Snow Disappearance Research Articles

An estimated cost of lost climate regulation services caused by thawing of the Arctic cryosphere

Recent and expected changes in Arctic sea ice cover, snow cover, and methane emissions from permafrost thaw are likely to result in large positive feedbacks to climate warming. There is little recognition of the significant loss in economic value that the disappearance of Arctic sea ice, snow, and permafrost will impose on humans. Here, we examine how sea ice and snow cover, as well as methane emissions due to changes in permafrost, may potentially change in the future, to year 2100, and how these changes may feed back to influence the climate. Between 2010 and 2100, the annual costs from the extra warming due to a decline in albedo related to losses of sea ice and snow, plus each year's methane emissions, cumulate to a present value cost to society ranging from US$7.5 trillion to US$91.3 trillion. The estimated range reflects uncertainty associated with (1) the extent of warming-driven positive climate feedbacks from the thawing cryosphere and (2) the expected economic damages per metric ton of CO2 equivalents that will be imposed by added warming, which depend, especially, on the choice of discount rate. The economic uncertainty is much larger than the uncertainty in possible future feedback effects. Nonetheless, the frozen Arctic provides immense services to all nations by cooling the earth's temperature: the cryosphere is an air conditioner for the planet. As the Arctic thaws, this critical, climate-stabilizing ecosystem service is being lost. This paper provides a first attempt to monetize the cost of some of those lost services.

Spatial heterogeneity in ecologically important climate variables at coarse and fine scales in a high-snow mountain landscape.

Climate plays an important role in determining the geographic ranges of species. With rapid climate change expected in the coming decades, ecologists have predicted that species ranges will shift large distances in elevation and latitude. However, most range shift assessments are based on coarse-scale climate models that ignore fine-scale heterogeneity and could fail to capture important range shift dynamics. Moreover, if climate varies dramatically over short distances, some populations of certain species may only need to migrate tens of meters between microhabitats to track their climate as opposed to hundreds of meters upward or hundreds of kilometers poleward. To address these issues, we measured climate variables that are likely important determinants of plant species distributions and abundances (snow disappearance date and soil temperature) at coarse and fine scales at Mount Rainier National Park in Washington State, USA. Coarse-scale differences across the landscape such as large changes in elevation had expected effects on climatic variables, with later snow disappearance dates and lower temperatures at higher elevations. However, locations separated by small distances (∼20 m), but differing by vegetation structure or topographic position, often experienced differences in snow disappearance date and soil temperature as great as locations separated by large distances (>1 km). Tree canopy gaps and topographic depressions experienced later snow disappearance dates than corresponding locations under intact canopy and on ridges. Additionally, locations under vegetation and on topographic ridges experienced lower maximum and higher minimum soil temperatures. The large differences in climate we observed over small distances will likely lead to complex range shift dynamics and could buffer species from the negative effects of climate change.

南アルプス南部，大聖寺平に分布する雪窪の形成過程

A snowpatch hollow is a landform that may reflect the timing of snow disappearance associated with Holocene climate fluctuations. Thus, the development of a snowpatch hollow provides information on geomorphic processes and landscape evolution on alpine slopes in the Holocene. In this study, first, we investigate micro-landforms and slope forming materials of snowpatch hollows located at the valley head of Okunishikochi-sawa, where the slopes were glaciated during MIS 4, around Daishojidaira (2699 m a.s.l.; 35°28.64′N, 138°09.40′E), near Mount Akaishi-dake, in the Southern Japanese Alps. Second, we monitor ground temperature at 1 cm depth and 20 cm depth in the snowpatch bare ground, and measure slow mass movements with a paint line drawn on the bare ground. The snowpatch hollows are divided into three landscape units based on slope profile, vegetation, and soil stratigraphy. Surface I unit is comparable to the margin of the snowpatch hollow. Pinus pumila communities occupy large parts of these slopes. The humic loam layer is generally thick, and directly covers the solifluction deposit, which is the surface material of the snowpatch hollow. The humic loam layer intercalates Kikai Akahoya tephra (K-Ah; 7300 cal BP) in the lower part. Surface II unit is located within surface I. The humic loam layer is less than 20 cm thick, and contains many clasts transported from nearby snowpatch bare ground. This layer does not intercalate K-Ah. Snowpatch plant communities are established on surface II. Surface III unit is comparable to the present-day snowpatch bare ground. Periglacial processes such as frost creep, needle ice creep, and gelifluction act on the slope surface. The presence of K-Ah below surface I indicates that the nivational process became less active by the early Holocene. These geomorphic changes would have been promoted by atmospheric warming after the Late Glacial age. Subsequently, surface II was formed mainly by solifluction and slope-wash erosion. A layer composed of granules and fine pebbles, which were transported from snow-free ground by niveo-fluvial processes, overlay most of surface II. Deposition of this layer started around 5600 cal BP, and continued until at least 1200 cal BP. Therefore, surface II is estimated to have formed from 5600 cal BP to 1200 cal BP. Frost creep, needle ice creep, and gelifluction have been partially active on the snowpatch bare ground of surface III, although the slope processes weakened in the Holocene.

