Structure, specific surface area and thermal conductivity of the snowpack around Barrow, Alaska

Dominé, Florent; Gallet, Jean‐Charles; Bock, Josué; Morin, Samuel

doi:10.1029/2011jd016647

Cited by 66 publications

(84 citation statements)

References 49 publications

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“…where h is the thickness of each layer and k eff is its thermal conductivity (Domine et al 2012). The heat flux F through the snow can then be expressed as…”

Section: Snow and Ice In The Arctic Tundramentioning

confidence: 99%

Effects of changing permafrost and snow conditions on tundra wildlife: critical places and times

et al. 2017

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The change of water phase around 0°C has considerable impacts on wildlife ecology because liquid and solid water strongly differ in their insulating capability, mechanical resistance, and light reflectance. Freeze and melt events thus have strong ecological relevance, particularly in the Arctic where snow and ice are omnipresent and their conditions are changing due to climate warming. We first review the mechanisms linking water phase transitions to wildlife ecology, with emphasis on seven key processes. These processes are illustrated with examples or detailed case studies, such as snowmelt and icing events affecting herbivore populations, thaw-induced collapse of structures used by wildlife for reproduction, and thermal erosion of ice wedges reducing waterfowl habitat. We infer that water phase transitions generate some critical places and critical times that play a disproportionate role in the ecology of tundra wildlife. We map these critical places and times to help structure future research on the effects of climate change on tundra wildlife in a context where changing permafrost and snow conditions might trigger abrupt ecological responses in the Arctic tundra.Key words: ice, permafrost, snow, tundra, wildlife.Résumé : Le changement de phase de l'eau autour de 0°C a des impacts considérables sur l'écologie de la faune parce que l'eau liquide et l'eau solide diffèrent fortement dans leur capacité d'isolation, leur résistance mécanique et leur réflectance à la lumière. Les évé-nements de gel et de dégel ont ainsi une grande pertinence écologique, particulièrement dans l'Arctique où la neige et la glace sont omniprésentes et leurs conditions changent en raison du réchauffement climatique. Nous passons d'abord en revue les mécanismes liant les transitions de phase de l'eau à l'écologie de la faune, l'accent étant mis sur sept processus clés. Ces processus sont illustrés par des exemples ou des études de cas détaillées, tels que des événements de fonte des neiges et de gel ayant un effet sur les populations herbivores, l'écroulement provoqué par le dégel des structures utilisées par la faune pour la reproduction et l'érosion thermique des fentes de glace réduisant l'habitat du gibier d'eau. Nous déduisons For personal use only. SYNTHESIS PAPERque ces transitions de phase de l'eau produisent quelques endroits critiques et temps critiques qui jouent un rôle disproportionné dans l'écologie de la faune de la toundra. Nous dressons la carte de ces endroits et temps critiques afin d'aider à structurer la recherche future sur les effets du changement climatique sur la faune de la toundra, dans un contexte où les conditions changeantes du pergélisol et de la neige pourraient déclencher des réponses écologiques brusques dans la toundra arctique.

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“…where h is the thickness of each layer and k eff is its thermal conductivity (Domine et al 2012). The heat flux F through the snow can then be expressed as…”

Section: Snow and Ice In The Arctic Tundramentioning

confidence: 99%

Effects of changing permafrost and snow conditions on tundra wildlife: critical places and times

et al. 2017

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“…First the warming of the boreal forest will limit depth hoar development and therefore reduce both above effects. Second, changes in the properties of tundra snowpacks (Domine et al, 2012) are more complex. The warming-induced growth of vegetation will change snow properties by sheltering snow from wind effects and limiting the formation of low-permeability Arctic wind slabs usually with a marked surface roughness due to their mode of formation (Gouttevin et al, 2012).…”

Section: Metamorphism Climate and Permeabilitymentioning

confidence: 99%

Seasonal evolution of snow permeability under equi-temperature and temperature-gradient conditions

