Canopy Snow Research Articles

Forest gap effects on snow storage in the transitional climate of the Eastern Cascade Range, Washington, United States

Forest thinning and gap creation are being implemented across the western United States of America (USA) to reduce wildfire and forest mortality risk as the climate warms. The Eastern Cascades in Washington, USA, is in a transitional zone between maritime and continental climate conditions and represents a data gap in observations describing the relationship between forest density and snowpack. We collected 3 years of snow observations across a range of forest densities to characterize how forest management efforts in this region may influence the magnitude and duration of snow storage. Observations indicate that peak snow storage magnitude in small gaps ranges from the same to over twice that observed in unburned forest plots in the Eastern Cascades. However, differences in snow duration are generally small. Across all Eastern Cascade sites and years, we observed a median difference of snow storage lasting 7 days longer in gaps as compared to nearby forest plots. A notable exception to this pattern occurred at one north-facing site, where snow lasted 30 days longer in the gap. These observations of similar snow storage duration in the Eastern Cascades are attributed to minimal differences in canopy snow interception processes between forests and gaps at some sites, and to higher ablation rates that counterbalance the higher snow accumulation in the gaps at other sites. At the north-facing site, more snow accumulated in the gap, and ablation rates in the open gap were similar to the shaded forest due to the aspect of the site. Thus, snow storage duration was much longer in the gap. Together, these data suggest that prescriptions to reduce forest density through thinning and creating gaps may increase the overall amount of snow storage by reducing loss due to sublimation and melting of canopy-intercepted snow. However, reducing forest density in the Eastern Cascades is unlikely to buffer climate-induced shortening of snow storage duration, with the possible exception of gap creation in north-facing forests. Lastly, these observations fill a spatial and climatic data gap and can be used to support hydrological modeling at spatial and temporal scales that are relevant to forest management decisions.

Challenges and Capabilities in Estimating Snow Mass Intercepted in Conifer Canopies With Tree Sway Monitoring

AbstractSnowpack accumulation in forested watersheds depends on the amount of snow intercepted in the canopy and its partitioning into sublimation, unloading, and melt. A lack of canopy snow measurements limits our ability to evaluate models that simulate canopy processes and predict snowpack. We tested whether monitoring changes in wind‐induced tree sway is a viable technique for detecting snow interception and quantifying canopy snow water equivalent (SWE). Over a 6 year period in Colorado, we monitored hourly sway of two conifers, each instrumented with an accelerometer sampling at 12 Hz. We developed an approach to distinguish changes in sway frequency due to thermal effects on tree rigidity versus intercepted snow mass. Over 60% of days with canopy snow had a sway signal that could not be distinguished from thermal effects. However, larger changes in tree sway could not generally be attributed to thermal effects, and canopy snow was present 93%–95% of the time, as confirmed with classified PhenoCam imagery. Using sway tests, we converted changes in sway to canopy SWE, which were correlated with total snowstorm amounts from a nearby SNOTEL site (Spearman r = 0.72 to 0.80, p < 0.001). Greater canopy SWE was associated with storm temperatures between −7°C and 0°C and wind speeds less than 4 m s−1. Lower canopy SWE prevailed in storms with lower temperatures and higher wind speeds. Monitoring tree sway is a viable approach for quantifying canopy SWE, but challenges remain in converting changes in sway to mass and distinguishing thermal and snow mass effects on tree sway.

Important Airborne Lidar Metrics of Canopy Structure for Estimating Snow Interception

