Showing papers on "Snowpack published in 2008"

Attribution of declining Western U.S. Snowpack to human effects

Abstract: Observations show snowpack has declined across much of the western United States over the period 1950–99. This reduction has important social and economic implications, as water retained in the snowpack from winter storms forms an important part of the hydrological cycle and water supply in the region. A formal model-based detection and attribution (D–A) study of these reductions is performed. The detection variable is the ratio of 1 April snow water equivalent (SWE) to water-year-to-date precipitation (P), chosen to reduce the effect of P variability on the results. Estimates of natural internal climate variability are obtained from 1600 years of two control simulations performed with fully coupled ocean–atmosphere climate models. Estimates of the SWE/P response to anthropogenic greenhouse gases, ozone, and some aerosols are taken from multiple-member ensembles of perturbation experiments run with two models. The D–A shows the observations and anthropogenically forced models have greater SWE/P reductions than can be explained by natural internal climate variability alone. Model-estimated effects of changes in solar and volcanic forcing likewise do not explain the SWE/P reductions. The mean model estimate is that about half of the SWE/P reductions observed in the west from 1950 to 1999 are the result of climate changes forced by anthropogenic greenhouse gases, ozone, and aerosols.

Principles of snow hydrology

Abstract: Preface 1. Introduction 2. Snow climatology and snow distribution 3. Snowpack condition 4. Ground-based snowfall and snowpack measurements 5. Remote sensing of the snowpack 6. Snowpack energy exchange: basic theory 7. Snowpack energy exchange: topographic and forest effects 8. Snowfall, snowpack and meltwater chemistry 9. Snowmelt runoff processes 10. Modelling snowmelt runoff 11. Snowmelt Runoff Model (SRM) 12. Snowpack management and modifications Appendices Index.

Topographic controls on snow distribution, soil moisture, and species diversity of herbaceous alpine vegetation, Niwot Ridge, Colorado

Abstract: [1] The nature of the snowpack has the potential to strongly influence the patterns of alpine plant productivity and composition by governing soil moisture levels, growing season duration and the thermal regime of alpine soils. This study evaluates these relationships by modeling the interrelationships of snow depth, snow water equivalent (SWE), snow disappearance rate, soil moisture, attributes of the alpine plant community and selected terrain factors using decision-tree techniques at Niwot Ridge, Colorado Front Range. The modeling results showed a strong correlation (r 2 > 0.9, P < 0.001) between the snow disappearance rate and SWE and terrain factors that control the degree of shelter and exposure of a given local and elevation. The model was sufficiently robust to predict the spatial distribution of the snowpack for 12 years that exhibited average snow fall (r 2 = 0.8, P < 0.001), but yielded lower correlation (r 2 = 0.2, P < 0.001) in drought years. Soil moisture was significantly correlated (r 2 = 0.7, P < 0.001) with snow-fall amounts and terrain factors; however, meltwater and summer rain offset the potential soil moisture deficit in windward sites. Annual plant biomass did not correlate well with snow attributes and soil moisture because the cascading impact of topography on snowpack and soil moisture was not well captured by measurements of aboveground biomass. In contrast, the species richness index was significantly correlated with snow depth and soil moisture (r 2 = 0.7, P < 0.001), thereby demonstrating the importance of snow on some attributes of the alpine plant community.

A comparison of measurement methods: terrestrial laser scanning, tachymetry and snow probing for the determination of the spatial snow-depth distribution on slopes

