EGU24-14659, updated on 09 Mar 2024
EGU General Assembly 2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Q-Arctic: A synergetic approach to observe and model pan-Arctic interactions between hydrology and carbon

Mathias Göckede1, Victor Brovkin2, Annett Bartsch3, Martin Heimann1, and the Q-Arctic Team*
Mathias Göckede et al.
  • 1Max Planck Institute for Biogeochemistry, Jena, Germany (
  • 2Max Planck Institute for Meteorology, Hamburg, Germany
  • 3b.geos GmbH, Korneuburg, Austria
  • *A full list of authors appears at the end of the abstract

Arctic permafrost has been identified as a critical element in the global climate system, since it stores a vast amount of carbon that is at high risk of being released under climate change. The feedbacks between permafrost carbon and climate change are moderated by complex interactions between physical, hydrological, biogeochemical, and ecological processes. Many of these are not well understood to date, and therefore also only rudimentarily represented in current Earth System Models (ESMs). A particular problem in this context is a scaling gap between processes and model grid.

The Q-ARCTIC project funded by the European Research Council (ERC) follows a synergetic approach by combining remote sensing and local-scale observations with modeling on scales from a few meters to hundreds of kilometers. The primary objective of Q-ARCTIC is to close the gap between process scales and the much coarser grid resolution of Earth System Models (ESMs), with a particular focus on the net effect of disturbance processes and associated changes in hydrology on the pan-Arctic scale. To close this gap, we developed new ESM modules representing subgrid through stochastic parameterizations, trained and evaluated with high-resolution remote sensing data and site-level observations.

We will present novel results based on in-situ observations that characterize prominent Arctic disturbance features, and satellite remote sensing products investigating fine scale (few meters) patterns in Arctic landscapes that are undergoing modifications linked to climate change. Targets investigated include for example sinking surfaces, wetness gradients in heterogeneous landscapes, or drained lake basins. Assimilation of these new datasets supported the development of new ESM model components that successfully capture the statistics of small-scale features, e.g. depressions linked to sinking surfaces, or surface water bodies that form when soil ice melts. Our results demonstrate that the ability to project the response of the high-latitude water, energy and carbon cycles to rising global temperatures may strongly depend on the ability to adequately represent the soil hydrology in permafrost affected regions.

Q-Arctic Team:

Abdullah Bolek, Barbara Widhalm, Clemens von Baeckmann, Constanze Reinken, Goran Georgievski, Helena Bergstedt, Judith Vogt, Kseniia Ivanova, Luana Basso, Mark Schlutow, Martijn Pallandt, Meike Schickhoff, Nathalie Ylenia Triches, Philipp de Vrese, Rustam Khairullin, Stiig Wilkenskjeld, Thomas Kleinen, Tobias Stacke, Veronika Gayler, Zoe Rehder

How to cite: Göckede, M., Brovkin, V., Bartsch, A., and Heimann, M. and the Q-Arctic Team: Q-Arctic: A synergetic approach to observe and model pan-Arctic interactions between hydrology and carbon, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14659,, 2024.