Forest canopies exert significant controls over the spatial distribution of snow cover. Canopy snow interception efficiency is controlled by intrinsic processes (e.g., canopy structure), extrinsic processes (e.g., meteorological conditions), and the interaction of intrinsic-extrinsic factors (i.e., air temperature and branch stiffness). In hydrological models, intrinsic processes governing snow interception are typically represented by two-dimensional metrics like the leaf area index (LAI). To improve snow interception estimates and their scalability, new approaches are needed for better characterizing the three-dimensional distribution of canopy elements. Airborne laser scanning (ALS) provides a potential means of achieving this, with recent research focused on using ALS-derived metrics that describe forest spacing to predict interception storage. A wide range of canopy structural metrics that describe individual trees can also be extracted from ALS, although relatively little is known about which of them, and in what combination, best describes intrinsic canopy properties known to affect snow interception. The overarching goal of this study was to identify important ALS-derived canopy structural metrics that could help to further improve our ability to characterize intrinsic factors affecting snow interception. Specifically, we sought to determine how much variance in canopy intercepted snow volume can be explained by ALS-derived crown metrics, and what suite of existing and novel crown metrics most strongly affects canopy intercepted snow volume. To achieve this, we first used terrestrial laser scanning (TLS) to quantify snow interception on 14 trees. We then used these snow interception measurements to fit a random forest model with ALS-derived crown metrics as predictors. Next, we bootstrapped 1000 calculations of variable importance (percent increase in mean squared error when a given explanatory variable is removed), keeping nine canopy metrics for the final model that exceeded a variable importance threshold of 0.2. ALS-derived canopy metrics describing intrinsic tree structure explained approximately two-thirds of the snow interception variability (R2 ≥ 0.65, RMSE ≤ 0.52 m3, relative RMSE ≤ 48%) in our study when extrinsic factors were kept as constant as possible. For comparison, a generalized linear mixed-effects model predicting snow interception volume from LAI alone had a marginal R2 = 0.01. The three most important predictor variables were canopy length, whole-tree volume, and unobstructed returns (a novel metric). These results suggest that a suite of intrinsic variables may be used to map interception potential across larger areas and provide an improvement to interception estimates based on LAI.

Characterizing Maritime Snow Canopy Interception in Forested Mountains

AbstractAir temperature (Tair) plays an important role in determining how a canopy intercepts snow and apart from event size is the single most important micrometeorological variable found to adequately influence interception rates and magnitude. We present results from a 6‐year study on snow‐forest interactions. This data set reveals the central role Tair plays in how a forest intercepts snow and the need to effectively incorporate this within snow process models. Warm temperature events show a higher canopy interception efficiency (CIE) for all sites across the study period, while colder Tair events demonstrated a lower corresponding CIE. Additionally, there is a structural component of the forest itself that plays a role in the ability of canopy to intercept snow. Recognizing the physical vertical structure of a forest as nontrivial, we present a simple canopy interception model that includes a novel three‐dimensional forest metric that captures canopy complexity, Gz, combined with event size and Tair to adequately predict event‐based interception. Low complexity forests decrease interception capacity from the outset, whereas a highly complex or diverse forest increases interception potential and leads to a nonlinear increase in temperature‐based canopy interception due to more surface area able to intercept falling snow. Essentially, forest structure sets the boundary condition of the potential to intercept, while event size and Tair determines the rate or amount of interception. We develop a simple canopy snow interception model from these data and compare modeled output against three commonly used interception models in both a maritime and continental snow climate. Partitioning the relative importance of snow‐forest interactions on canopy interception will help provide the information to accurately model snow‐forest interactions and also aid in our water resources predictive capabilities now and into the future.

Forest impacts on snow accumulation and ablation across an elevation gradient in a temperate montane environment

