CRITICAL REVIEW OF PHYSICAL MODELLING OF SNOW ACCUMULATION ON ROOFS WITH ARBITRARY GEOMETRY

A review of the most significant domestic and, due to numerical superiority, foreign works on physical modelling of snow transport and snow accumulation processes, in particular, for the purpose of determining snow loads on roofs with arbitrary geometry, is presented. The existing practice of development of recommendations on assignment of snow loads in Russian laboratories is considered and critically evaluated. Comparison of do-mesticworks with scientific articles in the advanced world scientific journals and foreign regulatory documents leads to unfavorable conclusions. Recommendations on assigning snow loads, issued by Russian laboratories on the basisof extremely outdated and poorly substantiated methodology, bear a serious risk for evaluating mechan-ical safety of modern structures, for which such recommendations are developed. Recommendations are offered to remedy this current dangerous practice. The article also gives some suggestions on forming a basis for field observations of snow loads on existing roofs.

CRITICAL REVIEW OF MODERN NUMERICAL MODELLING OF SNOW ACCUMULATION ON ROOFS WITH ARBITRARY GEOMETRY

The calculation of snow loads on roofs of buildings and structures with arbitrary geometry is a complex problem, solving which requires simulating snow accumulation with acceptable engineering accuracy. Experiments in wind tunnels, although widely used in recent years, do not allow to reproduce the real full-scale effects of all snow transport subprocesses, since it is impossible to satisfy all the similarity conditions. This situation, coupled with the continuous improvement of mathematical models, numerical methods, computer technologies and related software, makes the development and future implementation of numerical modelling in real construction practice and regulatory documents inevitable. This paper reviews currently existing mathematical models and numerical methods used to calculate the forms of snow deposits. And, although the lack of significant progress in the field of modelling snow accumulation still remains one of the major problems in CFD, use of existing models, supported by field observations and experimental data, allows to reproduce reasonably accurate snow distributions. The importance of the “symbiosis” between classical experimental methods and modern numerical models is specifically emphasized in the paper, as well as the fact that only the joint use of approaches can comprehensively describe modelling of snow accumulation and snow transport and provide better solutions to a wider range of problems.

The statistics of blowing snow occurrences from multi-year autonomous snow flux measurements in the French Alps

Wind-driven snow transport has important implications for the spatial-temporal heterogeneity of snow distribution and snowpack evolution in mountainous areas, such as the European Alps. The climatological and hydrological significance of this region have been extensively investigated using satellite and numerical models. However, knowledge of the spatiotemporal variability of blowing snow is in its infancy because of inaccuracies in satellite-based blowing snow algorithms and the absence of quantitative assessments. Here, we present the spatiotemporal variability and magnitude of blowing snow events, and explore the potential links with ambient meteorological conditions using near surface blowing snow observations from the ISAW outdoor environmental monitoring network. Results show frequent occurrence of blowing snow, and contrasting seasonal variability in the French Alps. On average, monthly blowing snow days range from 5.0 to 14.3 days when using the snow flux threshold of 0.1 g m−2 s−1. The minimum and maximum frequencies of blowing snow days are observed in September and January, respectively, accounting for between 16.7 % and 46.1 % of the month. However, the frequency of monthly blowing snow days varies widely between stations, and this variability is more pronounced at lower threshold levels. Blowing snow events with relatively high magnitudes of snow mass flux (1.0 g m−2 s−1) occur more frequently than low-intensity events (snow mass flux ranges from 0.1 to 0.5 g m−2 s−1). By imposing a minimum duration of 4 h, the monthly cumulative hours with blowing snow occurrences can be up to 255 hours, but show significant seasonal and spatial variability. The considerable variability observed across this region can be explained by contrasting local climate (particularly wind speed and air temperature), snowpack properties, topography and vegetation. The snow-mass transported during relatively high magnitude blowing snow events accounts for about 90 % of all the transported snow mass, highlighting the importance of major events. Blowing snow events that occur with concurrent snowfall are generally associated with intense snow transport. Transport of wet snow and dry snow is mostly concentrated in the range of 0.1 to 0.5 g m−2 s−1 and 0.5 to 1.0 g m−2 s−1, respectively. Understanding the spatiotemporal variability of blowing snow occurrences and the potential links with ambient meteorological conditions is critical for constructing effective avalanche disaster warning systems, and for promoting quantitative evaluation and development of satellite retrieval algorithms and blowing snow models.

Local simulations of snow redistribution by wind with an intermediate-complexity snow cover model driven by different wind downscaling methods

<p>In mountainous terrain, wind-driven transport of deposited snow affects the overall distribution of snow, and can have a significant effect on snowmelt patterns even at coarser resolution.  In an operational modelling perspective, a compromise must be found to represent this complex small-scale process with enough accuracy while mitigating the computational costs of snow cover simulations over large domains. To achieve this compromise, we implemented the SNOWTRAN-3D snow transport module within the FSM intermediate complexity snow cover model. We included a new layering scheme and a historical variable of past snow wetting, but without resolving the snow microstructure. Simulations are run and evaluated over a small mountain range in the Swiss Alps at 25 to 100 m resolution. Being implemented in the model framework of the SLF operational snow hydrology service (OSHD), simulations further benefit from snow data assimilation techniques to provide improved estimates of solid precipitation fields. As complex wind patterns in mountains are the key processes driving snow transport, we tested statistical and dynamical methods to downscale 1 km resolution COSMO winds to better reflect topographically-induced flow patterns. These simulations are a first step working towards the integration of wind transport processes over large domains in an intermediate-complexity and -resolution operational modelling framework.</p>

