21,529 research outputs found
SNOWMIP2: An evaluation of forest snow process simulation
The Northern Hemisphere has large areas that are forested and seasonally snow covered. Compared with open areas, forest canopies strongly influence interactions between the atmosphere and snow on the ground by sheltering the snow from wind and solar radiation and by intercepting falling snow, and these influences have important consequences for the meteorology, hydrology and ecology of forests. Many of the land surface models used in meteorological and hydrological forecasting now include representations of canopy snow processes, but these have not been widely tested in comparison with observations. Phase 2 of the Snow Model Intercomparison Project (SnowMIP2) was therefore designed as an intercomparison of surface mass and energy balance simulations for snow in forested areas. Model forcing and calibration data for sites with paired forested and open plots were supplied to modelling groups. Participants in 11 countries contributed outputs from 33 models, and results are published here for sites in Canada, the USA and Switzerland. On average, the models perform fairly well in simulating snow accumulation and ablation, although there is a wide inter-model spread and a tendency to underestimate differences in snow mass between open and forested areas. Most models capture the large differences in surface albedos and temperatures between forest canopies and open snow well. There is, however, a strong tendency for models to underestimate soil temperatures under snow, particularly for forest sites, and this would have large consequences for simulations of runoff and biological processes in the soil
Micrometeorological processes driving snow ablation in an Alpine catchment
Mountain snow covers typically become patchy over the course of a melting season. The snow pattern during melt is mainly governed by the end of winter snow depth distribution and the local energy balance. The objective of this study is to investigate micrometeorological processes driving snow ablation in an Alpine catchment. For this purpose we combine a meteorological model (ARPS) with a fully distributed energy balance model (Alpine3D). Turbulent fluxes above melting snow are further investigated by using data from eddy-correlation systems. We compare modelled snow ablation to measured ablation rates as obtained from a series of Terrestrial Laser Scanning campaigns covering a complete ablation season. The measured ablation rates indicate that the advection of sensible heat causes locally increased ablation rates at the upwind edges of the snow patches. The effect, however, appears to be active over rather short distances except for very strong wind conditions. Neglecting this effect, the model is able to capture the mean ablation rates for early ablation periods but strongly overestimates snow ablation once the fraction of snow coverage is below a critical value. While radiation dominates snow ablation early in the season, the turbulent flux contribution becomes important late in the season. Simulation results indicate that the air temperatures appear to overestimate the local air temperature above snow patches once the snow coverage is below a critical value. Measured turbulent fluxes support these findings by suggesting a stable internal boundary layer close to the snow surface causing a strong decrease of the sensible heat flux towards the snow cover. Thus, the existence of a stable internal boundary layer above a patchy snow cover exerts a dominant control on the timing and magnitude of snow ablation for patchy snow covers.<br/
Intercomparison of snow density measurements: bias, precision, and vertical resolution
Density is a fundamental property of porous media such as snow. A wide range of snow properties and physical processes are linked to density, but few studies have addressed the uncertainty in snow density measurements. No study has yet quantitatively considered the recent advances in snow measurement methods such as micro-computed tomography (uCT) in alpine snow. During the MicroSnow Davos 2014 workshop, different approaches to measure snow density were applied in a controlled laboratory environment and in the field. Overall, the agreement between uCT and gravimetric methods (density cutters) was 5 to 9 %, with a bias o
Statistical properties of fresh snow roughness
We present results from a series of experiments in which fresh snow roughness was measured by means of digital photography and analyzed using the random field approach. The aim of the paper is to investigate the scaling properties of fresh-snow-covered surfaces and to capture key roughness length scales which can characterize the surface geometry and the size of the snow crystals. Results from our experiments show the following: (1) fresh snow roughness exhibits two distinguished scaling regimes, one at scales comparable with the crystals size and another one at larger scales; (2) we confirm that the large scales are built up during snowfall and their scaling behavior is consistent with that of Ballistic Deposition (BD) processes; and (3) we suggest that the crossover length scale separating the two scaling regimes effectively defines a representative length scale of the aggregated snow crystals on the surface. The definition of this length scale is independent of the difficulties associated with measuring snow grain sizes by means of standard microscopic analysis of disaggregated crystals. Furthermore it can be obtained from a low-cost and quick experimental procedure. Results from this study provide a plausible justification for the wide scatter of aerodynamic roughness length values encountered in the literature for fresh snow. Moreover, they provide insight on the key roughness length scales which should be used for the modeling of this parameter
On the saltation of fresh snow in a wind tunnel: profile characterization and single particle statistics