Abstract. Forest cover modifies snow accumulation and ablation rates via canopy interception and changes in sub-canopy energy balance processes. However, the ways in which snowpacks are affected by forest canopy processes vary depending on climatic, topographic and forest characteristics. Here we present results from a 4-year study of snow–forest interactions in the Oregon Cascades. We continuously monitored snow and meteorological variables at paired forested and open sites at three elevations representing the Low, Mid, and High seasonal snow zones in the study region. On a monthly to bi-weekly basis, we surveyed snow depth and snow water equivalent across 900 m transects connecting the forested and open pairs of sites. Our results show that relative to nearby open areas, the dense, relatively warm forests at Low and Mid sites impede snow accumulation via canopy snow interception and increase sub-canopy snowpack energy inputs via longwave radiation. Compared with the Forest sites, snowpacks are deeper and last longer in the Open site at the Low and Mid sites (4–26 and 11–33 days, respectively). However, we see the opposite relationship at the relatively colder High sites, with the Forest site maintaining snow longer into the spring by 15–29 days relative to the nearby Open site. Canopy interception efficiency (CIE) values at the Low and Mid Forest sites averaged 79 and 76 % of the total event snowfall, whereas CIE was 31 % at the lower density High Forest site. At all elevations, longwave radiation in forested environments appears to be the primary energy component due to the maritime climate and forest presence, accounting for 93, 92, and 47 % of total energy inputs to the snowpack at the Low, Mid, and High Forest sites, respectively. Higher wind speeds in the High Open site significantly increase turbulent energy exchanges and snow sublimation. Lower wind speeds in the High Forest site create preferential snowfall deposition. These results show the importance of understanding the effects of forest cover on sub-canopy snowpack evolution and highlight the need for improved forest cover model representation to accurately predict water resources in maritime forests.

Snow disappearance timing is dominated by forest effects on snow accumulation in warm winter climates of the Pacific Northwest, United States

AbstractForests modify snow processes and affect snow water storage as well as snow disappearance timing. However, forest influences on snow accumulation and ablation vary with climate and topography and are therefore subject to temporal and spatial variability. We utilize multiple years of snow observations from across the Pacific Northwest, United States, to assess forest–snow interactions in the relatively warm winter conditions characteristic of maritime and transitional maritime–continental climates. We (a) quantify the difference in snow magnitude and disappearance timing between forests and open areas and (b) assess how forest modifications of snow accumulation and ablation combine to determine whether snow disappears later in the forest or in the open.We find that snow disappearance timing at 12 (out of 14) sites ranges from synchronous in the forest and open to snow persisting up to 13 weeks longer in the open relative to a forested area. By analyzing accumulation and ablation rates up to the day when snow first disappears from the forest, we find that the difference between accumulation rates in the open and forest is larger than the difference between ablation rates. Thus, canopy snow interception and subsequent loss, rather than ablation, set up longer snow duration in the open. However, at two relatively windy sites (hourly average wind speeds up to 8 and 17 m/s), differential snow disappearance timing is reversed: Snow persists 2–5 weeks longer in the forest. At the windiest sites, accumulation rates in the forest and open are similar. Ablation rates are higher in the open, but the difference between ablation rates in the forest and open at these sites is approximately equivalent to the difference at less windy sites. Thus, longer snow retention in the forest at the windiest sites is controlled by depositional differences rather than by reduced ablation rates. These findings suggest that improved quantification of forest effects on snow accumulation processes is needed to accurately predict the effect of forest management or natural disturbance on snow water resources.

Investigations on physical properties and ablation processes of snow cover during the spring snowmelt period in the headwater region of the Irtysh River, Chinese Altai Mountains

To explore the effects of the underlying surface on snow properties and the “forest effects” on snow accumulation and ablation processes in the headwater area of the Irtysh River in the Chinese Altai Mountains, the physical properties of snow and certain snowmelt processes were investigated during the snowmelt period in 2014. Our observations showed that the diurnal and daily variations of air and snow temperatures, the liquid water contents (LWCs), and the densities of surface snow layers at 0–5 cm depths were in agreement, but differences in snow properties were obvious at the bottom snow layers. The LWCs were divided into three categories according to snow temperature (T s): LWC = 0, T s < −3 °C; LWC <1 %, −3 ≤ T s < −1 °C; LWC <7 %, T s ≥ −1 °C. The snow densities were greatest in the top layers above all underlying surfaces (grassland, concrete, and river ice) during the snowmelt period. The snowmelt experiment indicated that the mean air temperature was the highest on the grassland and lowest in the glade, but the diurnal temperature range was the lowest in the continuous forest and highest on the grassland. The canopy snow interception rate of Abies sibirica reached up to 70 % and the mean value of the continuous forest cover was about 30 %. The snowmelt duration periods were 20 days on the grassland, 35 days in the continuous forest, and 43 days in the forest glade, and the corresponding average snow melt rates (SMRs) were 2.1, 1.2, and 1.4 mm d−1. For one single A. sibirica tree, the SMR in the sub-canopy was only half that on the edge and outside of the forest canopy.

