Temperature Measurements in an Air Layer Very Close to a Snow Surface

Nyberg, Alf

doi:10.1080/20014422.1938.11880662

Cited by 7 publications

(7 citation statements)

References 3 publications

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“…Radionov et al [1997] measured condensation rates at the snow surface as high as 1 mm month −1 . The condensation occurs at the snow surface because it is often colder than the air above it [ Nyberg , 1938]. If this process was occurring at SHEBA, it must have been subtle: We could not detect riming or hoar frost formation and the snow often looked pristine and new.…”

Section: Resultsmentioning

confidence: 99%

Winter snow cover on the sea ice of the Arctic Ocean at the Surface Heat Budget of the Arctic Ocean (SHEBA): Temporal evolution and spatial variability

2002

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[1] The evolution and spatial distribution of the snow cover on the sea ice of the Arctic Ocean was observed during the Surface Heat Budget of the Arctic Ocean (SHEBA) project. The snow cover built up in October and November, reached near maximum depth by midDecember, then remained relatively unchanged until snowmelt. Ten layers were deposited, the result of a similar number of weather events. Two basic types of snow were present: depth hoar and wind slab. The depth hoar, 37% of the pack, was produced by the extreme temperature gradients imposed on the snow. The wind slabs, 42% of the snowpack, were the result of two storms in which there was simultaneous snow and high winds (>10 m s À1 ). The slabs impacted virtually all bulk snow properties emphasizing the importance of episodic events in snowpack development. The mean snow depth (n = 21,169) was 33.7 cm with a bulk density of 0.34 g cm À3 (n = 357, r 2 of 0.987), giving an average snow water equivalent of 11.6 cm, 25% higher than the amount record by precipitation gauge. Both depth and stratigraphy varied significantly with ice type, the greatest depth, and the greatest variability in depth occurring on deformed ice (ridges and rubble fields). Across all ice types a persistent structural length in depth variations of $20 m was found. This appears to be the result of drift features at the snow surface interacting with small-scale ice surface structures. A number of simple ways of representing the complex temporal and spatial variations of the snow cover in ice-ocean-atmosphere models are suggested.

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Section: Resultsmentioning

confidence: 99%

Winter snow cover on the sea ice of the Arctic Ocean at the Surface Heat Budget of the Arctic Ocean (SHEBA): Temporal evolution and spatial variability

2002

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“…A more puzzling result was that the snow layers than gained mass (+ in Fig.14) were not always near the surface of the snow. Stable-isotope data indicate an accumulation of vapor in the upper layers of snow (Fig.12), and these layers are preferential sites for condensation of water vapor because they are colder than the snow lower in the pack (Nyberg, 1938). Condensation of vapor from the air results in the development of surface hoar (Lang and others, 1985: Colbeck.…”

Section: Discussionmentioning

confidence: 99%

Vapor transport, grain growth and depth-hoar development in the subarctic snow

1997

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ABSTRACT. M easurements from the sub arctic snowpack are used to explore the relation ship hctween grain growth and vapor flow, th e fundamental processes of dry-snow m eta m or phi sm. Du e to extreme temperature grad ients, the suba rctic pack undergoes extensive deplh-hoa r m etamorphi sm. By the end of the winter a fi ve-l ayered stru ctu re with a pronounced weak laye r near th e base of the snow evolves. Grain-size increases by a factor of 2-3, wh i le t he number of g ra i ns per unil mass d ecreases by a fac tor of 10. Obse rved growth rates require significant net inter-particle vapor fluxes. Stable-isoto pe ratios show that there are a lso significa nt net layer-to -I aye r vapor flu xes. Soil moi sture enters the base of th e p ack and mixes wit h the bottom 10 cm of snow, while iso topieally light water vapor fractionates from the basal layer a nd is d eposiled up to 50 cm high er in the p ack. End-of-winter density profi les for snow on the gro und, eomf,ared with snow on tabl es, indi cate th e ne t layer-to-laye r vapor flu x averages 6 x 10 kg m -2 S-I, th ough detail ed measurements show the net flu x is episod ic a nd varies with time and height in the pack, with peak net fl uxes ten tim es higher th a n average. A model, driven by observed temperatu re profiles, reproduces th e layer-lo-layer flu x pattern a nd predicts the observed weak layer at the base of the snow. Calcu lated layer-to-Iaye r vapor fluxes a re ten times higher than inter-particle flu xes, which implies that depth-hoar g rain g rowt h is limited by factors other than the vapor supply. This finding suggesls that gain and loss of water molecules due to sublimation from g rains ta kes place at a rate m a ny times hi gher than th e rate at which gr ains grow, a nd it expl ains why g rain s can meta morphose into different form s so r eadily.

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“…Both direct and indirect data suggest this is reasonable. In his careful and pioneering study, Nyberg (1938) found that on cloudy days, or clear days when the wind speed was > 1.75 m s− 1 , <0.4°C difference existed between air and snow surface temperatures. Guest and Davidson (1994), working on Arctic sea ice, also found that surface inversions were relatively infrequent and, even when present, produced differences in air and surface temperatures that did not exceed 2°C.…”

Section: Location Instruments and Methodsmentioning

confidence: 99%

Spatial variations in the winter heat flux at SHEBA: estimates from snow-ice interface temperatures

2001

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The temperature of the snow-ice interface was measured every 2.4 h throughout winter 1997/98 at 30 locations near the Surface Heat Budget of the Arctic Ocean (SHEBA) camp in the Beaufort Sea. Measurements were obtained from young ice, ridges, refrozen melt ponds and ice hummocks. Average snow depths at these locations were 567 cm, while mean interface temperatures ranged from −8° to −25°C, with minimums varying from −12° to −39°C. Interface temperatures were linearly related to snow depth, with increasing scatter at greater depths. The conductive heat flux during the winter, Fc, was estimated for each location using air and interface temperatures, snow depths and measured snow thermal conductivities. Fc was integrated to determine total heat loss for the winter at each site. Losses varied by a factor of four, with variations over short distances (10 m) as large as the variations between ice floes. Spot measurements along traverse lines confirm that large variations in interface temperature are common, and imply that small-scale spatial variability in the conductive flux is widespread. A comparison of the dependence of Fc on snow depth and ice thickness based on our observations with the dependence predicted by a one-dimensional theoretical model suggests that spatial heterogeneity may be an important issue to consider when estimating the heat flux over large aggregate areas. We suggest that the small-scale variability in the conductive flux arises because the combined snow and ice geometry can produce significant horizontal conduction of heat.

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Temperature Measurements in an Air Layer Very Close to a Snow Surface

Cited by 7 publications

References 3 publications

Winter snow cover on the sea ice of the Arctic Ocean at the Surface Heat Budget of the Arctic Ocean (SHEBA): Temporal evolution and spatial variability

Winter snow cover on the sea ice of the Arctic Ocean at the Surface Heat Budget of the Arctic Ocean (SHEBA): Temporal evolution and spatial variability

Vapor transport, grain growth and depth-hoar development in the subarctic snow

Spatial variations in the winter heat flux at SHEBA: estimates from snow-ice interface temperatures

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