We present experimental results on the snow drift in a turbulent boundary layer over a flat fresh snow-covered surface. Vertical profiles of mass flux and of the distribution of particle diameters were obtained by means of a pair of Snow Particle Counters parallel with measurements of the stream-wise velocity profile. The aim of the paper is to discuss current parameterizations of the vertical mass flux profile for fresh snow and to investigate the range of timescales involved in a developing saltation layer occurring in a turbulent boundary layer. The novelty of the work consists of using an intact fresh snow cover as an erodible surface able to provide realistic snow crystals as drifting particles. Results show that (1) the parameters scaling the vertical mass flux profiles of fresh snow can significantly differ from those given in the literature for ice or compacted snow particles; (2) though drifting snow covers an extremely wide range of temporal scales, the mean time interval between saltating particles ??t ? is the key timescale of the saltation process; (3) ??t ? allows for the optimal reconstruction of the mass flux as a continuous signal and for neglecting the effects related to the heterogeneous distribution of particle size on the mass flux. Implications on the modeling of snow drift and on the processing of field observations are discusse
Evaluation of snow cover and depth simulated by a land-surface model using detailed regional snow observations from Austria
An evaluation is undertaken of the accuracy with which the Joint UK Land Environment Simulator (JULES) can simulate snow cover and depth when driven using data from the Hadley Centre Regional Climate Model. The JULES model provides the facility to diagnose the thermal and hydrological state of the land surface and soil given time-varying inputs of air temperature, wind speed, humidity, shortwave and long-wave radiation, and precipitation. The observed dataset used in this study consists of daily snow depths measurements at 601 climate stations with more than 15 years of observations in the period from January 1976 to December 2000. In this study, the JULES model was driven using two datasets at 25 km horizontal resolution: one produced using the UK Met Office Hadley Centre regional climate model (RCM), HadRM3-P (RCM), the other in which RCM precipitation and air temperature data were replaced with observed values (RCM+PT). The results indicate good agreement between the land-surface model simulations and observations of snow cover at climate stations. The median snow cover accuracy indices for all 601 stations were 89% and 91% for the RCM and the combined RCM+PT driving datasets, respectively, with only a small inter-annual variation. In contrast, the differences between modeled and measured snow depth were much larger. The median values of mean snow depth bias were similar, −0.4 cm for the RCM and −1.2 cm for the RCM+PT, however, the RCM simulation was found to overestimate the observed snow depth at more than 25% of climate stations. The extent to which the results from RCM-driven simulations match observed data is strongly related to the accuracy of the RCM precipitation. The large overestimation has significant impact on the snow mass simulation and the assessment of extreme values in the mountains. We note that even if snow cover can be simulated with a high degree of accuracy, this should not imply a similarly high degree of accuracy in the simulation of snow depth. Model performance was poorest in regions of significant topographic heterogeneity and our findings suggest that the most promising additional model developments should be directed towards computationally-efficient representation of sub-grid topography
Soil erosion by snow gliding - a first quantification attempt in a subalpine area in Switzerland
Snow processes might be one important driver of soil erosion in Alpine grasslands and thus the unknown variable when erosion modelling is attempted. The aim of this study is to assess the importance of snow gliding as a soil erosion agent for four different land use/land cover types in a subalpine area in Switzerland. We used three different approaches to estimate soil erosion rates: sediment yield measurements in snow glide depositions, the fallout radionuclide Cs-137 and modelling with the Revised Universal Soil Loss Equation (RUSLE). RUSLE permits the evaluation of soil loss by water erosion, the Cs-137 method integrates soil loss due to all erosion agents involved, and the measurement of snow glide deposition sediment yield can be directly related to snow-glide-induced erosion. Further, cumulative snow glide distance was measured for the sites in the winter of 2009/2010 and modelled for the surrounding area and long-term average winter precipitation (1959-2010) with the spatial snow glide model (SSGM). Measured snow glide distance confirmed the presence of snow gliding and ranged from 2 to 189 cm, with lower values on the north-facing slopes. We observed a reduction of snow glide distance with increasing surface roughness of the vegetation, which is an important information with respect to conservation planning and expected and ongoing land use changes in the Alps. Snow glide erosion estimated from the snow glide depositions was highly variable with values ranging from 0.03 to 22.9 t ha(-1) yr(-1) in the winter of 2012/2013. For sites affected by snow glide deposition, a mean erosion rate of 8.4 t ha(-1) yr(-1) was found. The difference in long-term erosion rates determined with RUSLE and Cs-137 confirms the constant influence of snow-glide-induced erosion, since a large difference (lower proportion of water erosion compared to total net erosion) was observed for sites with high snow glide rates and vice versa. Moreover, the difference between RUSLE and Cs-137 erosion rates was related to the measured snow glide distance (R-2 = 0.64; p > 0.005) and to the snow deposition sediment yields (R-2 = 0.39; p = 0.13). The SSGM reproduced the relative difference of the measured snow glide values under different land uses and land cover types. The resulting map highlighted the relevance of snow gliding for large parts of the investigated area. Based on these results, we conclude that snow gliding appears to be a crucial and non-negligible process impacting soil erosion patterns and magnitude in subalpine areas with similar topographic and climatic conditions
