Dry/wet snow indicator from SMOS

This dataset provides daily dry/wet sonw indicator over ice sheet and ice shelves as detected from L-band satellite observations performed by the radiometer carried out by the ESA SMOS mission. The method uses an adaptive threshold to detect the daily melt occurrence in each grid point and for each year. The developed algorithm is based on Torinesi et al. (2003) and described in Leduc-Leballeur et al. (2020).

Product description

The algorithm returns a daily binary indicator: 0 for dry snow and 1 for wet snow.

The SMOS ice melt occurrence products are provided over the Equal-Area Scalable Earth version 2.0 grid (EASE-Grid 2.0; Brodzik et al., 2012) in the Southern and Northern Hemisphere Azimuthal projections. They are daily products with a spatial resolution of 25 km x 25 km.

These products are build from the Level 3 SMOS brightness temperature product provided by CATDS (Al Bitar et al., 2017).

Datasets

Condition of use

For questions or collaborations, please to contact: smosmelt-contact at ifac.cnr.it

Information and data available on this page are provided without warranty of any kind. When using this dataset in a publication, please to cite the related work with:

Leduc-Leballeur M., Picard G., Macelloni G., Mialon A., Kerr Y. H., 2020, Melt in Antarctica derived from Soil Moisture and Ocean Salinity (SMOS) observations at L band, The Cryosphere, 14, 539–548, https://doi.org/10.5194/tc-14-539-2020.

Seasonal evolution of the wet snow extent

Seasonal evolution of the wet snow extent in AntarcticaSeasonal evolution of the wet snow extent in Greenland

To go further

Multi-frequencies microwave observations from SMOS and AMSR2 are used to provide a classification of the wet/dry snow status in Antarctica. This work is presented in Leduc-Leballeur et al., 2026 and the dataset is available here.

References

Al Bitar A., Mialon A., Kerr Y. H., Cabot F., Richaume P., Jacquette E., Quesney A., Mahmoodi A., Tarot S., Parrens M., Al-Yaari A., Pellarin T., Rodriguez-Fernandez N., Wigneron J.-P., 2017, The global SMOS Level 3 daily soil moisture and brightness temperature maps, Earth System Science Data, 9(1), 293–315, https://doi.org/10.5194/essd-9-293-2017.

Brodzik M. J., Billingsley B., Haran T., Raup B., Savoie M. H., 2012, EASE-grid 2.0: incremental but significant improvements for earth-gridded data sets, ISPRS Int. J. Geo-Inf., 1, 32–45, https://doi.org/10.3390/ijgi1010032.

Leduc-Leballeur M., Picard G., Macelloni G., Mialon A., Kerr Y. H., 2020, Melt in Antarctica derived from Soil Moisture and Ocean Salinity (SMOS) observations at L band, The Cryosphere, 14, 539–548, https://doi.org/10.5194/tc-14-539-2020.

Leduc-Leballeur M., Picard G., Zeiger P., Macelloni G., 2026, Empirical classification of dry-wet snow status in Antarctica using multi-frequency passive microwave observations, The Cryosphere, 20, 1199–1216, https://doi.org/10.5194/tc-20-1199-2026.

Leduc-Leballeur M., Picard G., Zeiger P., 2026, Dry-wet snow status in Antarctica using daily multi-frequency passive microwave observations, https://doi.org/10.57932/421499d3-5705-4cc8-96f7-6902e01e5049

Torinesi O., Fily M., and Genthon C., 2003, Variability and Trends of the Summer Melt Period of Antarctic Ice Margins since 1980 from Microwave Sensors, Journal of Climate, 16(7), 1047–1060, https://doi.org/10.1175/1520-0442(2003)016<1047:VATOTS>2.0.CO;2.

Acknowledgements

This work benefits from the ESA funding support through various projects (SMOS ESL, CryoSMOS) and contributes to eo science for society.