Estimating Permafrost Distribution and Covariability with Landscape Characteristics

The Science

Understanding permafrost distribution in the subsurface will help scientists better understand Arctic change due to climate warming. Although ground temperature can be measured in boreholes, few boreholes exist to do these measurements. Researchers measured the temperature and electrical resistivity of the ground on the Seward Peninsula in Alaska and used machine learning to gather details about the permafrost. By linking permafrost properties with observations aboveground, researchers demonstrated the slope aspect and angle and the vegetation exhibit correlation with permafrost size and temperature.

The Impact

As climate warming changes the Arctic landscape above and below the surface, knowing where and how deep the ground is frozen is crucial to predict how the Arctic will change. A combination of temperature and electrical resistivity measurements can provide reliable estimates of permafrost location and depth. Research also shows a direct link between the state of permafrost and its location on hillslopes. Knowing such relationships can improve estimates of where permafrost exist and help predict Arctic change.

Summary

Assessing the lateral and vertical extent of permafrost is critical to understanding Arctic ecosystems’ fate under climate change. Yet, direct measurements of permafrost distribution and temperature are often limited to few borehole locations. In this study, researchers assessed the use of co-located ground temperature and ground electrical resistivity measurements to estimate at high resolution the distribution of permafrost in 3 watersheds underlain by discontinuous permafrost. Synthetic modeling showed that combining co-located temperature and electrical resistivity tomography using machine learning methods can identify permafrost distribution more accurately than conventional methods. By linking the size of the identified permafrost bodies to surface observations, researchers showed that tall vegetation (>0.5 m) and gentle slopes (<15°) are related to warmer and smaller permafrost bodies and a more frequent occurrence of taliks. In addition, results indicate that talik occurrence is not always associated with tall shrubs, confirming a variety of trajectories in temperature and vegetation dynamics across the landscape.

Principal Investigator

Baptiste Dafflon
Lawrence Berkeley National Laboratory
[email protected]

Program Manager

Daniel Stover
U.S. Department of Energy, Biological and Environmental Research (SC-33)
Environmental System Science
[email protected]

Funding

This research is part of the Next-Generation Ecosystem Experiments (NGEE) Arctic project, which is funded by the Biological and Environmental Research program in the U.S. Department of Energy’s Office of Science (Grant DE-AC02-05CH11231).

References