Beyond MAGT: learning more from permafrost thermal monitoring data with additional metrics

Abstract

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. We observed depth-related differences in decadal MAGT warming rates of more than 0.23 °C decade−1 (50th percentile) for observation depths between 10 and 20 m. The magnitude of these differences is reduced to 0.17 °C decade−1 (50th percentile) when considering the thermal integral(τ‾) – A metric describing a depth-averaged warming trend. The effect of sensor depth on warming trends is greatest in ice-poor soils. In warm permafrost, we find that depth of zero annual amplitude (dza) and mean annual surface temperature (MAGST) exhibit qualitatively different behaviour than MAGT which can help disambiguate low or imperceptible warming rates by the latter metric. Finally, we recommend a parsimonious set of five TSP metrics to provide a better picture of permafrost thaw than MAGT or ALT alone. These are: height of the permafrost table (TOP), dza, τ‾, mean annual ground temperature (MAGT), and MAGST. 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).