The impacts of mountain pine beetle disturbance on the energy balance of snow during the melt period

AbstractMountain snowpacks provide most of the annual discharge of western US rivers, but the future of water resources in the western USA is tenuous, as climatic changes have resulted in earlier spring melts that have exacerbated summer droughts. Compounding changes to the physical environment are biotic disturbances including that of the mountain pine beetle (MPB), which has decimated millions of acres of western North American forests. At the watershed scale, MPB disturbance increases the peak hydrograph, and at the stand scale, the ‘grey’ phase of MPB canopy disturbance decreases canopy snow interception, increases snow albedo, increases net shortwave radiation, and decreases net longwave radiation versus the ‘red’ phase. Fewer studies have been conducted on the red phase of MPB disturbance and in the mixed coniferous stands that may follow MPB‐damaged forests. We measured the energy balance of four snowpacks representing different stages of MPB damage, management, and recovery: a lodgepole pine stand, an MPB‐infested stand in the red phase, a mixed coniferous stand (representing one successional trajectory), and a clear‐cut (representing reactive management) in the Tenderfoot Creek Experimental Forest in Montana, USA. Net longwave radiation was lower in the MPB‐infested stand despite higher basal area and plant area index of the other forests, suggesting that the desiccated needles serve as a less effective thermal buffer against longwave radiative losses. Eddy covariance observations of sensible and latent heat flux indicate that they are of similar but opposite magnitude, on the order of 20 MJ m−2 during the melt period. Further analyses reveal that net turbulent energy fluxes were near zero because of the temperature and atmospheric vapour pressure encountered during the melt period. Future research should place snow science in the context of forest succession and management and address important uncertainties regarding the timing and magnitude of needlefall events. Copyright © 2015 John Wiley &amp; Sons, Ltd.

The influence of canopy snow parameterizations on snow albedo feedback in boreal forest regions

AbstractVariation in snow albedo feedback (SAF) among Coupled Model Intercomparison Project phase 5 climate models has been shown to explain much of the variation in projected 21st century warming over Northern Hemisphere land. Prior studies using observations and models have demonstrated both considerable spread in the albedo and a negative bias in the simulated strength of SAF, over snow‐covered boreal forests. Boreal evergreen needleleaf forests are capable of intercepting snowfall throughout the winter and consequently exert a significant impact on seasonal surface albedo. Two satellite data products and tower‐based observations of albedo are compared with simulations from multiple versions of the Community Climate System Model (CCSM4) to investigate the causes of weak simulated SAF over the boreal forest. The largest bias occurs in April and May, when simulated SAF is one half the strength of SAF in observations. This is traced to two features of the canopy snow parameterizations used in the land model. First, there is no mechanism for the dynamic removal of snow from the canopy when temperatures are below freezing, which results in albedo values in midwinter that are biased high. Second, when temperatures do rise above freezing, all snow on the canopy is melted instantaneously, which results in an unrealistically early transition from a snow‐covered to a snow‐free canopy. These processes combine to produce large differences between simulated and observed monthly albedo and are the source of the weak bias in SAF. This analysis highlights the importance of canopy snow parameterizations for simulating the hemispheric scale climate response to surface albedo perturbations.

