The Cryosphere
The Cryosphere
TC
Articles | Volume 16, issue 12
Articles | Volume 16, issue 12
https://doi.org/10.5194/tc-16-5061-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-16-5061-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 16, issue 12
Research article
 | 
21 Dec 2022
Research article |  | 21 Dec 2022

The sensitivity of satellite microwave observations to liquid water in the Antarctic snowpack

Ghislain Picard, Marion Leduc-Leballeur, Alison F. Banwell, Ludovic Brucker, and Giovanni Macelloni

Data sets

AMSR-E/AMSR2 Unified L3 Daily 12.5 km Brightness Temperatures, Sea Ice Concentration, Motion & Snow Depth Polar Grids W. N. Meier, T. Markus, and J. C. Comiso https://doi.org/10.5067/RA1MIJOYPK3P

Bedmap2: improved ice bed, surface and thickness datasets for Antarctica (https://secure.antarctica.ac.uk/data/bedmap2) P. Fretwell, H. D. Pritchard, D. G. Vaughan, et al. https://doi.org/10.5194/tc-7-375-2013

The global SMOS Level 3 daily soil moisture and brightness temperature maps (https://data.catds.fr/cpdc/Common_products/GRIDDED/L3/RE07/MIR_CDF3TS/) Ahmad Al Bitar, Arnaud Mialon, Yann H. Kerr, François Cabot, Philippe Richaume, Elsa Jacquette, Arnaud Quesney, Ali Mahmoodi, Stéphane Tarot, Marie Parrens, Amen Al-Yaari, Thierry Pellarin, Nemesio Rodriguez-Fernandez, and Jean-Pierre Wigneron https://doi.org/10.5194/essd-9-293-2017

Surface melting observations in Antarctica by microwave radiometers: Correcting 26-year time series from changes in acquisition hours (https://snow.univ-grenoble-alpes.fr/melting/) G. Picard and M. Fily https://doi.org/10.1016/j.rse.2006.05.010

Model code and software

smrt-model/smrt_liquid_water_paper: Initial release Ghislain Picard https://doi.org/10.5281/zenodo.7302799

smrt-model/smrt: v1.1.0 G. Picard, M. Sandells, and H. Löwe https://doi.org/10.5281/zenodo.7086080

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Short summary
Using a snowpack radiative transfer model, we investigate in which conditions meltwater can be detected from passive microwave satellite observations from 1.4 to 37 GHz. In particular, we determine the minimum detectable liquid water content, the maximum depth of detection of a buried wet snow layer and the risk of false alarm due to supraglacial lakes. These results provide information for the developers of new, more advanced satellite melt products and for the users of the existing products.
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