Evaluation of Wet Snow Dielectric Mixing Models for L-Band Radiometric Measurement of Liquid Water Content in Greenland’s Percolation Zone

Abstract. Determining the effective permittivity of snow and firn is essential for the accurate estimation of liquid water amount (LWA). Here, we compare ten commonly used microwave dielectric mixing models for estimating LWA in snow and firn using L-band radiometry. We specifically focus on the percolation zone of the Greenland Ice Sheet (GrIS), where the average volume fraction of liquid water is approximately 6 percent. We used L-band brightness temperature (TB) observations from the NASA Soil Moisture Active Passive (SMAP) mission in an inversion-based framework to estimate LWA, applying different dielectric mixing formulations in forward simulation. We compared the permittivities of the mixing models over a range of conditions and their impact on the LWA retrieval. We also compared the LWA retrievals to the corresponding LWA from two state-of-the-art Surface Energy and Mass Balance (SEMB) models. Both SEMB models were forced with in situ measurements from automatic weather stations (AWS) of the Programme for Monitoring of the Greenland Ice Sheet (PROMICE) and Greenland Climate Network (GC-Net) located in the percolation zone of the GrIS and initialized with relevant in situ profiles of density, stratigraphy, and sub-surface temperature measurements. The results show that the mixing models produce substantially different real and imaginary parts of the dielectric constant. The choice of mixing model has a significant impact on the LWA retrieved from the TB. The correspondence with the SEMB LWA varied by model and site; the Sihvola power-law based mixing model showed an overall better performance than the other models for 2023 melt season. The analysis facilitates an appropriate choice of dielectric mixing model on the LWA retrieval algorithm.