スギ高齢人工林における冠雪害発生と林孔との関係

スギ高齢人工林における冠雪害発生と林孔との関係

Modelling crown snow loads in Finland: a comparison of two methods

The spatial occurrence of heavy crown snow loads in Finland between 1961 and 2010 is studied by using for the first time a model that classifies the snow load into four different types: rime, dry snow, wet snow and frozen snow. In producing this climatology, we used meteorological observations made at 29 locations across Finland. The model performance is evaluated against classified daily images of canopy snow cover and with the help of two short case studies. The results are further compared to those achieved with a simpler method used in previous studies. The heaviest crown snow loads are found to occur typically in eastern Finland. The new method reveals that this holds not only for the total snow loads but also for the different snow load types, although there are certain differences in their geographical occurrence. The greatest benefit achieved with the new method is the inclusion of rime accretion. The forests most prone to heavy riming are those located on tree-covered hills in northern Finland, but as the terrain elevation affects riming efficiency greatly, these small-scale variations in the snow load amounts could not be described in this study in great detail. Moreover, the results are more inaccurate in northern Finland where variations in the terrain elevation are greater than elsewhere. Otherwise, the largest uncertainties in this study are related to wind speed measurements and possibly partly because of that, we were not able to detect any significant trends in the crown snow-load amounts over the study period.

Representation of canopy snow interception, unloading and melt in a parsimonious snowmelt model

Recent improvements in the Utah Energy Balance (UEB) snowmelt model are focused on snow–vegetation–atmosphere interactions to understand how different types of vegetation affect snow processes in the mountains of Western USA. This work presents field work carried out in the Rocky Mountains of Northern Utah to evaluate new UEB model algorithms that represent the processes of canopy snow interception, sublimation, mass unloading and melt. Four years' continuous field observations showed generally smaller accumulations of snow beneath the forest canopies in comparison with open (sage and grass) areas, a difference that is attributed to interception and subsequent sublimation and redistribution of intercepted snow by wind, much of it into surrounding open areas. Accumulations beneath the denser forest (conifer) canopies were found to be less than the accumulation beneath the less dense forest (deciduous) canopies. The model was able to represent the accumulation of snow water equivalent in the open and beneath the deciduous forest quite well but without accounting for redistribution tended to overestimate the snow water equivalent beneath the conifer forest. Evidence of redistribution of the intercepted snow from the dense forest (i.e. conifer forest) to the adjacent area was inferred from observations. Including a simple representation of redistribution in the model gave satisfactory prediction of snow water equivalent beneath the coniferous forest. The simulated values of interception, sublimation and unloading were also compared with previous studies and found in agreement. Copyright © 2013 John Wiley & Sons, Ltd.

Development and testing of a snow interceptometer to quantify canopy water storage and interception processes in the rain/snow transition zone of the North Cascades, Washington, USA

[1] Tree canopy snow interception is a significant hydrological process, capable of removing up to 60% of snow from the ground snowpack. Our understanding of canopy interception has been limited by our ability to measure whole canopy water storage in an undisturbed forest setting. This study presents a relatively inexpensive technique for directly measuring snow canopy water storage using an interceptometer, adapted from Friesen et al. (2008). The interceptometer is composed of four linear motion position sensors distributed evenly around the tree trunk. We incorporate a trunk laser-mapping installation method for precise sensor placement to reduce signal error due to sensor misalignment. Through calibration techniques, the amount of canopy snow required to produce the measured displacements can be calculated. We demonstrate instrument performance on a western hemlock (Tsuga heterophylla) for a snow interception event in November 2011. We find a snow capture efficiency of 83 ± 15% of accumulated ground snowfall with a maximum storage capacity of 50 ± 8 mm snow water equivalent (SWE). The observed interception event is compared to simulated interception, represented by the variable infiltration capacity (VIC) hydrologic model. The model generally underreported interception magnitude by 33% using a leaf area index (LAI) of 5 and 16% using an LAI of 10. The interceptometer captured intrastorm accumulation and melt rates up to 3 and 0.75 mm SWE h−1, respectively, which the model failed to represent. While further implementation and validation is necessary, our preliminary results indicate that forest interception magnitude may be underestimated in maritime areas.