Abstract: Determination of the spatial snow-depth distribution is important in potential avalanche- starting zones, both for avalanche prediction and for the dimensioning of permanent protection measures. Knowledge of the spatial distribution of snow is needed in order to validate snow depths computed from snowpack and snowdrift models. The inaccessibility of alpine terrain and the acute danger of avalanches complicate snow-depth measurements (e.g. when probes are used), so the possibility of measuring the snowpack using terrestrial laser scanning (TLS) was tested. The results obtained were compared to those of tachymetry and manual snow probing. Laser measurements were taken using the long-range laser profile measuring system Riegl LPM-i800HA. The wavelength used by the laser was 0.9 mm (near-infrared). The accuracy was typically within 30 mm. The highest point resolution was 30 mm when measured from a distance of 100 m. Tachymetry measurements were carried out using Leica TCRP1201 systems. Snowpack depths measured by the tachymeter were also used. The datasets captured by tachymetry were used as reference models to compare the three different methods (TLS, tachymetry and snow probing). This is the first time that the accuracy of TLS systems in snowy and alpine weather conditions has been quantified. The relative accuracy between the three measurement methods is bounded by a maximum offset of � 8 cm. Between TLS and the tachymeter the standard deviation is 1 ¼ 2 cm, and between manual probing and TLS it is up to 1 ¼ 10 cm, for maximum distances for the TLS and tachymeter of 300 m.

Rain versus Snow in the Sierra Nevada, California: Comparing Doppler Profiling Radar and Surface Observations of Melting Level

Abstract: The maritime mountain ranges of western North America span a wide range of elevations and are extremely sensitive to flooding from warm winter storms, primarily because rain falls at higher elevations and over a much greater fraction of a basin’s contributing area than during a typical storm. Accurate predictions of this rain–snow line are crucial to hydrologic forecasting. This study examines how remotely sensed atmospheric snow levels measured upstream of a mountain range (specifically, the bright band measured above radar wind profilers) can be used to accurately portray the altitude of the surface transition from snow to rain along the mountain’s windward slopes, focusing on measurements in the Sierra Nevada, California, from 2001 to 2005. Snow accumulation varies with respect to surface temperature, diurnal cycles in solar radiation, and fluctuations in the free-tropospheric melting level. At 1.5°C, 50% of precipitation events fall as rain and 50% as snow, and on average, 50% of measured pre...

Quantifying Uncertainty in Modeling Snow Microwave Radiance for a Mountain Snowpack at the Point-Scale, Including Stratigraphic Effects

Abstract: Merging microwave radiances and modeled estimates of snowpack states in a data assimilation scheme is a potential method for snowpack characterization. A radiance assimilation scheme for snow requires a land surface model (LSM) coupled to a radiative transfer model (RTM). In this paper, we explore the degree of model fidelity required in order for radiance assimilation to yield benefits for snowpack characterization. Specifically, we characterize the uncertainty of Microwave Emission Model for Layered Snowpacks (MEMLS) radiance predictions by quantifying model accuracy and sensitivity to the following: (1) the LSM snowpack layering scheme and (2) the properties of the snow layers, including melt-refreeze ice layers. MEMLS was consistent with the measured brightness temperatures at 18.7 and 36.5 GHz with a bias (mean absolute error) of 0.1 K (3.1 K) for the vertical polarization and 3.4 K (9.3 K) for the horizontal polarization. An error in the predictions at horizontal polarization is due to uncertainty in ice-layer properties. It was found that in order for predicted brightness temperatures from the coupled LSM and RTM to be adequate for radiance assimilation purposes, the following must be satisfied: (1) the LSM snowpack layering scheme must accurately represent the stratigraphic snowpack layers; (2) dynamics of melt-refreeze ice layers must be modeled explicitly, and the predicted density of melt-refreeze layers must be accurate within ; and (3) the MEMLS correlation length must be predicted within 0.016 mm, or effective optical grain diameter must be predicted within 0.045 mm. Recommendations for future field measurements are made.

Spatially distributed temperatures at the base of two mountain snowpacks measured with fiber-optic sensors

Abstract: Snowpack base temperatures vary during accumulation and diurnally. Their measurement provides insight into physical, biological and chemical processes occurring at the snow/soil interface. Recent advances in Raman-spectra instruments, which use the scattered light in a standard telecommunications fiber-optic cable to infer absolute temperature along the entire length of the fiber, offer a unique opportunity to obtain basal snow temperatures at resolutions of 1 m, 10 s, and 0.18C. Measurements along a 330 m fiber over 24 hours during late-spring snowmelt at Mammoth Mountain, California, USA, showed basal snow temperatures of 0 � 0.28C using 10 s averages. Where the fiber- optic cable traversed bare ground, surface temperatures approached 408C during midday. The durability of the fiber optic was excellent; no major damage or breaks occurred through the winter of burial. Data from the Dry Creek experimental watershed in Idaho across a small stream valley showed little variability of temperature on the northeast-facing, snow-covered slope, but clearly showed melting patterns and the effects of solar heating on southwest-facing slopes. These proof-of-concept experiments show that the technology enables more detailed spatial and temporal coverage than traditional point measurements of temperature.

