| 06 Aug 2025
Beyond MAGT: learning more from permafrost thermal monitoring data with additional metrics
Abstract. Metrics such as the mean annual ground temperature (MAGT) and active layer thickness (ALT) are used to monitor and quantify permafrost change. However, these have limitations including those arising from the effects of latent heat, which reduce their sensitivity. We investigated the behaviour of existing and novel metrics derived from temperature observations (TSP metrics) using an ensemble of more than seventy 120-year simulations. We evaluated which TSP metrics provide new insight into permafrost change and evaluated how reliably each one indicates changes in sensible, latent, and total heat contents for different levels of sensor quality. We also quantified the effect of sensor placement on the magnitude of observed MAGT trends.
Based on this, we recommend a parsimonious set of five TSP metrics that provide a better picture of permafrost thaw than MAGT alone. These are: height of the permafrost table (TOP), depth of zero annual amplitude (dza), thermal integral (τ), mean annual ground temperature (MAGT), and mean annual surface temperature (MAGST).
We observed depth-related differences in MAGT warming rates of more than 0.23 °C dec-1 in 50 % of 10-year observation periods for observation depths between 10 m and 20 m. The magnitude of these differences roughly corresponds to the mean warming rate reported for discontinuous permafrost. The effect of sensor depth on warming trends is found to be greatest in ice-poor soils. These results illustrate the challenge of interpreting the magnitude of observed ground temperature trends.
Our results can be used to inform permafrost monitoring strategies and help contextualize observed trends. Consistent metrics can be produced from observed and simulated thermal data via the "tspmetrics" library available on the Python Package Index (PyPi).
Competing interests: SG is the owner of Cryogeeks (13756378 Canada Inc.), which distributes GeoPrecision equipment, referred to in this study for describing sensing systems. The authors declare that they have no other competing interests.
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This study proposes and seeks to demonstrate the use of novel metrics derived from temperature observations to complement commonly used metrics such as mean annual ground temperature (MAGT) and active layer thickness (ALT), with the goal of improving the quantification of permafrost change, especially by better accounting for the effects of latent heat. The authors investigate the behaviour of existing and novel metrics using an ensemble of more than seventy 120 year simulations. They also apply these metrics to observations and discuss issues associated with sensor deployment and resolution. I think the topic is of interest and value to the community, and I strongly agree with the authors that new metrics need to be explored and proposed. I believe the real value and usefulness of new or improved metrics can only be assessed through their adoption, or lack thereof, in future studies. The work presented by the authors is detailed and appears correct with regard to the calculations and testing performed. I therefore have only minor comments.
Minor comments:
In the abstract (lines 11–14), the text reads as if it presents a finding related to MAGT, but it does not discuss how other metrics may be more suitable, particularly with respect to uncertainty versus informative value. Later in the paper (L.389), there is some discussion of the value of the “annual thermal integral” in this context. Consider revising the abstract to more clearly highlight what the new metrics can contribute.
In the abstract and the introduction, consider clarifying that MAGT is generally inferred at a single depth and is sometimes compared across sites at different depths. I found this background somewhat unclear.
L.550: Few details are provided on the model. Consider adding a few sentences describing the processes represented in the active layer and talik, if present (for example, advection). Please also explain how freeze thaw energy is represented in the model. While some details are provided in the Supplementary Material, the main text lacks basic information on the model type.
The use of a model may influence the results if the model has limitations in representing certain ongoing hydro thermal processes. Consider clarifying potential weaknesses and their implications (for testing the value of the metrics).