Metamorphism of Arctic marine snow during the melt season. Impact on albedo
The energy budget of Arctic sea ice is strongly affected by the snow cover. Intensive sampling of snow properties was conducted near Qikiqtarjuak in Baffin Bay on typical landfast sea ice during two melt seasons in 2015 and 2016. The sampling included stratigraphy, vertical profiles of snow specific...
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ftcopernicus:oai:publications.copernicus.org:tcd76602 2023-05-15T13:10:37+02:00 Metamorphism of Arctic marine snow during the melt season. Impact on albedo Verin, Gauthier Dominé, Florent Babin, Marcel Picard, Ghislain Arnaud, Laurent 2019-07-24 application/pdf https://doi.org/10.5194/tc-2019-113 https://tc.copernicus.org/preprints/tc-2019-113/ eng eng doi:10.5194/tc-2019-113 https://tc.copernicus.org/preprints/tc-2019-113/ eISSN: 1994-0424 Text 2019 ftcopernicus https://doi.org/10.5194/tc-2019-113 2020-07-20T16:22:44Z The energy budget of Arctic sea ice is strongly affected by the snow cover. Intensive sampling of snow properties was conducted near Qikiqtarjuak in Baffin Bay on typical landfast sea ice during two melt seasons in 2015 and 2016. The sampling included stratigraphy, vertical profiles of snow specific surface area (SSA), density and surface spectral albedo. Both seasons feature four main phases: I) dry snow cover, II) surface melting, III) ripe snowpack and IV) melt pond formation. Each of them was characterized by distinctive physical and optical properties. Highest SSA of 49.3 m 2 kg −1 was measured during phase I on surface windslab together with a high broadband albedo of 0.87. The next phase was marked by alternative episodes of surface melting which dramatically decreased the SSA below 3 m 2 kg −1 and episodes of snowfall reestablishing the pre-melt conditions. Albedo was highly time variable especially in the near-infrared with minimum values around 0.45 at 1000 nm. At some point, the melt progressed leading to a fully ripe snowpack composed of clustered rounded grains in phase III. Albedo began to decrease in the visible as snow thickness decreased but remained steady at longer wavelengths. Moreover, its spatial variability clearly appeared for the first time following snow depth heterogeneity. The impacts on albedo of both snow SSA and thickness were quantitatively investigated using a radiative transfer model. Comparisons between albedo measurements and simulations show that our data on snow physical properties are relevant for radiative transfer modeling. They also point out to the importance of the properties of the very surface snow layer for albedo computation, especially during phase II when several distinctive layers of snow superimposed following snowfalls, melt or diurnal cycles. Text albedo Arctic Baffin Bay Baffin Bay Baffin Sea ice Copernicus Publications: E-Journals Arctic Baffin Bay |
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Open Polar |
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Copernicus Publications: E-Journals |
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ftcopernicus |
language |
English |
description |
The energy budget of Arctic sea ice is strongly affected by the snow cover. Intensive sampling of snow properties was conducted near Qikiqtarjuak in Baffin Bay on typical landfast sea ice during two melt seasons in 2015 and 2016. The sampling included stratigraphy, vertical profiles of snow specific surface area (SSA), density and surface spectral albedo. Both seasons feature four main phases: I) dry snow cover, II) surface melting, III) ripe snowpack and IV) melt pond formation. Each of them was characterized by distinctive physical and optical properties. Highest SSA of 49.3 m 2 kg −1 was measured during phase I on surface windslab together with a high broadband albedo of 0.87. The next phase was marked by alternative episodes of surface melting which dramatically decreased the SSA below 3 m 2 kg −1 and episodes of snowfall reestablishing the pre-melt conditions. Albedo was highly time variable especially in the near-infrared with minimum values around 0.45 at 1000 nm. At some point, the melt progressed leading to a fully ripe snowpack composed of clustered rounded grains in phase III. Albedo began to decrease in the visible as snow thickness decreased but remained steady at longer wavelengths. Moreover, its spatial variability clearly appeared for the first time following snow depth heterogeneity. The impacts on albedo of both snow SSA and thickness were quantitatively investigated using a radiative transfer model. Comparisons between albedo measurements and simulations show that our data on snow physical properties are relevant for radiative transfer modeling. They also point out to the importance of the properties of the very surface snow layer for albedo computation, especially during phase II when several distinctive layers of snow superimposed following snowfalls, melt or diurnal cycles. |
format |
Text |
author |
Verin, Gauthier Dominé, Florent Babin, Marcel Picard, Ghislain Arnaud, Laurent |
spellingShingle |
Verin, Gauthier Dominé, Florent Babin, Marcel Picard, Ghislain Arnaud, Laurent Metamorphism of Arctic marine snow during the melt season. Impact on albedo |
author_facet |
Verin, Gauthier Dominé, Florent Babin, Marcel Picard, Ghislain Arnaud, Laurent |
author_sort |
Verin, Gauthier |
title |
Metamorphism of Arctic marine snow during the melt season. Impact on albedo |
title_short |
Metamorphism of Arctic marine snow during the melt season. Impact on albedo |
title_full |
Metamorphism of Arctic marine snow during the melt season. Impact on albedo |
title_fullStr |
Metamorphism of Arctic marine snow during the melt season. Impact on albedo |
title_full_unstemmed |
Metamorphism of Arctic marine snow during the melt season. Impact on albedo |
title_sort |
metamorphism of arctic marine snow during the melt season. impact on albedo |
publishDate |
2019 |
url |
https://doi.org/10.5194/tc-2019-113 https://tc.copernicus.org/preprints/tc-2019-113/ |
geographic |
Arctic Baffin Bay |
geographic_facet |
Arctic Baffin Bay |
genre |
albedo Arctic Baffin Bay Baffin Bay Baffin Sea ice |
genre_facet |
albedo Arctic Baffin Bay Baffin Bay Baffin Sea ice |
op_source |
eISSN: 1994-0424 |
op_relation |
doi:10.5194/tc-2019-113 https://tc.copernicus.org/preprints/tc-2019-113/ |
op_doi |
https://doi.org/10.5194/tc-2019-113 |
_version_ |
1766236396946718720 |