The impact of beetle-induced conifer death on stand-scale canopy snow interception

Bark beetles have killed more than 100,000 km2 of pine forest in western North America, causing trees to lose the majority of their canopy material and potentially leading to enhanced subcanopy snow accumulation. Over a 45-day period, we tested this hypothesis by measuring daily snow accumulation in three living and two dead lodgepole pine stands and in three adjacent clearings. The largest clearing was selected as our reference clearing based on previous studies. At maximum pre-melt snow water equivalent (SWE), this clearing had accumulated 50.4-cm SWE, while 45.6-cm SWE accumulated under dead stands and 38.1-cm SWE accumulated under living stands. Dead stand snowpacks were both denser and deeper than those in living stands. We attribute higher subcanopy accumulation under dead stands, compared to living stands, to diminished canopy snow interception and sublimation. Storm-scale canopy interception was also estimated by comparing SWE in forests and clearings before and after storm events. Over 10 storms, dead and living stands intercepted 18 and 41% of snowfall, respectively. The amount of interception increased linearly with storm size in the living stands, but not dead stands. We estimate more than half of snow falling on living stands sublimated, with measurably less sublimation in dead stands.

Seasonal variation in boreal pine forest albedo and effects of canopy snow on forest reflectance

The low shortwave albedo of evergreen coniferous forests increases net radiation and thus the local temperature as compared to open areas. The difference between albedos of evergreen forests and open areas is most pronounced in winter and spring, when the forest canopies mask the reflective ground snow. However, also the albedo of coniferous evergreen forests changes as a function of the amount and optical properties of snow in the ground and canopy. In this study, we examined the shortwave radiation balance of a boreal Scots pine dominated forest. Canopy snow cover was observed to substantially influence the albedo, increasing it by about 0.2 as compared to snow free conditions. However, albedo varied greatly between and within the canopy snow classes, probably due to differences in illumination conditions and snow amount and properties. During midwinter months, most of the incident solar radiation was reflected during days with a lot of snow in the canopy. The difference in reflected radiation between the winters with least and most snow was 54MJm−2, which was also close to the difference (55MJm−2) between the reflectance of an average winter and that of a simulated snow free winter, corresponding to less than 2% of the annual solar irradiance. The albedo of the forest was greatest in midwinter, when the cold weather and low solar radiation caused the falling snow to remain on the tree branches. As the incident solar radiation in these months is very low, we concluded that the positive feedback to climate warming in case of a potentially decreased snow cover in this boreal pine forest would remain small.

Simulation of forest snow processes at Fraser with a energy balance based snow melt model (WEB-DHM-S)

A newly developed physically based distributed biosphere hydrological model with three layered energy balance snow melt module (WEB-DHM-S) has been implemented at point scale to evaluate the forest snow processes at Fraser Experiment Forest site (USA) for two snow seasons (2003-2005). Results illustrate that the model is capable of representing the sub-canopy snow depth and snow water equivalent well with average correlation coefficient of 0.9. Energy fluxes are analyzed in detail for above canopy and below canopy snow processes. It can be concluded that the radiation energy is dominant in above canopy where sensible heat flux is dominant in addition to the radiation energy in sub-canopy snow processes. Furthermore, the sensitivity runs against the interception capacity shows that the interception capacity plays a major role in canopy snow sublimation.

Modeling Snow–Canopy Processes on an Idealized Mountain

Abstract Snow interception in a coniferous forest canopy is an important hydrological feature, producing complex mass and energy exchanges with the surrounding atmosphere and the snowpack below. Subcanopy snowpack accumulation and ablation depends on the effects of canopy architecture on meteorological conditions and on interception storage by stems, branches, and needles. Mountain forests are primarily composed of evergreen conifer species that retain their needles throughout the year and hence intercept snow efficiently during winter. Canopy-intercepted snow can melt, fall to the ground, and/or sublimate into the air masses above and within the canopy. To improve the understanding of snow–canopy interception processes and the associated influences on the snowpack below, a series of model experiments using a detailed, physically based snow–canopy and snowpack evolution model [Alpine Multiscale Numerical Distributed Simulation Engine (AMUNDSEN)] driven with observed meteorological forcing was conducted. A cone-shaped idealized mountain covered with a geometrically regular pattern of coniferous forest stands and clearings was constructed. The model was applied for three winter seasons with different snowfall intensities and distributions. Results show the effects of snow–canopy processes and interactions on the pattern of ground snow cover, its duration, and the amount of meltwater release, in addition to showing under what conditions the protective effect of a forest canopy overbalances the reduced accumulation of snow on the ground. The simulations show considerable amounts of canopy-intercepted snowfall can sublimate, leading to reduced snow accumulation beneath the forest canopy. In addition, the canopy produces a shadowing effect beneath the trees that leads to reduced radiative energy reaching the ground, reduced below-canopy snowmelt rates, and increased snow-cover duration relative to nonforested areas. During snow-rich winters, the shadowing effect of the canopy dominates and snow lasts longer inside the forest than in the open, but during winters with little snow, snow sublimation losses dominate and snow lasts longer in the open areas than inside the forest. Because of the strong solar radiation influence on snowmelt rates, the details of these relationships vary for northern and southern radiation exposures and time of year. In early and high winter, the radiation protection effect of shadowing by the canopy is small. If little snow is available, an intermittent melt out of the snow cover inside the forest can occur. In late winter and spring, the shadowing effect becomes more efficient and snowmelt is delayed relative to nonforested areas.