Incorporation of satellite-derived snow-cover area in spatial snowmelt modeling for a large area: determination of a gridded degree-day factor

AbstractSpatial degree-day factors (DDFs) are required for spatial snowmelt modeling over large areas by the degree-day method. We propose a method to obtain DDFs by incorporating snow disappearance dates (SDDs), derived from 10 day composites of Satellite Pour l’Observation de la Terre (SPOT)/VEGETATION data, into the degree-day method. This approach allowed determination of DDFs for each gridpoint so as to better reflect regional characteristics than use of spatially constant DDFs obtained from point measurements. Simulations at six observation sites successfully accounted for variations in snow water equivalent (SWE), even at elevations different from the closest measurement site. These results suggest that incorporating satellite-derived SDDs into the degree-day method decreases spatial uncertainty compared with the use of spatially constant DDFs. Application of our method to Japanese cold regions revealed that gridded DDFs were negatively correlated with accumulated positive degree-days (APDDs) and were high only when APDDs were low. These results imply that high DDFs resulted from the dominant contribution of solar radiation to snowmelt at low temperatures and that low DDFs resulted from a relatively high contribution of sensible heat flux at high temperatures. The proposed method seems to adequately account for the main energetic components of snowmelt during the snow-cover season over large areas.

Role of snow and glacier melt in controlling river hydrology in Liddar watershed (western Himalaya) under current and future climate

Snowmelt and icemelt are believed to be important regulators of seasonal discharge of Himalayan rivers. To analyze the long term contribution of snowmelt and glacier/icemelt to river hydrology we apply a water budget model to simulate hydrology of the Liddar watershed in the western Himalaya, India for the 20th century (1901–2010) and future IPCC A1B climate change scenario. Long term (1901–2010) temperature and precipitation data in this region show a warming trend (0.08°C yr−1) and an increase in precipitation (0.28 mm yr−1), with a significant variability in seasonal trends. In particular, winter months have undergone the most warming, along with a decrease in precipitation rates; precipitation has increased throughout the spring. These trends have accelerated the melting and rapid disappearance of snow, causing a seasonal redistribution in the availability of water. Our model results show that about 60% of the annual runoff of the Liddar watershed is contributed from the snowmelt, while only 2% is contributed from glacier ice. The climate trend observed from the 1901 to 2010 time period and its impact on the availability of water will become significantly worse under the IPCC climate change scenarios. Our results suggest that there is a significant shift in the timing and quantity of water runoff in this region of the Himalayas due to snow distribution and melt. With greatly increased spring runoff and its reductions in summer potentially leading to reduced water availability for irrigation agriculture in summer.

