Articles | Volume 13, issue 4
The Cryosphere, 13, 1283–1296, 2019
The Cryosphere, 13, 1283–1296, 2019

Research article 18 Apr 2019

Research article | 18 Apr 2019

Estimating the snow depth, the snow–ice interface temperature, and the effective temperature of Arctic sea ice using Advanced Microwave Scanning Radiometer 2 and ice mass balance buoy data

Lise Kilic et al.

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Cited articles

Baordo, F. and Geer, A.: Microwave Surface Emissivity over sea-ice, EUMETSAF NWP SAF, Tech. Rep. NWPSAF_EC_VS_026, 1–30, 2015. a
Comiso, J.: Sea ice effective microwave emissivities from satellite passive microwave and infrared observations, J. Geophys. Res., 88, 7686–7704, 1983. a, b, c
Comiso, J., Cavalieri, D., and Markus, T.: Sea ice concentration, ice temperature, and snow depth using AMSR-E data, IEEE T. Geosci. Remote, 41, 243–252, 2003. a
Draper, N. R. and Smith, H.: Applied regression analysis, John Wiley & Sons, Inc., Hoboken, NJ, USA, 1998. a
Dybkjær, G., Tonboe, R., and Høyer, J. L.: Arctic surface temperatures from Metop AVHRR compared to in situ ocean and land data, Ocean Sci., 8, 959–970,, 2012. a
Short summary
In this study, we develop and present simple algorithms to derive the snow depth, the snow–ice interface temperature, and the effective temperature of Arctic sea ice. This is achieved using satellite observations collocated with buoy measurements. The errors of the retrieved parameters are estimated and compared with independent data. These parameters are useful for sea ice concentration mapping, understanding sea ice properties and variability, and for atmospheric sounding applications.