The Effects of Layers in Dry Snow on Its Passive Microwave Emissions Using Dense Media Radiative Transfer Theory Based on the Quasicrystalline Approximation (QCA/DMRT)

Abstract: A model for the microwave emissions of multilayer dry snowpacks, based on dense media radiative transfer (DMRT) theory with the quasicrystalline approximation (QCA), provides more accurate results when compared to emissions determined by a homogeneous snowpack and other scattering models. The DMRT model accounts for adhesive aggregate effects, which leads to dense media Mie scattering by using a sticky particle model. With the multilayer model, we examined both the frequency and polarization dependence of brightness temperatures (Tb's) from representative snowpacks and compared them to results from a single-layer model and found that the multilayer model predicts higher polarization differences, twice as much, and weaker frequency dependence. We also studied the temporal evolution of Tb from multilayer snowpacks. The difference between Tb's at 18.7 and 36.5 GHz can be 5 K lower than the single-layer model prediction in this paper. By using the snowpack observations from the Cold Land Processes Field Experiment as input for both multi- and single-layer models, it shows that the multilayer Tb's are in better agreement with the data than the single-layer model. With one set of physical parameters, the multilayer QCA/DMRT model matched all four channels of Tb observations simultaneously, whereas the single-layer model could only reproduce vertically polarized Tb's. Also, the polarization difference and frequency dependence were accurately matched by the multilayer model using the same set of physical parameters. Hence, algorithms for the retrieval of snowpack depth or water equivalent should be based on multilayer scattering models to achieve greater accuracy.

Evaluation of miniature temperature‐loggers to monitor snowpack evolution at mountain permafrost sites, northwestern Canada

Abstract: A technique to monitor snowpack development using miniature temperature-loggers mounted in a vertical array is evaluated from nearly 100 site-years of measurements in northwestern Canada. The method shows good agreement between interpreted values and actual snow depths checked during site visits. Inferred snowpack build-up and ablation follow the patterns recorded at nearby climatological stations while absolute amounts and the duration of snow cover vary with elevation and vegetation type. Interpretation of snowpack evolution was possible at 93 per cent of the monitoring sites, a success rate that is judged to be acceptable given the low costs of the technique and the difficulty of obtaining the same information through other methods. Copyright © 2008 John Wiley & Sons, Ltd.

Improving predictions of summer climate change in the United States

Abstract: [1] Across vast, agriculturally intensive regions of the United States, the spread in predictions of summer temperature and soil moisture under global warming is curiously elevated in current climate models. Some models show modest warming of 2-3C° and little drying or slight moistening by the 22nd century, while at the other extreme are simulations with warming as large as 7-8C° and 20-40% reductions in soil moisture. We show this region of large spread arises from differences in simulations of snow albedo feedback. During winter and early spring, models with strong snow albedo feedback exhibit large reductions in snowpack and hence water storage. This water deficit persists in summer soil moisture, with reduced evapotranspiration yielding warmer temperatures. Comparison of simulated feedback strength to observations of the feedback from the current climate's seasonal cycle suggests the inter-model differences are excessive. At the same time, the multi-model mean feedback strength agrees reasonably well with the observed value. We estimate that if the next generation of models were brought into line with observations of snow albedo feedback, the unusually wide divergence in simulations of summer warming and drying over the US would shrink by roughly one third to one half.

