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

Ground temperature is the most common variable in permafrost monitoring and one of three products used to characterize the permafrost Essential Climate Variable by the World Meteorological Organization.

PermafrostNet’s data scientist, Nicholas Brown, has conducted an investigation into the metrics used to assess indicators of permafrost and heat changes in the ground.

Based on this investigation, recommendations are provided for a set of five metrics that offer a more comprehensive picture of permafrost thaw.

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.

The team investigated the behaviour of existing and novel metrics derived from temperature observations (TSP metrics) using an ensemble of more than seventy 120-year simulations. They 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. They also quantified the effect of sensor placement on the magnitude of observed MAGT trends.

Brown, N. and Gruber, S. (2025). Beyond MAGT: learning more from permafrost thermal monitoring data with additional metrics, EGUSphere [preprint], DOI: https://doi.org/10.5194/egusphere-2025-2658

Seminar – 18 September – Development and demonstration of a statistical ranking framework for ground temperature models, tailored towards permafrost environments.

Hannah Macdonell will be presenting Development and demonstration of a statistical ranking framework for ground temperature models, tailored towards permafrost environments.

Date: 18 September 2024
Time: 13:00-14:00 Eastern Time
Location: Zoom (details are posted in our Teams site).

Models used to simulate permafrost variables such as ground temperature are important tools for understanding the current state and future conditions of permafrost. However, few objective methods of establishing model accuracy exist for permafrost environments. Additionally, models often range in their performance given different conditions such as terrain type or seasonality. Hannah will be presenting her master’s research that looked at (1) identifying patterns in ground-temperature model performance under different testing conditions and (2) developing a quantitative measure of ground-temperature model performance in permafrost zones.