Team
- Christina Schaedel Senior Research Scientist
- Ted Schuur Co-PI; Northern Arizona University Center for Ecosystem Science & Society
- Deborah Huntzinger Co-PI, NAU Center for Ecosystem Science & Society
- Bill Riley Lawrence Berkeley National Lab, Climate and Ecosystem Sciences Division
- Jeralyn Poe NAU School of Informatics, Computing, and Cyber Systems
- Jon M Wells Former Collaborator
Models help us to describe, understand, and predict the natural world.
Some models are specific to one natural process, for example, rainfall. Global climate models, however, take into account many natural processes—like greenhouse gas emissions, carbon uptake by plants, and ocean temperatures—to make predictions about global average temperatures or other climate conditions. If these models are missing key components that drive patterns of change, their predictions will be unreliable or inaccurate.
Permafrost is one major driver of global change that is currently underrepresented in climate models. Permafrost is perennially frozen ground that, as it thaws, is causing the land to collapse and release unaccounted-for amounts of greenhouse gasses into our atmosphere. For people living on top of permafrost, and for realistic global carbon budget estimates, there is a critical need for accurate accounting of permafrost emissions in climate models.
The Warming Permafrost Model Intercomparison Project (WrPMIP) is working to facilitate the representation of permafrost processes in models, provide guidance to model developers, and ultimately improve how models represent permafrost.
Our Work
Our collaborative group of international experts is working on several key aspects of improving permafrost model representation:
- Model assessment: We met virtually and in person to discuss how to best assess the performance of various permafrost enabled models.
- Regional simulations: We conducted simulations of the Pan-Arctic region to test how models respond to perturbation across large scales and under varying climatic conditions.
- Site-level simulations: We modeled expected warming for a specific location, and then compared those results to field experiments where we manipulated warming in the environment. This allowed precise comparisons between model responses and observed warming responses.
- Functional benchmarks: We are creating a standardized set of criteria that can be used to compare and evaluate performance of models. These criteria will be integrated into frameworks adopted by the research community, like the International Land Model Benchmarking project (ILAMB).
As permafrost isn’t contained within the boundaries of just one country, international engagement is critical to ensuring that models are informed by a variety of perspectives, and that researchers all around the world are working with models that accurately represent permafrost.
At in-person meetings and conferences like AGU, WrPMIP is envisioning the future of permafrost modeling and creating a community of practice where experts can share their expertise, challenges, and new findings.
Impact
If permafrost thaw is not accounted for in climate models, and in the projections they make for our future, they may be underestimating the pace and magnitude of the warming we will experience.
By improving these models, WrPMIP is working towards better estimates of permafrost emissions so we can have a clearer picture of the future climate.
WrPMIP is funded by the Department of Energy’s Regional & Global Model Analysis program.
What happens to the carbon in permafrost is one of the biggest unknowns about our future climate.Dr. Christina Schädel, Senior Research Scientist, Woodwell Climate Research Center
