The ESA CCI SM Freeze/Thaw Product: Global detection of frozen grounds from 1987 to the present

The ESA CCI Soil Moisture product provides a global long-term consistent data record of soil moisture from 1978 up to the present day. It is produced by fusing measurements from a total of 19 both passive and active satellite microwave observations. Determining the physical state of water in the soil is crucial for this product, as retrievals of soil moisture are unreliable in frozen or snow-covered conditions. Beyond its role as a quality control variable, the freeze/thaw state is itself a key environmental indicator, as it impacts the exchange of energy and water between land and atmosphere, shapes seasonal hydrological cycles, and influences agriculture, ecosystems, and climate feedbacks.  

As such, as of version 9.2, the ESA CCI Soil Moisture project is providing an additional global Freeze/Thaw dataset, covering the period from November 1978 to December 2024 with daily temporal and ~25km spatial resolution. This dataset consists of a binary classification (frozen or thawed), the total number of available sensors, the number of sensors detecting frozen soils, and an agreement index for each datapoint. The product combines frozen flags from both active and passive sensors in a conservative manner, i.e. a datapoint is classified as frozen if the frozen soil classification of at least one sensor yields a positive result.  

For passive sensors, the classification of frozen soils follows a decision-tree based algorithm, which incorporates vertically polarized brightness temperature measurements at three different frequencies (Ka/K/Ku-band). These frequency bands are consistently available from 1978 onwards for all sensors included in the CCI SM product except for the L-band sensors SMOS and SMAP, which are thus excluded from the processing of the Freeze/Thaw product.  For active sensors, the surface state flag indicator provided by EUMETSAT H SAF is incorporated directly and a datapoint is marked as ‘frozen’ if its value is other than 1, which includes temporarily frozen soils, permanent ice, and melting water on the surface.   

The current product achieves an estimated accuracy of 75% against in situ surface temperature observations from ISMN and 92% compared to ERA5 reanalysis temperature fields data. The unanimity rule leads to some over-flagging and will thus be refined in future versions. Furthermore, the classification algorithm will be optimised for each sensor and its uncertainty quantified in order to merge individual classifications more robustly.