Multi-scale snowdrift-permitting modelling of mountain snowpack

The interaction of mountain terrain with meteorological processes causes substantial temporal and spatial variability in snow accumulation and ablation. Processes impacted by complex terrain include large-scale orographic enhancement of snowfall, small-scale processes such as gravitational and wind-induced transport of snow, and variability in the radiative balance such as through terrain shadowing. In this study, a multi-scale modelling approach is proposed to simulate the temporal and spatial evolution of high-mountain snowpacks. The multi-scale approach combines atmospheric data from a numerical weather prediction system at the kilometre scale with process-based downscaling techniques to drive the Canadian Hydrological Model (CHM) at spatial resolutions allowing for explicit snow redistribution modelling. CHM permits a variable spatial resolution by using the efficient terrain representation by unstructured triangular meshes. The model simulates processes such as radiation shadowing and irradiance to slopes, blowing-snow transport (saltation and suspension) and sublimation, avalanching, forest canopy interception and sublimation, and snowpack melt. Short-term, kilometre-scale atmospheric forecasts from Environment and Climate Change Canada's Global Environmental Multiscale Model through its High Resolution Deterministic Prediction System (HRDPS) drive CHM and are downscaled to the unstructured mesh scale. In particular, a new wind-downscaling strategy uses pre-computed wind fields from a mass-conserving wind model at 50 m resolution to perturb the mesoscale HRDPS wind and to account for the influence of topographic features on wind direction and speed. HRDPS-CHM was applied to simulate snow conditions down to 50 m resolution during winter 2017/2018 in a domain around the Kananaskis Valley (∼1000 km2) in the Canadian Rockies. Simulations were evaluated using high-resolution airborne light detection and ranging (lidar) snow depth data and snow persistence indexes derived from remotely sensed imagery. Results included model falsifications and showed that both wind-induced and gravitational snow redistribution need to be simulated to capture the snowpack variability and the evolution of snow depth and persistence with elevation across the region. Accumulation of windblown snow on leeward slopes and associated snow cover persistence were underestimated in a CHM simulation driven by wind fields that did not capture lee-side flow recirculation and associated wind speed decreases. A terrain-based metric helped to identify these lee-side areas and improved the wind field and the associated snow redistribution. An overestimation of snow redistribution from windward to leeward slopes and subsequent avalanching was still found. The results of this study highlight the need for further improvements of snowdrift-permitting models for large-scale applications, in particular the representation of subgrid topographic effects on snow transport.

Drifting-snow statistics from multiple-year autonomous measurements in Adélie Land, East Antarctica

Drifting snow is a widespread feature over the Antarctic ice sheet, whose climatological and hydrological significance at the continental scale have been consequently investigated through modelling and satellite approaches. While field measurements are needed to evaluate and interpret model and satellite products, most drifting-snow observation campaigns in Antarctica involved data collected at a single location and over short time periods. With the aim of acquiring new data relevant to the observation and modelling of drifting snow in Antarctic conditions, two remote locations in coastal Adélie Land (East Antarctica) that are 100 km apart were instrumented in January 2010 with meteorological and second-generation IAV Engineering acoustic FlowCapt™ sensors. The data, provided nearly continuously so far, constitute the longest dataset of autonomous near-surface (i.e. within 2 m) measurements of drifting snow currently available over the Antarctic continent. This paper presents an assessment of drifting-snow occurrences and snow mass transport from up to 9 years (2010–2018) of half-hourly observational records collected in one of the Antarctic regions most prone to snow transport by wind. The dataset is freely available to the scientific community and can be used to complement satellite products and evaluate snow-transport models close to the surface and at high temporal frequency.

The role of surface cohesion is wind-driven snow transport

<p>The wind-driven saltation of sediments, such as snow and sand, is responsible for a wide range of geophysical processes. Blowing-snow, in particular, affects snow surface properties and drives snow redistribution in alpine terrain. As such, it is of fundamental importance for avalanche mechanics. One of the most important controls on initiation and development of snow saltation is the surface cohesion induced by ice particle sintering. Although inter-particle cohesion is known to limit the number of grains lifted from the surface through aerodynamic entrainment and granular splash, the role of cohesion in the development of saltation from onset to steady state is still poorly understood. Using a numerical model based on the discrete element method, we show that saltation over cohesive beds sustains itself at wind speeds one order of magnitude smaller than those necessary to initiate it, giving rise to hysteresis in which the occurrence of transport depends on the history of the wind. Our results further suggest that saltation over cohesive beds requires much longer distances to saturate, thereby increasing the size of the smallest stable bed forms.</p>

Shifting Hydrological Processes in a Canadian Agroforested Catchment due to a Warmer and Wetter Climate

This study examines the hydrological sensitivity of an agroforested catchment to changes in temperature and precipitation. A physically based hydrological model was created using the Cold Regions Hydrological Modelling platform to simulate the hydrological processes over 23 years in the Acadie River Catchment in southern Québec. The observed air temperature and precipitation were perturbed linearly based on existing climate change projections, with warming of up to 8 °C and an increase in total precipitation up to 20%. The results show that warming causes a decrease in blowing snow transport and sublimation losses from blowing snow, canopy-intercepted snowfall and the snowpack. Decreasing blowing snow transport leads to reduced spatial variability in peak snow water equivalent (SWE) and a more synchronized snow cover depletion across the catchment. A 20% increase in precipitation is not sufficient to counteract the decline in annual peak SWE caused by a 1 °C warming. On the other hand, peak spring streamflow increases by 7% and occurs 20 days earlier with a 1 °C warming and a 20% increase in precipitation. However, when warming exceeds 1.5 °C, the catchment becomes more rainfall dominated and the peak flow and its timing follows the rainfall rather than snowmelt regime. Results from this study can be used for sustainable farming development and planning in regions with hydroclimatic characteristics similar to the Acadie River Catchment, where climate change may have a significant impact on the dominating hydrological processes.