Improving permafrost dynamics in land surface models: insights from dual sensitivity experiments

• Main Author: Damseaux, Adrien (Dr.)
• Format: Doctoral or Postdoctoral Thesis
• Language: English
• Published: 2024
• Subjects: ddc:530; Extern; Institut für Physik und Astronomie; Arctic; Active layer monitoring; Active layer thickness; Circumpolar Active Layer Monitoring Network; Climate change; permafrost
• Online Access: https://publishup.uni-potsdam.de/frontdoor/index/index/docId/63945; https://nbn-resolving.org/urn:nbn:de:kobv:517-opus4-639450; https://doi.org/10.25932/publishup-63945; https://publishup.uni-potsdam.de/files/63945/damseaux_diss.pdf

The thawing of permafrost and the subsequent release of greenhouse gases constitute one of the most significant and uncertain positive feedback loops in the context of climate change, making predictions regarding changes in permafrost coverage of paramount importance. To address these critical questions, climate scientists have developed Land Surface Models (LSMs) that encompass a multitude of physical soil processes. This thesis is committed to advancing our understanding and refining precise representations of permafrost dynamics within LSMs, with a specific focus on the accurate modeling of heat fluxes, an essential component for simulating permafrost physics. The first research question overviews fundamental model prerequisites for the representation of permafrost soils within land surface modeling. It includes a first-of-its-kind comparison between LSMs in CMIP6 to reveal their differences and shortcomings in key permafrost physics parameters. Overall, each of these LSMs represents a unique approach to simulating soil processes and their interactions with the climate system. Choosing the most appropriate model for a particular application depends on factors such as the spatial and temporal scale of the simulation, the specific research question, and available computational resources. The second research question evaluates the performance of the state-of-the-art Community Land Model (CLM5) in simulating Arctic permafrost regions. Our approach overcomes traditional evaluation limitations by individually addressing depth, seasonality, and regional variations, providing a comprehensive assessment of permafrost and soil temperature dynamics. I compare CLM5's results with three extensive datasets: (1) soil temperatures from 295 borehole stations, (2) active layer thickness (ALT) data from the Circumpolar Active Layer Monitoring Network (CALM), and (3) soil temperatures, ALT, and permafrost extent from the ESA Climate Change Initiative (ESA-CCI). The results show that CLM5 aligns well with ESA-CCI and CALM for ...