Vegetation, topography and snow melt at the Forest-Tundra Ecotone in arctic Europe: a study using synthetic aperture radar
This research was conducted as part of DART (Dynamic Response of the Forest-Tundra Ecotone to Environmental Change), a four year (1998-2002) European Commission funded international programme of research addressing the potential dynamic response of the (mountain birch) forest-tundra ecotone to environmental change. Satellite remote sensing was used to map landscape scale (lO(^1)-lO(^3) m) patterns of vegetation and spatial dynamics of snow melt at the forest-tundra ecotone at three sites along ca. an 8º latitudinal gradient in the Fermoscandian mountain range. Vegetation at the forest-tundra ecotone was mapped using visible -near infrared (VIR) satellite imagery, with class definition dependent on the timing of the acquisition of imagery (related to highly dynamic vegetation phenology) and spatial variation in the FTE. Multi-temporal spacebome ERS-2 synthetic aperture radar (SAR) was used for mapping snow melt. Comprehensive field measurements of snow properties and meteorological data combined with a physically based snow backscatter model indicated potential for mapping wet snow cover at each site. Significant temporal backscatter signatures enabled a classification algorithm to be developed to map the pattern of snow melt across the forest- tundra ecotone. However, diurnal and seasonal melt-freeze effects relative to the timing of ERS-2 SAR image acquisition effectively reduce the temporal resolution of data. Further, the study sites with large topographic variation and complex vegetative cover, provided a challenging operating environment and problems were identified with the robustness of classification during the later stages of snow melt because of the effects of vegetation. Significant associations were identified between vegetation, topography, and snow melt despite limitations in the snow mapping
Estimation of soil redistribution rates due to snow cover related processes in a mountainous area (Valle d'Aosta, NW Italy)
Mountain areas are widely affected by soil erosion, which is generally linked to runoff processes occurring in the growing season and snowmelt period. Also processes like snow gliding and full-depth snow avalanches may be important factors that can enhance soil erosion, however the role and importance of snow movements as agents of soil redistribution are not well understood yet. The aim of this study was to provide information on the relative importance of snow related processes in comparison to runoff processes. In the study area, which is an avalanche path characterized by intense snow movements, soil redistribution rates were quantified with two methods: (i) by field measurements of sediment yield in an avalanche deposition area during 2009 and 2010 winter seasons; (ii) by caesium-137 method, which supplies the cumulative net soil loss/gain since 1986, including all the soil erosion processes. The snow related soil accumulation estimated with data from the deposit area (27.5 Mg ha<sup>−1</sup> event<sup>−1</sup> and 161.0 Mg ha<sup>−1</sup> event<sup>−1</sup>) was not only higher than the yearly sediment amounts, reported in literature, due to runoff processes, but it was even more intense than the yearly total deposition rate assessed with <sup>137</sup>Cs (12.6 Mg ha<sup>−1</sup> yr<sup>−1</sup>). The snow related soil erosion rates estimated from the sediment yield at the avalanche deposit area (3.7 Mg ha<sup>−1</sup> and 20.8 Mg ha<sup>−1</sup>) were greater than the erosion rates reported in literature and related to runoff processes; they were comparable to the yearly total erosion rates assessed with the <sup>137</sup>Cs method (13.4 Mg ha<sup>−1</sup> yr<sup>−1</sup> and 8.8 Mg ha<sup>−1</sup> yr<sup>−1</sup>). The <sup>137</sup>Cs method also showed that, where the ground avalanche does not release, the erosion and deposition of soil particles from the upper part of the basin was considerable and likely related to snow gliding. Even though the comparison of both the approaches is linked to high methodological uncertainties, mainly due to the different spatial and temporal scales considered, we still can deduce, from the similarity of the erosion rates, that soil redistribution in this catchment is driven by snow movement, with a greater impact in comparison to the runoff processes occurring in the snow-free season. Nonetheless, the study highlights that soil erosion processes due to the snow movements should be considered in the assessment of soil vulnerability in mountain areas, as they significantly determine the pattern of soil redistribution
Winter accumulation in the percolation zone of Greenland measured by airborne radar altimeter
We here determine the surface elevation and the winter snow accumulation rate along a profile in the percolation zone of the Greenland Ice Sheet from data collected with ESA's Airborne SAR/Interferometric Radar Altimeter System (ASIRAS) in spring 2004. The altimeter data show that in addition to a backscatter peak at the air-snow interface a dominant second peak occurs. This second peak appears due to the strong scattering properties of the last summer surface layer. A robust re-tracking algorithm was developed that enables the tracking of both interfaces. Utilizing this algorithm, the winter snow thickness is estimated to 1.50 +/- 0.13 m. This compares favorably with field measurements (1.43 +/- 0.04 m). The snow depth estimates in combination with snow-density measurements of 420 kg m(-3) give a mean winter mass accumulation rate of 63 cm water equivalent (w.e.) and a spatial variation of +/-6 cm w.e. Furthermore a strong correlation is found between surface gradient and accumulation rate, with higher accumulation rate in flatter areas. The approach adopted here has significant potential for remote measurements of winter snow accumulation rate across ice sheets at larger spatial scales
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