Retrieval and validation of total seasonal liquid water amounts in the percolation zone of the Greenland ice sheet using L-band radiometry

Hossan, Alamgir; Colliander, Andreas; Vandecrux, Baptiste; Schlegel, Nicole-Jeanne; Harper, Joel; Marshall, Shawn; Miller, Julie Z.

doi:https://doi.org/10.5194/tc-19-4237-2025

Articles | Volume 19, issue 10

https://doi.org/10.5194/tc-19-4237-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/tc-19-4237-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 19, issue 10

Research article

|

06 Oct 2025

Research article |

| 06 Oct 2025

Retrieval and validation of total seasonal liquid water amounts in the percolation zone of the Greenland ice sheet using L-band radiometry

Alamgir Hossan, Andreas Colliander, Baptiste Vandecrux, Nicole-Jeanne Schlegel, Joel Harper, Shawn Marshall, and Julie Z. Miller

Data sets

SMAP Radiometer Twice-Daily rSIR-Enhanced EASE-Grid 2.0 Brightness Temperatures (NSIDC-0738, Version 2) M. J. Brodzik et al. https://doi.org/10.5067/YAMX52BXFL10

PROMICE and GC-Net automated weather station data in Greenland P. How et al. https://doi.org/10.22008/FK2/IW73UU

The SUMup collaborative database: Surface mass balance, subsurface temperature and density measurements from the Greenland and Antarctic ice sheets (2024 release) Baptiste Vandecrux et al. https://doi.org/10.18739/A2M61BR5M

Retrieval and Validation of Total Seasonal Liquid Water Amounts in the Percolation Zone of Greenland Ice Sheet Using L-band Radiometry (Version 1) A. Hossan https://doi.org/10.5281/zenodo.13800047

Model code and software

MATLAB code for firn thermodynamic and hydrological modelling S. Marshall https://doi.org/10.5683/SP2/WRWJAZ

Short summary

We used L-band observations from the Soil Moisture Active Passive (SMAP) mission to quantify the surface and subsurface liquid water amounts (LWAs) in the percolation zone of the Greenland ice sheet. The algorithm is described, and the validation results are provided. The results demonstrate the potential for creating an LWA data product across the Greenland ice sheet (GrIS), which will advance our understanding of ice sheet physical processes for better projection of Greenland’s contribution to global sea level rise.