Spatiotemporal Characteristics of Snowpack Density in the Mountainous Regions of the Western United States

Abstract: Snow density is calculated as a ratio of snow water equivalent to snow depth. Until the late 1990s, there were no continuous simultaneous measurements of snow water equivalent and snow depth covering large areas. Because of that, spatiotemporal characteristics of snowpack density could not be well described. Since then, the Natural Resources Conservation Service (NRCS) has been collecting both types of data daily throughout the winter season at snowpack telemetry (SNOTEL) sites located in the mountainous areas of the western United States. This new dataset provided an opportunity to examine the spatiotemporal characteristics of snowpack density. The analysis of approximately seven years of data showed that at a given location and throughout the winter season, year-to-year snowpack density changes are significantly smaller than corresponding snow depth and snow water equivalent changes. As a result, reliable climatological estimates of snow density could be obtained from relatively short records. ...

A method for the detection of the severe rain‐on‐snow event on Banks Island, October 2003, using passive microwave remote sensing

Abstract: [1] Severe wintertime rain-on-snow (ROS) events create a strong ice layer (or layers) in the snow on arctic tundra that act as a barrier to ungulate grazing. They are linked with large-scale ungulate (reindeer, caribou, elk, and musk-ox) herd declines via starvation and reduced calf production rate when the animals are unable to penetrate the resulting subsnowpack ice layer. ROS events also produce considerable perturbation in the mean wintertime soil temperature under the snowpack. ROS is a sporadic but well-known and significant phenomenon that is currently very poorly documented. Characterization of the distribution and occurrence of severe ROS events is based only on anecdotal evidence, indirect observations of carcasses found adjacent to iced snowpacks, and irregular detection by a sparse observational weather network. We have analyzed in detail a particular ROS event that took place on Banks Island in early October 2003 that resulted in the death of 20,000 musk oxen. We make use of multifrequency passive microwave imagery from the Special Sensor Microwave Imager satellite sensor suite in conjunction with a strong-fluctuation-theory (SFT) emissivity model. We show that a combination of time series analysis and cluster analysis based on microwave spectral gradients and polarization ratios provides a means to detect the stages of the ROS event resulting from the modification of the vertical structure of the snowpack, specifically wetting the snow, the accumulation of liquid water at the base of the snow during the rain event, and the subsequent modification of the snowpack after refreezing. SFT model analysis provides quantitative confirmation of our interpretation of the evolution of the microwave properties of the snowpack as a result of the ROS event. In addition to the grain coarsening owing to destructive metamorphism, we detect the presence of the internal water and ice layers, directly identifying the physical properties producing the hazardous conditions. This analysis offers the potential to characterize both the frequency and global distribution of ROS using multifrequency satellite passive microwave imagery.

The Impact of Snow Model Complexity at Three CLPX Sites

Abstract: Many studies have developed snow process understanding by exploring the impact of snow model complexity on simulation performance. This paper revisits this topic using several recently developed land surface models, including the Simplified Simple Biosphere Model (SSiB); Noah; Variable Infiltration Capacity (VIC); Community Land Model, version 3 (CLM3); Snow Thermal Model (SNTHERM); and new field measurements from the Cold Land Processes Field Experiment (CLPX). Offline snow cover simulations using these five snow models with different physical complexity are performed for the Rabbit Ears Buffalo Pass (RB), Fraser Experimental Forest headquarters (FHQ), and Fraser Alpine (FA) sites between 20 September 2002 and 1 October 2003. These models simulate the snow accumulation and snowpack ablation with varying skill when forced with the same meteorological observations, initial conditions, and similar soil and vegetation parameters. All five models capture the basic features of snow cover dynamics but show remarkable discrepancy in depicting snow accumulation and ablation, which could result from uncertain model physics and/or biased forcing. The simulated snow depth in SSiB during the snow accumulation period is consistent with the more complicated CLM3 and SNTHERM; however, early runoff is noted, owing to neglected water retention within the snowpack. Noah is consistent with SSiB in simulating snow accumulation and ablation at RB and FA, but at FHQ, Noah underestimates snow depth and snow water equivalent (SWE) as a result of a higher net shortwave radiation at the surface, resulting from the use of a small predefined maximum snow albedo. VIC and SNTHERM are in good agreement with each other, and they realistically reproduce snow density and net radiation. CLM3 is consistent with VIC and SNTHERM during snow accumulation, but it shows early snow disappearance at FHQ and FA. It is also noted that VIC, CLM3, and SNTHERM are unable to capture the observed runoff timing, even though the water storage and refreezing effects are included in their physics. A set of sensitivity experiments suggest that Noah’s snow simulation is improved with a higher maximum albedo and that VIC exhibits little improvement with a larger fresh snow albedo. There are remarkable differences in the vegetation impact on snow simulation for each snow model. In the presence of forest cover, SSiB shows a substantial increase in snow depth and SWE, Noah and VIC show a slight change though VIC experiences a later onset of snowmelt, and CLM3 has a reduction in its snow depth. Finally, we observe that a refined precipitation dataset significantly improves snow simulation, emphasizing the importance of accurate meteorological forcing for land surface modeling.