Modelling the effects of the mountain pine beetle on snowmelt in a subalpine forest

ABSTRACTThe recent mountain pine beetle epidemic in the Colorado River Basin has resulted in widespread tree mortality in pine stands across the Colorado Plateau. Because of complex micro‐scale (i.e. tree well scale) interactions between vegetation and snow processes, one of the most significant issues resulting from this epidemic is the potential hydrologic impacts of the effects of changing forest structure. Using SNTHERM, we conducted a comparative modelling scenario analysis of the snowpack along a transect between two trees over the course of the snow ablation season (28 February–30 June) under four forest stand conditions to assess changes in snowpack characteristics because of loss of canopy biomass. We found that the red phase scenario (intermediate phase of tree death) exhibited a 4‐day earlier snow disappearance date than the living stand scenario and grey phase scenario (advanced phase of tree death), although the timing of isothermal conditions at 0 °C was identical. The modelled clearcut scenario snowpack became isothermal at 0 °C 10 days earlier than the living, red phase, or grey phase scenarios. The clearcut modelling scenario also exhibited the greatest homogenization of snow properties, and the spatio‐temporal distribution of snow disappearance at the tree well scale was 70% as variable as the living, red phase and grey phase modelling scenarios. These results provide insight to the processes responsible for changing hydrologic dynamics in snow‐dominated forest ecosystems with the onset of vegetation stress and death and may help inform future forest management strategies.Copyright © 2012 John Wiley & Sons, Ltd.

Interactions between Seasonal Snow Cover, Ground Surface Temperature and Topography (Andes of Santiago, Chile, 33.5°S)

ABSTRACTThe spatial variables which affect the surface thermal regime are explored in a valley in a high‐altitude catchment of the Andes of Santiago. Two one‐year (2009–10 and 2010–11) ground surface temperature (GST) time series are analysed separately and linear mixed‐effects models are used to quantify the effects of site characteristics on mean GST (MGST) and ground surface thermal regimes. The effect of snow cover onset and disappearance dates on MGST is further examined in a sensitivity analysis. Elevation has the strongest effect on MGST (1°C/100 m), 30 additional days of snow cover suppress MGST by an estimated 0.1 to 0.6°C and openwork boulder surfaces are cooler by an estimated 0.6 to 0.8°C. The sensitivity analysis corroborates the effect of late snow cover in the linear models, which can overwhelm the spatial differences in radiative effects. A positive MGST found on active rock glaciers would suggest negative thermal offsets probably related to the presence of coarse blocky material at the surface, and which may also be present outside rock glaciers. We suggest that spatial patterns of MGST can serve as a proxy for spatial patterns in the lower limit of permafrost occurrence. Copyright © 2012 John Wiley & Sons, Ltd.

Improved snowmelt simulations with a canopy model forced with photo‐derived direct beam canopy transmissivity

The predictive capacity of a physically based snow model to simulate point‐scale, subcanopy snowmelt dynamics is evaluated in a mixed conifer forest, southern Sierra Nevada, California. Three model scenarios each providing varying levels of canopy structure detail were tested. Simulations of three water years initialized at locations of 24 ultrasonic snow depth sensors were evaluated against observations of snow water equivalent (SWE), snow disappearance date, and volumetric soil water content. When canopy model parameters canopy openness and effective leaf area index were obtained from satellite and literature‐based sources, respectively, the model was unable to resolve the variable subcanopy snowmelt dynamics. When canopy parameters were obtained from hemispherical photos, the improvements were not statistically significant. However, when the model was modified to accept photo‐derived time‐varying direct beam canopy transmissivity, the error in the snow disappearance date was reduced by as much as one week and positive and negative biases in melt‐season SWE and snow cover duration were significantly reduced. Errors in the timing of soil meltwater fluxes were reduced by 11 days on average. The optimum aggregated temporal model resolution of direct beam canopy transmissivity was determined to be 30 min; hourly averages performed no better than the bulk canopy scenarios and finer time steps did not increase overall model accuracy. The improvements illustrate the important contribution of direct shortwave radiation to subcanopy snowmelt and confirm the known nonlinear melt behavior of snow cover.

Spatial snowfall distribution in mountainous areas estimated with a snow model and satellite remote sensing

