Articles | Volume 13, issue 3
https://doi.org/10.5194/tc-13-1005-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-13-1005-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
29 Mar 2019
Research article |
| 29 Mar 2019
In situ observed relationships between snow and ice surface skin temperatures and 2 m air temperatures in the Arctic
Pia Nielsen-Englyst
CORRESPONDING AUTHOR
Research & Development, Danish Meteorological Institute (DMI), 2100 Copenhagen Ø, Denmark
DTU Space Institute, Technical University of Denmark (DTU), 2800 Kongens Lyngby, Denmark
Jacob L. Høyer
Research & Development, Danish Meteorological Institute (DMI), 2100 Copenhagen Ø, Denmark
Kristine S. Madsen
Research & Development, Danish Meteorological Institute (DMI), 2100 Copenhagen Ø, Denmark
Rasmus Tonboe
Research & Development, Danish Meteorological Institute (DMI), 2100 Copenhagen Ø, Denmark
Gorm Dybkjær
Research & Development, Danish Meteorological Institute (DMI), 2100 Copenhagen Ø, Denmark
Emy Alerskans
Research & Development, Danish Meteorological Institute (DMI), 2100 Copenhagen Ø, Denmark
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Rasmus T. Tonboe, Steinar Eastwood, Thomas Lavergne, Atle M. Sørensen, Nicholas Rathmann, Gorm Dybkjær, Leif Toudal Pedersen, Jacob L. Høyer, and Stefan Kern
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The Cryosphere, 10, 2217–2239, https://doi.org/10.5194/tc-10-2217-2016, https://doi.org/10.5194/tc-10-2217-2016, 2016
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Sea ice, frozen seawater floating on polar oceans, is covered by meltwater puddles, so-called melt ponds, during summer. Methods used to compute Arctic sea-ice concentration (SIC) from microwave satellite data are influenced by melt ponds. We apply eight such methods to one microwave dataset and compare SIC with visible data. We conclude all methods fail to distinguish melt ponds from leads between ice floes; SIC biases are negative (positive) for ponded (non-ponded) sea ice and can exceed 20 %.
N. Ivanova, L. T. Pedersen, R. T. Tonboe, S. Kern, G. Heygster, T. Lavergne, A. Sørensen, R. Saldo, G. Dybkjær, L. Brucker, and M. Shokr
The Cryosphere, 9, 1797–1817, https://doi.org/10.5194/tc-9-1797-2015, https://doi.org/10.5194/tc-9-1797-2015, 2015
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Thirty sea ice algorithms are inter-compared and evaluated systematically over low and high sea ice concentrations, as well as in the presence of thin ice and melt ponds. A hybrid approach is suggested to retrieve sea ice concentration globally for climate monitoring purposes. This approach consists of a combination of two algorithms plus the implementation of a dynamic tie point and atmospheric correction of input brightness temperatures.
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Christopher Chambers, Ralf Greve, Bas Altena, and Pierre-Marie Lefeuvre
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Arctic sea ice and the Greenland Ice Sheet (GrIS) are melting later in the year due to a warming climate. Through analyses of weather station, climate model, and reanalysis data, physical links are evaluated between Baffin Bay open water duration and western GrIS melt conditions. We show that sub-Arctic air mass movement across this portion of the GrIS strongly influences late summer and autumn melt, while near-surface, off-ice winds inhibit westerly atmospheric heat transfer from Baffin Bay.
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Short summary
The paper facilitates the construction of a satellite-derived 2 m air temperature (T2m) product for Arctic snow/ice areas. The relationship between skin temperature (Tskin) and T2m is analysed using weather stations. The main factors influencing the relationship are seasonal variations, wind speed and clouds. A clear-sky bias is estimated to assess the effect of cloud-limited satellite observations. The results are valuable when validating satellite Tskin or estimating T2m from satellite Tskin.
The paper facilitates the construction of a satellite-derived 2 m air temperature (T2m) product...