The effect of refreezing on the isotopic composition of melting snowpack

Abstract: The isotopic composition of solid and liquid portions of natural melting snowpack is investigated in detail by the separating of liquid water from snow grains at different depths of the snowpack. The slope of the δD–δ18O line for the liquid phase is found to be lower than for the solid phase. This is proved to be due to the isotopic fractionation occurring in the melt–freeze mass exchange within the snowpack. Melting of the snowpack has no clear impact on the δD–δ18O line for the solid phase, but the slope of the δD–δ18O line for the liquid shows an overall slight decrease in the melting period. When the snowpack is refrozen, the refreezing process would inevitably cause the slope of the solid phase to decrease because of the discrepancy between the slopes of the two phases. Thus the slope of the solid would become lower and lower as the diurnal melt–freeze episodes cycle throughout the melting season. This effect is then demonstrated by looking into the isotopic composition changes of glacier firn. The extent of the effect depends on the snowpack properties and environmental conditions. The slope changes also result in a decreasing trend in deuterium excess. Copyright © 2007 John Wiley & Sons, Ltd.

Influence of canopy density on snow distribution in a temperate mountain range

Abstract: We analyse spatial variability and different evolution patterns of snowpack in a mixed beech–fir stand in the central Pyrenees. Snow depth and density were surveyed weekly along six transects of contrasting forest cover during a complete accumulation and melting season; we also surveyed a sector unaffected by canopy cover. Forest density was measured using the sky view factor (SVF) obtained from digital hemispherical photographs. During periods of snow accumulation and melting, noticeable differences in snow depth and density were found between the open site and those areas covered by forest canopy. Principal component analysis provided valuable information in explaining these observations. The results indicate a high variability in snow accumulation within forest areas related to differences in canopy density. Maximum snow water equivalent (SWE) was reduced by more than 50% beneath dense canopies compared with clearings, and this difference increased during the melting period. We also found significant temporal variations: when melting began in sectors with low SVF, most of the snow had already thawed in areas with high SVF. However, specific conditions occasionally produced a different response of SWE to forest cover, with lower melting rates observed beneath dense canopies. The high values of correlation coefficients for SWE and SVF (r > 0·9) indicate the reliability of predicting the spatial distribution of SWE in forests when only a moderate number of observations are available. Digital hemispherical photographs provide an appropriate tool for this type of analysis, especially for zenith angles in the range 35–55 . Copyright © 2007 John Wiley & Sons, Ltd.

Isotopic variation of snow cover and streamflow in response to changes in canopy structure in a snow‐dominated mountain catchment

Abstract: Isotopic composition of snow cover and streamflow was determined in a snow-dominated, forested watershed to quantify the spatial variability and processes that alter stable isotope (oxygen-18, 18O and deuterium, 2H) composition under different forest canopy conditions (clear-cut, partial-cut (thinned), and unimpacted forest). Snow sampling was carried out on 4 days in late winter and early spring 2006. Meteorological data, precipitation, and streamflow were continuously monitored during the study. Isotope analyses of precipitation samples were conducted weekly through the 2005–2006 snow season. Values of δ18O varied between − 22·0 and − 9·5‰ , and δ2H varied between − 170 and − 76‰ . Isotope concentrations from snowpack samples varied between − 17·5 and − 13·8‰ for δ18O, and between − 129 and − 102‰ for δ2H. These ranges reflect differences in precipitation, accumulation, sublimation, and melting of the snow cover. Streamflow samples were collected during the snowmelt season from two locations every alternate day from the beginning of April until the end of May. Streamflow and snow from a partial-cut and an uncut forest were enriched in the heavy isotopes (18O and 2H) relative to streamflow and snow from a clear-cut forest. Based on the low water contents of the snowpack under dense canopies, we infer that the isotope enrichment resulted primarily from sublimation of snow intercepted by the canopy, with more enrichment in denser canopies. There was no significant correlation between snowpack isotope concentration and altitude. Results indicate that variations in canopy structure can alter snow isotope composition. This finding will provide a useful index of snowpack sublimation, and thus, improved parameterization of distributed hydrological models. Copyright © 2008 John Wiley & Sons, Ltd.

