Abstract. The Soil Moisture and Ocean Salinity (SMOS) satellite is a valuable tool for monitoring global soil freeze–thaw dynamics, particularly in high-latitude environments where these processes are important for understanding ecosystem and carbon cycle dynamics. This paper introduces the updated SMOS Level-3 (L3) Soil Freeze–Thaw (FT) product and details its threshold-based classification algorithm, which utilizes L-band passive microwave measurements to detect soil freeze–thaw transitions; this is possible due to the difference in dielectric properties between frozen and thawed soils at this frequency band. The algorithm applies gridded brightness temperature data from the SMOS satellite, augmented with ancillary datasets of air temperature and snow cover, to generate global estimates of the freeze–thaw state. A recent update to the algorithm includes improved noise reduction through temporal filtering. Validation results against in situ soil moisture and temperature measurements and comparisons to ERA5-Land reanalysis data demonstrate the ability of the product to detect the day of first freezing, an important metric for better understanding greenhouse gas fluxes and ecosystem dynamics, with improved accuracy. However, limitations remain, particularly in regions affected by radio frequency interference (RFI) and during spring melt periods, when wet snow hinders soil thaw detection. Despite these challenges, the SMOS FT product provides crucial data for carbon cycle studies, particularly in relation to methane fluxes, as soil freezing affects methane emissions in high-latitude regions. The SMOS L3FT dataset is available at https://doi.org/10.57780/sm1-fbf89e0 (ESA, 2023).
Rautiainen et al. (2025) studied this question.