et al. 2013

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Abstract. The permeability (K) of snow to air flow affects the transfer of energy, water vapor and chemical species between the snow and the atmosphere. Yet today little is known about the temporal evolution of snow permeability as a function of metamorphic regime. Furthermore, our ability to simulate snow permeability over the seasonal evolution of a snowpack has not been tested. Here we have measured the evolution of snow permeability in a subarctic snowpack subject to high temperature-gradient (TG) metamorphism. We have also measured the evolution of the same snowpack deposited over tables so that it evolved in the equi-temperature (ET) regime. Permeability varies in the range 31 × 10 −10 (ET regime) to 650 × 10 −10 m 2 (TG regime). Permeability increases over time in TG conditions and decreases under ET conditions. Using measurements of density ρ and of specific surface area (SSA), from which the equivalent sphere radius r is determined, we show that the equation linking SSA, density ρ and permeability, K = 3.0 r 2 e (−0.013ρ) (with K in m 2 , r in m and ρ in kg m −3 ) obtained in a previous study adequately predicts permeability values. The detailed snowpack model Crocus is used to simulate the physical properties of the TG and ET snowpacks. For the most part, all variables are well reproduced. Simulated permeabilities are up to a factor of two greater than measurements for depth hoar layers, which we attribute to snow microstructure and its aerodynamic properties. Finally, the large difference in permeabilities between ET and TG metamorphic regimes will impact atmosphere-snow energy and mass exchanges. These effects deserve consideration in predicting the effect of climate change on snow properties and snow-atmosphere interactions.

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“…Indeed, the overall ice-air interface area generally decreases during snow metamorphism, leading to a SSA decrease over time. The measured SSA values vary from 224 m 2 kg −1 for diamond dust crystals (Domine et al, 2012) to less than 2 m 2 kg −1 for melt-freeze crusts (Domine et al, 2007b). This variable can easily be measured in the field using DUFISSS (DUal Frequency Integrating Sphere for Snow SSA measurement, Gallet et al, 2009), a device allowing the rapid retrieval of snow specific surface area from infrared reflectance measurements at 1310 nm.…”

Section: Introductionmentioning

confidence: 99%

Snow spectral albedo at Summit, Greenland: measurements and numerical simulations based on physical and chemical properties of the snowpack

et al. 2013

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Abstract. The broadband albedo of surface snow is determined both by the near-surface profile of the physical and chemical properties of the snowpack and by the spectral and angular characteristics of the incident solar radiation. Simultaneous measurements of the physical and chemical properties of snow were carried out at Summit Camp, Greenland (72 • 36 N, 38 • 25 W, 3210 m a.s.l.) in May and June 2011, along with spectral albedo measurements. One of the main objectives of the field campaign was to test our ability to predict snow spectral albedo by comparing the measured albedo to the albedo calculated with a radiative transfer model, using measured snow physical and chemical properties. To achieve this goal, we made daily measurements of the snow spectral albedo in the range 350-2200 nm and recorded snow stratigraphic information down to roughly 80 cm. The snow specific surface area (SSA) was measured using the DUFISSS instrument (DUal Frequency Integrating Sphere for Snow SSA measurement, Gallet et al., 2009). Samples were also collected for chemical analyses including black carbon (BC) and dust, to evaluate the impact of light absorbing particulate matter in snow. This is one of the most comprehensive albedo-related data sets combining chemical analysis, snow physical properties and spectral albedo measurements obtained in a polar environment. The surface albedo was calculated from density, SSA, BC and dust profiles using the DISORT model (DIScrete Ordinate Radiative Transfer, Stamnes et al., 1988) and compared to the measured values. Results indicate that the energy absorbed by the snowpack through the whole spectrum considered can be inferred within 1.10 %. This accuracy is only slightly better than that which can be obtained considering pure snow, meaning that the impact of impurities on the snow albedo is small at Summit. In the near infrared, minor deviations in albedo up to 0.014 can be due to the accuracy of radiation and SSA measurements and to the surface roughness, whereas deviations up to 0.05 can be explained by the spatial heterogeneity of the snowpack at small scales, the assumption of spherical snow grains made for DISORT simulations and the vertical resolution of measurements of surface layer physical properties. At 1430 and around 1800 nm the discrepancies are larger and independent of the snow properties; we propose that they are due to errors in the ice refractive index at these wavelengths. This work contributes to the development of physically based albedo schemes in detailed snowpack models, and to the improvement of retrieval algorithms for estimating snow properties from remote sensing data.

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Structure, specific surface area and thermal conductivity of the snowpack around Barrow, Alaska

Cited by 66 publications

References 49 publications

Effects of changing permafrost and snow conditions on tundra wildlife: critical places and times

Effects of changing permafrost and snow conditions on tundra wildlife: critical places and times

Seasonal evolution of snow permeability under equi-temperature and temperature-gradient conditions

Snow spectral albedo at Summit, Greenland: measurements and numerical simulations based on physical and chemical properties of the snowpack

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