Arctic Ecosystem Modeling: What Role Can Paleo History Play in Reducing Model Uncertainty?
Authors
Hannah Mevenkamp1* (hkmevenkamp@alaska.edu), Tobey Carman1, Helene Genet1, Ruth Rutter1, Shawn Serbin3, Eugenie Susanne Euskirchen1, Colleen Iversen3
Institutions
1University of Alaska–Fairbanks, AK; 2Brookhaven National Laboratory, Upton, NY; 3Oak Ridge National Laboratory, Oak Ridge, TN
URLs
Abstract
Ongoing and expected changes in the carbon balance of the Arctic tundra are important for the global carbon budget, but uncertainty remains in the ability to model Arctic ecosystems. The influence of initial conditions is often underestimated as a source of this model uncertainty, particularly with respect to the initial model set-up with pre-run, equilibrium, and spin-up simulations that are necessary to reach an accurate representation of pre-industrial conditions. This is particularly relevant in areas underlain by permafrost like the Arctic.
Arctic permafrost contains large amounts of carbon (1,460–1,600 petagrams of carbon) and dates to the last glacial maximum (LGM). This permafrost has remained stable under pre-industrial conditions due to a hysteresis behavior, resulting in a much longer thermal memory than commonly accounted for in modeling. Consequently, this leads to an underestimation of pre-industrial permafrost extent and may cause significant model uncertainty concerning carbon balance and soil temperatures.
The project assesses whether considering paleo history improves soil thermal and carbon balance representation in the Dynamic Vegetation, Dynamic Organic Soil, Terrestrial Ecosystem Model. Researchers conduct simulations at several sites across Alaska and compare simulations with and without paleo history with borehole observations and carbon flux measurements. The team examines the impact of different paleo climate scenarios, each varying the temperature difference from the LGM to pre-industrial conditions. Initial simulations reveal that colder paleo climate scenarios result in initially cooler soils, which in some instances exhibit a more rapid warming trend under recent climatic warming compared to warmer scenarios. This shift in thermal dynamics carries significant implications for the carbon balance and overall model uncertainty. Through this project, the team aims to assess the potential benefits of adopting paleo history more widely in modeling to reduce these model uncertainties.