Evaluation of Earth System Model Simulation for Subsurface Thermal Dynamics of Arctic Landscapes: Insight from an Intermodal Comparison at a Column Scale
Authors
Yu Zhang1* (yuzhang@lanl.gov), Xiang Huang1, Charles Abolt1, Scott Painter2, Ethan Coon2, Katrina Bennett1, Colleen Iversen2
Institutions
1Los Alamos National Laboratory, Los Alamos, NM; 2Oak Ridge National Laboratory, Oak Ridge, TN
URLs
Abstract
The Arctic is warming twice as fast as the rest of the planet, which poses a significant threat to both the Arctic and low-latitude regions. Earth system models (ESMs) serve as efficient tools for capturing interactions and predicting the impacts of Arctic warming. Within an ESM, the land model component is critical for simulating hydrothermal, ecological, and biogeochemical processes. Many ESM-based studies focus on Arctic prediction by improving process representation and employing finer mesh resolutions. However, the uncertainties of these model predictions are still poorly understood due to of a lack of observations that can be used for comparison at ESM scales. To address this, the study explores a novel model-data integrated approach (ModEx) to evaluate ESM predictions for Arctic landscapes. The team focused on the performance and uncertainty in DOE’s E3SM Land Model (ELM) in simulating subsurface hydrothermal dynamics for tundra landscapes. Using the field observations and well-tested process-based Advanced Terrestrial Simulator (ATS) model at the Barrow Environmental Observatory (BEO) as a reference, researchers validated ELM’s simulation for the BEO site at a column scale. Using the same parameters, subsurface layer partitioning, and meteorological forcing in ELM and ATS, the team found that ELM, with its default 15% soil moisture as the initial condition, consistently underestimates soil moisture. However, aligning with the ATS initialization strategy of using saturated soil as an initial condition, ELM significantly improves in modeling soil moisture variation. Adopting this initialization approach, subsequent simulations found that the ELM subsurface temperature fits well with field observations. The project’s simulations also found that snow is an important control on ELM subsurface simulation. The study showcases the effectiveness of the ModEx approach to evaluate ESM performance in Arctic prediction with the potential to extend this approach to evaluate other processes beyond subsurface hydrothermal dynamics.