Abstract
Abstract. Mapping sea ice concentration (SIC) and understanding sea ice properties and variability is important, especially today with the recent Arctic sea ice decline. Moreover, accurate estimation of the sea ice effective temperature (Teff) at 50 GHz is needed for atmospheric sounding applications over sea ice and for noise reduction in SIC estimates. At low microwave frequencies, the sensitivity to the atmosphere is low, and it is possible to derive sea ice parameters due to the penetration of microwaves in the snow and ice layers. In this study, we propose simple algorithms to derive the snow depth, the snow–ice interface temperature (TSnow−Ice) and the Teff of Arctic sea ice from microwave brightness temperatures (TBs). This is achieved using the Round Robin Data Package of the ESA sea ice CCI project, which contains TBs from the Advanced Microwave Scanning Radiometer 2 (AMSR2) collocated with measurements from ice mass balance buoys (IMBs) and the NASA Operation Ice Bridge (OIB) airborne campaigns over the Arctic sea ice. The snow depth over sea ice is estimated with an error of 5.1 cm, using a multilinear regression with the TBs at 6, 18, and 36 V. The TSnow−Ice is retrieved using a linear regression as a function of the snow depth and the TBs at 10 or 6 V. The root mean square errors (RMSEs) obtained are 2.87 and 2.90 K respectively, with 10 and 6 V TBs. The Teff at microwave frequencies between 6 and 89 GHz is expressed as a function of TSnow−Ice using data from a thermodynamical model combined with the Microwave Emission Model of Layered Snowpacks. Teff is estimated from the TSnow−Ice with a RMSE of less than 1 K.
Highlights
In situ observations of the variables controlling the sea ice energy and momentum balance in polar regions are scarce
We derive simple algorithms to estimate sea ice parameters such as the snow depth, the TSnow−Ice, and the Teff of sea ice at microwave frequencies, from Advanced Microwave Scanning Radiometer 2 (AMSR2) channels. This is achieved using the European Space Agency (ESA) Round Robin Data Package (RRDP), which contains AMSR2 data collocated with ice mass balance buoys (IMBs) data and Operation Ice Bridge (OIB) campaign data
A root mean square errors (RMSEs) of 5.1 cm is obtained between the estimated and the IMB snow depths using an independent IMB test data set. This snow depth retrieval is applicable to first-year ice (FYI) and multi-year ice (MYI), with lower uncertainties for FYI than for MYI (3.9 cm compared to 7.2 cm)
Summary
In situ observations of the variables controlling the sea ice energy and momentum balance in polar regions are scarce. Sea ice is covered by snow, which can reach a mean thickness of up to ∼ 50 cm in the Arctic (Sato and Inoue, 2018). Snow on sea ice strongly affects the sea ice energy and radiation balance, with its high insulation of heat and reflectivity of solar radiation. Snow is a poor conductor of heat: it insulates the sea ice and reduces the winter ice growth (Fichefet and Maqueda, 1999). The high albedo of snow on sea ice compared to open-water albedo plays an important role in the sea ice albedo feedback mechanism and Arctic amplification (Hall, 2004). The high albedo of snow on sea ice compared to open-water albedo plays an important role in the sea ice albedo feedback mechanism and Arctic amplification (Hall, 2004). Sato and Inoue (2018) suggest that the recent
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