Simulation of seasonal snow-cover distribution for glacierized sites on Sonnblick, Austria, with the Alpine3D model

Abstract: A detailed model of Alpine surface processes is used to simulate the amount of preferential deposition as well as redistribution of snow due to snowdrift for two alpine glaciers (Goldbergkees and Kleinfleiskees, Austrian Alps). The sequence of snow-cover modelling consists of the simulation of the wind field with a mesoscale atmospheric model, a three-dimensional finite-element drift module, an energy-balance module and a snowpack module. All modules with the exception of the wind-field model are integrated within the Alpine3D model frame. The drift module of Alpine3D distinguishes between saltation and suspension and is able to capture preferential deposition of snow precipitation and redistribution of previously deposited snow. Validation of the simulated snow depth is done using the spatially dense snow-probing dataset collected during a campaign in May 2003. Simulated snow depths agree with measurements during winter 2002/03 at locations with detailed snow-height monitoring, taking into account the high spatial variability of snow depth on the glacier. Moreover, comparison of snow accumulation from model results with detailed probing on 1 May 2003 for the total glacier area shows that Alpine3D is able to capture major patterns of spatial distribution of snow accumulation. For the first time, the Alpine3D approach of using high-resolution wind fields from a meteorological model and a physical description of snow transport could be validated for a very steep glacierized area and for a full accumulation season. The results show that drift is a dominant factor to be considered for detailed glacier mass balances. Another dominant factor not considered in this study may be snow redistribution due to avalanches.

Modeling Soil Moisture Processes and Recharge under a Melting Snowpack

Abstract: Recharge into bedrock under a melting snowpack is being investigated as part of a study designed to understand hydrologic processes involving snow at Yosemite National Park in the Sierra Nevada Mountains of California. Snowpack measurements, accompanied by water content and matric potential measurements of the soil under the snowpack, allowed for estimates of infiltration into the soil during snowmelt, and percolation into the bedrock. Infiltration rates into the soil exceeded the permeability of the bedrock and caused ponding to be sustained at the soil-bedrock interface during the snow melt period. During a 7-day period with no measured snowmelt, drainage of the ponded water into the underlying fractured granitic bedrock was estimated to be 16 mm/day. The numerical simulator, TOUGH2, was used to reproduce the field data and evaluate the potential for vertical flow into the fractured bedrock or lateral flow at the bedrock/soil interface. The field data and model results support the notion that although most snowmelt on shallow soils overlying relatively impermeable upland bedrock tends to run off and contribute directly to streamflow, at least some of the snowmelt can infiltrate and potentially provide recharge to local or regional aquifers.

Characterization of Errors in a Coupled Snow Hydrology–Microwave Emission Model

Abstract: Traditional approaches to the direct estimation of snow properties from passive microwave remote sensing have been plagued by limitations such as the tendency of estimates to saturate for moderately deep snowpacks and the effects of mixed land cover within remotely sensed pixels. An alternative approach is to assimilate satellite microwave emission observations directly, which requires embedding an accurate microwave emissions model into a hydrologic prediction scheme, as well as quantitative information of model and observation errors. In this study a coupled snow hydrology [Variable Infiltration Capacity (VIC)] and microwave emission [Dense Media Radiative Transfer (DMRT)] model are evaluated using multiscale brightness temperature (TB) measurements from the Cold Land Processes Experiment (CLPX). The ability of VIC to reproduce snowpack properties is shown with the use of snow pit measurements, while TB model predictions are evaluated through comparison with Ground-Based Microwave Radiometer (G...