We describe an approach for reconstructing snowfall that combines satellite observations of the snow disappearance date (SDD) with a snow model for two mountainous areas in Japan having distinct snow climatology. This approach allows assessment of the distribution of snow and topographical effects on snowfall within a catchment. We also evaluated how the reconstructed snowfall affects the catchment snow hydrology. Validation at observation sites demonstrated that a combination of the snow model and snowfall reconstructions successfully estimated the seasonal changes of snow water equivalent (SWE). In Japan, the dependence of snowfall on elevation is stronger in mountainous areas along the coast on the Sea of Japan side of Japan’s central mountain spine (where snowfall triples with every 1000 m increase in elevation; Csf = 0.002 m−1) compared with inland locations of the same region (where snowfall doubles with every 1000 m increase; Csf = 0.001 m−1). Moreover, the reconstructed snowfall improved the estimation of maximum catchment SWE. Maximum total SWE, estimated with reconstructed snowfall, was 3.8 × 108 m3 in Kurobe catchment (along the coast on the Sea of Japan side of Japan’s central mountain spine), while that, estimated by convectional method with the spatially-constant Csf = 0.001 m−1, was 2.0 × 108 m3. As a result, estimations of the snow disappearance date and of the catchment snowmelt were also improved. These results suggest that it is useful to estimate the spatial snow distribution, especially where steep topography causes large gradients of snowfall amount with respect to elevation.

Comparing and combining SWE estimates from the SNOW‐17 model using PRISM and SWE reconstruction

Snow models such as SNOW‐17 may estimate past snow water equivalent (SWE) using either a forward configuration based on spatial extrapolation of measured precipitation, such as with the parameter‐elevation regressions on independent slopes model (PRISM), or a reconstruction configuration based on snow disappearance timing and back‐calculated snowmelt. However, little guidance exists as to which configuration is preferable. Because the two approaches theoretically have opposite sensitivities to model forcing, combining (averaging) their SWE estimates may be advantageous. Using 154 snow pillow sites located in maritime mountains of the western United States, we compared forward, reconstruction, and combined configurations of a simplified SNOW‐17. We evaluated model errors in annual precipitation, peak SWE, and SWE errors during the accumulation and ablation seasons. We also conducted a separate analysis to assess the sensitivity of peak SWE to biased forcing data and model parameters. The forward model had the greatest precipitation accuracy, while the combined model had the greatest accuracy in peak SWE and SWE during the accumulation and ablation seasons. In determining peak SWE, the forward and reconstruction models demonstrated opposite sensitivities to errors in air temperature and model parameters, and the combined model minimized errors due to temperature bias and parameter uncertainty. In basins with precipitation gages, we recommend PRISM for precipitation estimation and the combined model for SWE estimation. In areas with high precipitation uncertainty, reconstruction is more viable. Accurate model parameters dramatically improved reconstruction, so more work is needed to advance parameter estimation techniques in complex terrain.

Tree species distribution on mafic and felsic fells in Finnish Lapland

Physical–chemical properties of glacial tills, derived from felsic or mafic lithologies, were studied in the forest, treeline, and on tundra in western Finnish Lapland. Scots pine [Pinus sylvestris L.] dominated on felsic fells, but excess soil water content was found edaphically constraining for pine. Low soil electrical conductivity (ECa) and low Ca to Al ratios was found to constrain Norway spruce [Picea abies (L.) Karst.]. The soil ECa positively correlated with soil Mg, Na, and Ca, but negatively with Al signifying the distribution of spruce to be associated with mafic lithologies. The limit of mountain birch [Betula pubescens ssp. Czerepanovi Hämet-Ahti] was below the conifer krummholz-zone. In winter, the treeline soil was unfrozen beneath the snowpack, whereas subzero temperatures applied to forest and tundra. In spring, soil water became available weeks before final melting of snowpack, while soil temperature (ST) increased notably above 0oC three weeks after the disappearance of snow. Early season ST was not attributed to elevation or aspect. Mid-season ST was highest on tundra. We contend that, instead of ST, water or N availability, winter winds, and spatial distribution of snow are crucial with regard to spreading of tree species on the studied fells.

Improving the treatment of the vertical snow burial fraction over short vegetation in the NCAR CLM3

One deficiency of the NCAR Community Land Model (CLM3) is the disappearance of the simulated snow even in the middle of winter over a boreal grassland site due to unrealistically modeled high downward turbulent fluxes. This is caused by the inappropriate treatment of the vertical snow burial fraction for short vegetation. A new snow burial fraction formulation for short vegetation is then proposed and validated using in situ observations. This modification in the CLM3 largely removes the unrealistic surface turbulent fluxes, leading to a more reasonable snowmelt process, and improves the snow water equivalent (SWE) simulation. Moreover, global offline simulations show that the proposed formulation decreases sensible and latent heat fluxes as well as the ground temperature during the snowmelt season over short vegetation dominant regions. Correspondingly, the SWE is enhanced, leading to the increase in snowmelt-induced runoff during the same period. Furthermore, sensitivity tests indicate that these improvements are insensitive to the exact functional form or parameter values in the proposed formulation.