Impact of land-use changes on snow in a forested region with heavy snowfall in Hokkaido, Japan

We simulated snow processes in a forested region with heavy snowfall in Japan, and evaluated both the regional-scale snow distribution and the potential impact of land-use changes on the snow cover and water balances over the entire domain. SnowModel reproduced the snow processes at open and forested sites, which were confirmed by snow water equivalent (SWE) measurements at two intensive observation sites and snow depth measurements at the Automated Meteorological Data Acquisition System sites. SnowModel also reproduced the observed snow distribution (from the MODIS snow cover data) over the simulation domain during thaw. The observed SWE was less at the forested site than at the open site. The SnowModel simulations showed that this difference was caused mainly by differences in sublimation. The type of land use changed the maximum SWE, onset and duration of snowmelt, and the daily snowmelt rate due to canopy snow interception. Citation Suzuki, K., Kodama, Y., Nakai, T., Liston, G. E., Yamamoto, K., Ohata, T., Ishii, Y., Sumida, A., Hara, T. & Ohta, T. (2011) Impact of land-use changes in a forested region with heavy snowfall in Hokkaido, Japan. Hydrol. Sci. J. 56(3), 443–467.

Simulation of snow accumulation and melt in needleleaf forest environments

Abstract. Drawing upon numerous field studies and modelling exercises of snow processes, the Cold Regions Hydrological Model (CRHM) was developed to simulate the four season hydrological cycle in cold regions. CRHM includes modules describing radiative, turbulent and conductive energy exchanges to snow in open and forest environments, as well as account for losses from canopy snow sublimation and rain evaporation. Due to the physical-basis and rigorous testing of each module, there is a minimal need for model calibration. To evaluate CRHM, simulations of snow accumulation and melt were compared to observations collected at paired forest and clearing sites of varying latitude, elevation, forest cover density, and climate. Overall, results show that CRHM is capable of characterising the variation in snow accumulation between forest and clearing sites, achieving a model efficiency of 0.51 for simulations at individual sites. Simulations of canopy sublimation losses slightly overestimated observed losses from a weighed cut tree, having a model efficiency of 0.41 for daily losses. Good model performance was demonstrated in simulating energy fluxes to snow at the clearings, but results were degraded from this under forest cover due to errors in simulating sub-canopy net longwave radiation. However, expressed as cumulative energy to snow over the winter, simulated values were 96% and 98% of that observed at the forest and clearing sites, respectively. Overall, the good representation of the substantial variations in mass and energy between forest and clearing sites suggests that CRHM may be useful as an analytical or predictive tool for snow processes in needleleaf forest environments.

SNOWMIP2: An Evaluation of Forest Snow Process Simulations

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; 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 modeling groups. Participants in 11 countries contributed output from 33 models, and the results are published here for sites in Canada, the United States, and Switzerland. On average, the models perform fairly well in simulating snow accumulation and ablation, although there is a wide intermodal 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 temperature under snow, particularly for forest sites, and this would have large consequences for simulations of runoff and biological processes in the soil.