Satellite-Based Extension of the Soil Freezing Curve Paradigm: Detecting Extrinsic Freeze/Thaw Thresholds with SMAP in Mid-Latitudinal Agricultural Fields
Abstract. We present a novel method for surface freeze/thaw (F/T) classification based on L-band brightness temperature (TB), as measured by the Soil Moisture Active Passive (SMAP) mission, combined with thermodynamic temperature estimates, whether in situ or derived from near real-time model output. Variations in the cryosphere have significant, lasting impacts on physical, biological, and social systems, and act as sensitive indicators of climate change. Remote sensing at microwave frequencies is uniquely suited for monitoring the cryosphere’s spatial and temporal dynamics. Indeed, SMAP was tasked with providing a daily classification of the surface F/T state as one of two primary mission goals. Although surface F/T events are extrinsically driven phenomena, most existing classification algorithms rely on intrinsic thresholds – those derived from single-variable observables – that may not accurately reflect in situ conditions. Meanwhile, soil physicists have long used a robust framework to study the relationship between unfrozen water content and sub-freezing temperature, known as the soil freezing characteristic curve (SFC). These curves, and to a lesser extent their soil thawing characteristic curve (STC) branches, have been well studied in laboratory settings using a variety of instruments and methods. These concepts have not been extended to remote sensing (RS) until now.
The remotely sensed surface freezing characteristic curves (SurFCs) introduced here are the satellite-pixel-scale counterpart to SFCs. SurFCs are constructed with SMAP TB measurements, which are inversely correlated with water content, along with thermodynamic temperature records at two mid-latitude sites. We used in situ temperature data from SMAP core validation sites near Kenaston, Saskatchewan and Carman, Manitoba, covering a combined total of nine years, alongside modelled temperature estimates from the Goddard Earth Observing System Model, Version 5 Forward Processing product (GEOS-5 FP). SurFCs constructed with in situ soil temperatures showed a structure like that of SFCs, including analogue thawing branches, identified as surface thawing characteristic curves (SurTCs). Lastly, we show SurTCs can serve as a tool for identifying extrinsic thresholds – transition points linked to both the system’s physical state and its external drivers – enhancing the realism and operational accuracy of satellite-based F/T classification. Overall, the proposed TBHmin approach improved detection accuracy by 39.4 % compared to the widely used Normalized Polarization Ratio (NPR) method.
This analysis challenges the prevailing assumption that 0.15 °C is a universal F/T threshold. Instead, we argue that the threshold should be determined from measurements of the system’s physical response and environmental forcing (SurFC/SurTC). Although useful, a 0.15 °C classifier is not uniformly applicable across freeze–thaw phenomena or measurement methods.
Review „Satellite-Based Extension of the Soil Freezing Curve Paradigm: Detecting Extrinsic Freeze/Thaw Thresholds with SMAP in Mid-Latitudinal Agricultural Fields“
The authors present a well written and thoughtful study on a relevant issue. In my opinion this manuscript will contribute to the field and fits well into the Cryosphere journal. In the following, I listed some comments that, in my opinion, will strengthen the paper
General comments:
The paper is well grounded in literature regarding passive microwave remote sensing and laboratory studies, however it is lacking in some respects regarding active systems. While some methodological aspects may be different, similar ideas regarding freeze/thaw retrieval have been explored with active systems (e.g. ASCAT, Sentinel-1) which should be touched on in the introduction and discussion. I will list a couple of suggestions of papers to cite at the end, but the authors should also do their own literature research in this direction.
Specific comments:
Some publications to consider (there is more out there, these are just some suggestions):
Naeimi et al., "ASCAT Surface State Flag (SSF): Extracting Information on Surface Freeze/Thaw Conditions From Backscatter Data Using an Empirical Threshold-Analysis Algorithm," in IEEE Transactions on Geoscience and Remote Sensing, vol. 50, no. 7, pp. 2566-2582, July 2012, doi: 10.1109/TGRS.2011.2177667.
Bartsch, A., Muri, X., Hetzenecker, M., Rautiainen, K., Bergstedt, H., Wuite, J., Nagler, T., and Nicolsky, D.: Benchmarking passive-microwave-satellite-derived freeze–thaw datasets, The Cryosphere, 19, 459–483, https://doi.org/10.5194/tc-19-459-2025, 2025.
Bergstedt, Helena, et al. "Deriving a frozen area fraction from metop ASCAT backscatter based on Sentinel-1." IEEE Transactions on Geoscience and Remote Sensing 58.9 (2020): 6008-6019.