Significance of Snowpack for Root-zone Water and Temperature Cycles in Subarctic Lapland

Snowmelt timing is a critical factor for tree growth in high latitudes, but threshold conditions with respect to soil moisture availability and soil temperature for the root-zone processes are not well known. We monitored snowpack thickness, air and soil temperature, and water content in the soil, sapwood, and roots of downy birch (Betula pubescens Roth.) in Finnish Lapland through 1999–2003. An extreme cold event in January 1999 (TAIR = −49°C) resulted in soil freezing (at 10-cm depth) down to T10 = −26°C at a snow-free site, but beneath the 50-cm-thick snowpack the soil temperature was T10 = −0.5°C. Snowmelt water was able to infiltrate partially frozen soil sequences, such that an increase in water content of the soil and birch roots occurred two to six weeks before soil temperatures rose notably above 0°C. The soil T10 reached +0°C a week after the disappearance of snow. The increase in water content of birch trunks was coincidental with the air temperature rises notably above 0°C. The systematic interseasonal pattern of water content in the birch root-trunk system, i.e. high peaks in late winter–early spring and fall, suggests sap flow in downy birch.

Distribution and development of under-ice phytoplankton in 90-m deep water column of Lake Päijänne (Finland) during spring convection

Distribution and development of phytoplankton were studied in the deep and large Lake Paijanne from mid-winter until the disappearance of ice. Diatoms were an important part of the phytoplankton assemblage and, with cryptophytes and chrysophytes, made up 50–80% of the phytoplankton biomass. In mid-winter, chlorophyll a and phytoplankton biomass were uniformly distributed over the whole water column down to a depth of 90 m. Thus, most of the phytoplankton was in virtual darkness and there was negligible growth. Only motile cryptophytes were concentrated in the layers below the ice and were rare in deep water. After the disappearance of snow, convection developed, but at first cryptophytes were able to resist mixing. When convection turned from penetrative to predominantly horizontal, all phytoplankton were generally uniformly distributed in the water column. In spite of the full under-ice overturn with low average availability of light, the phytoplankton biomass doubled in April. The growth of cryptophytes was higher than that of diatoms, suggesting that motile species gained an advantage by being able to maintain themselves in the upper, illuminated layers. The results show that knowledge of the basic physical framework is essential for interpretation of under-ice phytoplankton results.

Analyses of seasonal snow disappearance in an alpine valley from micro‐ to meso‐scale (Loetschental, Switzerland)

AbstractThe seasonal snow cover duration depends on climatic conditions, vegetation and topography. Conventional approaches of snow cover monitoring, based on point measurements or remote sensing techniques, are not suitable for meso‐scale spatial and temporal observations, or for analyses of the snow extent. However, these meso‐scale analyses are the basis for an understanding of ecological, hydrological and climatic systems in high mountains. Therefore, new approaches are required to monitor and to analyse the meso‐scale spatial snow cover distribution.In the presented study, we used 30 point measurement data and terrestrial images, which were taken by two digital cameras. The micro‐scale point measurements show the snow cover duration in several topographical positions. The terrestrial images monitor the variation of snow extent on a northwest and southeast‐facing slope. They provide a spatial resolution of 10 m, and due to bad weather conditions, a temporal resolution of 5 days. Both, the micro‐ as well as meso‐scale data enabled statistical analyses of the impact of topography on snow cover duration.The combination of terrestrial images and point measurements facilitated the verification of the representativeness of point measurements as well as their extrapolation capabilities. One important conclusion of the presented study is that snow cover duration can be explained just partly by topographical features. Copyright © 2008 John Wiley & Sons, Ltd.

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.

