality inputs with no major bias for higher resolution limited area or downscaling models.

Intraseasonal variation in the thermoinsulation effect of snow cover on soil temperatures and energy balance

We present the results of an analysis of the observed variation in the energy balance of a soil surface at Barrow, Alaska, during 1993–1998. When combined with snow depth measurements, the data allow several stages to be distinguished in the intraseasonal variation of the snow cover effect on the temperature regime and energy balance of the underlying soil. Each stage corresponds to specific thermoinsulation effects of the snow cover in terms of the energy‐balance dependence of the soil‐surface on snow depth. Stages in the intraseasonal surface energy balance variation can be used as a basis for incorporating detailed snow physics in modeling of the soil freezing/thawing phenomenon and for consideration of the distributed energy balance of snow covered landscapes. Preliminary ideas are presented on applying the results obtained for nonpermafrost regions.

Refinements to SSiB with an Emphasis on Snow Physics: Evaluation and Validation Using GSWP and Valdai Data

Refinements to the snow-physics scheme of SSiB (Simplified Simple Biosphere Model) are described and evaluated. The upgrades include a partial redesign of the conceptual architecture to better simulate the diurnal temperature of the snow surface. For a deep snowpack, there are two separate prognostic temperature snow layers - the top layer responds to diurnal fluctuations in the surface forcing, while the deep layer exhibits a slowly varying response. In addition, the use of a very deep soil temperature and a treatment of snow aging with its influence on snow density is parameterized and evaluated. The upgraded snow scheme produces better timing of snow melt in GSWP-style simulations using ISLSCP Initiative I data for 1987-1988 in the Russian Wheat Belt region. To simulate more realistic runoff in regions with high orographic variability, additional improvements are made to SSiB's soil hydrology. These improvements include an orography-based surface runoff scheme as well as interaction with a water table below SSiB's three soil layers. The addition of these parameterizations further help to simulate more realistic runoff and accompanying prognostic soil moisture fields in the GSWP-style simulations. In intercomparisons of the performance of the new snow-physics SSiB with its earlier versions using an 18-year single-site dataset from Valdai Russia, the version of SSiB described in this paper again produces the earliest onset of snow melt. Soil moisture and deep soil temperatures also compare favorably with observations.

The Impact of Detailed Snow Physics on the Simulation of Snow Cover and Subsurface Thermodynamics at Continental Scales

The three-layer snow model is coupled to the global catchment-based Land Surface Model (LSM) of the NASA Seasonal to Interannual Prediction Project (NSIPP) project, and the combined models are used to simulate the growth and ablation of snow cover over the North American continent for the period 1987-1988. The various snow processes included in the three-layer model, such as snow melting and re-freezing, dynamic changes in snow density, and snow insulating properties, are shown (through a comparison with the corresponding simulation using a much simpler snow model) to lead to an improved simulation of ground thermodynamics on the continental scale.

Turbulent fluxes during blowing snow: field tests of model sublimation predictions

Sublimation fluxes during blowing snow have been estimated to return 10–50% of seasonal snowfall to the atmosphere in North American prairie and arctic environments. These fluxes are calculated as part of blowing snow two-phase particle transport models with provision for phase change based upon a particle-scale energy balance. Blowing snow models have normally been evaluated based upon their ability to reproduce diagnostic mass flux gradient measurements and regional-scale snow redistribution patterns and snow mass. Direct evidence is presented here that large latent heat fluxes (40–60 W m−2) that result in sublimation rates of 0·05–0·075 mm snow water equivalent hour−1, are associated with mid-winter, high-latitude blowing snow events. For events with wind speeds above the threshold level for snow transport, these fluxes are in the range of those predicted by the Prairie Blowing Snow Model. The fluxes are well in excess of those found during spring snowmelt and which can be predicted by standard bulk aerodynamic transfer equations, suggesting that blowing snow physics will have to be incorporated in land surface schemes and hydrological models in order to properly represent snow surface mass and energy exchange during blowing snow events. Copyright © 1999 John Wiley & Sons, Ltd.

Hydrologic modeling of an arctic tundra watershed: Toward Pan‐Arctic predictions

A simple land surface model is used to explore the dynamics of the hydrologic cycle operating in arctic tundra regions. The model accounts for the topographic control of surface hydrology, ground thermal processes, and snow physics. The approach described relies only on the statistics of the topography rather than the details of the topography and is therefore computationally inexpensive and compatible with the large spatial scales of today's climate models. As such, the model can easily be applied on an arctic‐wide basis to explore issues ranging from the delivery of seasonal melt water to the Arctic Ocean to impacts of climate change on the hydrologic cycle.

Teaching Technical Writing Through Snowpack Study

In the section I teach of Technical Writing at Plymouth State College, students learn to handle the content, form, and style of scientific reports by writing about a snowpack (accumulated snow on the ground). In this context, snowpack study requires students to learn and apply only elementary concepts of snow physics, but it establishes common experiences in science for students with non-scientific backgrounds. During an initial field trip, students examine the layers in a snowpack and observe the various characteristics of snow. For two weeks after the first field trip, students study local weather history and learn basic concepts of snow science, snow stratigraphy, and snow metamorphism. Based on their new understanding of snow, they hypothesize changes that have occurred in the snowpack, and they learn to identify types of snow particles in the field. Then they return to the snowpack to make a second set of observations. During the second field trip, they reexamine the snowpack, compare their hypotheses with actual conditions they observe, and account for persistence and change in the snowpack. At each stage in the snowpack study unit, students write up their findings in a series of technical reports, then write essays in which they examine their personal experience in snowpack study and assess the snowpack

Snowpack physics explored at Fall Meeting

A special session, “Snowpack Physics: Processes and Distributions,” was held on December 10 at the Fall 1991 AGU Meeting to survey applications of snow physics spanning scales from millimeters to kilometers, and to tie these in with recent advances in our understanding of the micro‐ and meso scale processes in a snow cover.The first half of the session involved the relationships between snow physical process and properties and remote sensing, snowgas interactions, and snowmelt chemistry.

A Semianalytic Energy Balance Climate Model with Explicit Sea Ice and Snow Physics

Abstract An energy balance climate model (EBCM) is presented having 1) a seasonal cycle; 2) surface-air, land-sea, and latitudinal resolution; 3) simulation of sea ice in terms of a number of explicit physical processes and in such a way that the sea ice fraction in any given zone changes continuously during the course of the seasonal cycle; 4) simulation of a continuously varying land-snow fraction in terms of explicit physical processes; and 5) a detailed treatment of surface and planetary albedo. A semianalytic solution is used which permits use of 6 day time steps, with very little dependence of the simulated climate on the choice of time step length for time steps of 1 to 6 days. Model sensitivity to internal parameter changes is investigated. The temperature response to a doubling of the drag coefficients for the vertical fluxes of latent and sensible heat is complex, and involves radiative constraints, the effect of stronger coupling to the large thermal inertia of the mixed layer, and ice and snow...