HONO emissions from snow surfaces

Abstract: Photochemical production of NO_x and HONO from surface snow can significantly impact the NO_x, OH, and O_3 budgets in the overlying atmosphere. NO_x production is driven by the solar photolysis of NO_3^− within or at the surface of snowpacks. HONO, however, is a secondary species that involves H-atom transfer between natural donors and photogenerated NO_2. Here we investigate the mechanism of HONO generation in snowpacks by exploring how its emissions respond to on-and-off illumination and temperature cycles, and to the addition of various snow dopants. The presence of humic substances within or at the surface of the snowpack significantly enhances, and may be an essential requisite for HONO production. Emission fluxes of NO, NO_2, and HONO from snow surfaces were measured under controlled temperature, ozone mixing ratio and actinic flux conditions. We used natural mid-latitude surface snow as the snow substrate. Their combined peak emission fluxes reached up to ~3 × 10^(10) molecules cm^(−2) s^(−1), ~10^3 times larger than typical emissions from polar snowpacks. Less than 1% of available N was released in these experiments. We report significant post-irradiation HONO emissions from the snow. Present results indicate a strong, direct correlation between HONO emissions and the HULIS (humic-like substances) content of the snow surface.

The effect of soil freezing on N cycling: comparison of two headwater subcatchments with different vegetation and snowpack conditions in the northern Hokkaido Island of Japan

Abstract: Climate change models predict that the snowpacks of temperate forests will develop later and be shallower resulting in a higher propensity for soil freezing In the northern most island of Japan, Hokkaido, snowpack depth decreases from west to east This snowpack depth gradient provided a unique opportunity to test the effects of variable snowpack and soil freezing on N biogeochemistry The Shibecha Northern Catchment in Shibecha Experimental Forest, eastern Hokkaido had deciduous trees and a mean annual snowpack of 07 m while the M3 catchment in Uryu Experimental Forest, western Hokkaido had mixed deciduous and coniferous tree species and a mean annual snowpack of 20 m We conducted a field study (October 2004–April 2005) to determine if differences in Shibecha and Uryu soil extractable N, N mineralization, and nitrification were controlled by the variability in soil freezing during winter or tree species composition that affected the quality of the forest floor The mixed deciduous and coniferous trees forming the Uryu forest floor had a higher C:N ratio (250 vs 224 at Shibecha), higher lignin:N ratio (15 vs 88), and higher lignin concentrations (028 vs 018 g lignin g−1) These differences in forest floor quality contributed to higher net N mineralization and nitrification in Shibecha compared to Uryu In Shibecha, soil remained frozen for the entire study For Uryu, except for an early period with cold temperatures and no snow, the soil generally remained unfrozen As a result of the early winter cold period and soil freezing, extractable soil NH 4 + did not change but NO 3 − increased Reciprocal 0–5 cm mineral soil transplants made between Shibecha and Uryu and incubated during winter at 0, 5, and 30 cm suggested that soil freezing resulted in greater net N mineralization yet lower nitrification regardless of the soil origin The effect of soil freezing should be considered when evaluating differences in N dynamics between temperate ecosystems having a propensity for soil freezing

Fracture propagation propensity in relation to snow slab avalanche release: Validating the Propagation Saw Test

Abstract: [1] The ‘Propagation Saw Test’ (PST) was designed to assess the fracture propagation propensity of weak snowpack layers in relation to snow slab avalanche release. Its predictions were tested against independent field observations of weak layer fracture initiation and slope-scale fracture propagation (e.g., avalanche release). A total of 170 tests were performed at 23 sites. Approximately 76% of tests correctly predicted the observed slope-scale fracture propagation or lack thereof; however, 20% of tests predicted that propagation would not occur at sites that had recently propagated fractures. The predictive accuracy of the dataset improves if only test columns approximately 1.0 m long are selected. Critical fracture energy release rate calculations show that the lowest values are found in snowpacks where fractures initiated but did not propagate. This suggests that physical descriptions of propagation propensity in weak snowpack layers should include a sustainability term.