Spring snow melt timing and changes over Arctic lands

Spring snow cover over Arctic lands has, on average, melted approximately 4–7 days earlier since the late 1980s compared to the previous 20 years. The earlier disappearance of snow has been identified in non-mountainous regions at the 60° and 70°N parallels over Eurasia and North America using visible satellite observations of continental snow cover extent (SCE) mapped by the National Oceanic and Atmospheric Administration (NOAA). The change was greater in the farthest north continental locations. Northern Hemisphere SCE declined by almost 10% (May) to 20% (June) between the two intervals. At latitude 70°N, eight segments of longitude (each 10° in width) show significant (negative) trends. However, only two longitudinal segments at 60°N show significant trends, one positive and one negative. SCE changes coincide with increasing spring warmth and the earlier diminution of sea ice in the last several decades. However, while sea ice has continued to decrease during this recent interval, snowmelt dates in the Arctic changed in a step-like fashion during the mid to late 1980s and have remained much the same since that time.

Tempo-spatial characteristics of energy budget and evapotranspiration in the eastern Siberia

Spatio-temporal variations in the energy budget and evapotranspiration (ET) in eastern Siberia were examined for a period of 19 years, from 1986 to 2004, for the Lena and Kolyma watersheds, which are underlain by permafrost. The energy budget and ET were calculated with a land surface model [Yamazaki, T., Yabuki, H., Ishii, Y., Ohta, T., Ohata, T., 2004. Water and energy exchanges at forests and a grassland in eastern Siberia evaluated using a one-dimensional land surface model. J. Hydrometeol. 5, 504–515] that considered vegetation, snow, and soil processes. Station data were used to compile gridded time series of forcing data. The spatial distribution of the energy budget showed that the latent heat flux ( Q E) was a significant term in the surface energy budget in forested regions, while the sensible heat ( Q H) was significant in the tundra region. A similar result was also obtained for the seasonal variation; in the Kolyma watershed, for instance, Q H dominated the seasonal energy budget, even during the growing season. In the Lena watershed, 53% of precipitation ( P G) was lost through ET, which occurred during a very sharply pronounced growing season. Transpiration ( E T) was a major component of ET in the Lena watershed, while in the Kolyma watershed, evaporation from the forest floor ( E S) was dominant. This suggested clear relations between the energy budget and the difference in land surface and climate. In the Lena and Kolyma watersheds, a time series of P G exhibited strong annual variations with an increasing trend during 1986–2004. ET also exhibited an increasing trend in the two watersheds. However, the interannual variation was weaker than that of P G, reflecting the influence of extensive permafrost in the area. The ET components also showed an increasing trend. In contrast, E S decreased during 1986–2004, the trend of E S thus being inversely correlated to that of P G. Interestingly, annual ET also exhibited an inverse correlation with P G in the Lena and Kolyma watersheds, although this relationship was weak. In contrast, ET displayed a strong correlation with air temperature ( T a) and the timing of the disappearance of snow.

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

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 (r2 > 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 (r2 = 0.8, P < 0.001), but yielded lower correlation (r2 = 0.2, P < 0.001) in drought years. Soil moisture was significantly correlated (r2 = 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 (r2 = 0.7, P < 0.001), thereby demonstrating the importance of snow on some attributes of the alpine plant community.

A sensitivity study of factors influencing warm/thin permafrost in the Swiss Alps

AbstractAlpine permafrost distribution is controlled by a great number of climatic, topographic and soil-specific factors, including snow cover, which plays a major role. In this study, a one-dimensional finite-element numerical model was developed to analyze the influence of individual snow-specific and climatic factors on the ground thermal regime. The results indicate that the most important factor is snow depth. Snow depths below the threshold value of 0.6 m lack sufficient insulation to prevent low atmospheric temperatures from cooling the soil. The date of first winter snow insulation and variations in mean annual air temperature (MAAT) are also shown to be important. Delays in early-winter snow insulation and in summer snow disappearance are shown to be of approximately equal significance to the ground thermal conditions. Numerical modelling also indicates that the duration of effective thermal resistance of snow cover governs the slope of the linear dependency between MAAT and mean annual ground surface temperatures (MAGST). Consequently, the most direct effect of a long-term rise in air temperatures on ground temperatures is predicted under a thin snow cover with early snowmelt in spring and/or where a large change in the date of total snowmelt occurs, in response to atmospheric warming.