Effects of land surface model resolution on fluxes and soil state in the Arctic

• Published in: Environmental Research Letters
• Main Authors: Meike Schickhoff, Philipp de Vrese, Annett Bartsch, Barbara Widhalm, Victor Brovkin
• Format: Article in Journal/Newspaper
• Language: English
• Published: IOP Publishing 2024
• Subjects: land surface modeling; permafrost; high resolution; Arctic; Environmental technology. Sanitary engineering; TD1-1066; Environmental sciences; GE1-350; Science; Q; Physics; QC1-999; Siberia
• Online Access: https://doi.org/10.1088/1748-9326/ad6019; https://doaj.org/article/4e2df50108204ad4b12911c7f118aecb

Arctic land is characterized by a high surface and subsurface heterogeneity on different scales. However, the effects of land surface model resolution on fluxes and soil state variables in the Arctic have never been systematically studied, even though smaller scale heterogeneities are resolved in high-resolution land boundary condition datasets. Here, we compare 210 km and 5 km setups of the land surface model JSBACH3 for an idealized case study in eastern Siberia to investigate the effects of high versus low-resolution land boundary conditions on simulating the interactions of soil physics, hydrology and vegetation. We show for the first time that there are differences in the spatial averages of the simulated fluxes and soil state variables between resolution setups. Most differences are small in the summer mean, but larger within individual months. Heterogeneous soil properties induce large parts of the differences while vegetation characteristics play a minor role. Active layer depth shows a statistically significant increase of +20% in the 5 km setup relative to the 210 km setup for the summer mean and +43% for August. The differences are due to the nonlinear vertical discretization of the soil column amplifying the impact of the heterogeneous distributions of soil organic matter content and supercooled water. Resolution-induced differences in evaporation fluxes amount to +43% in July and are statistically significant. Our results show that spatial resolution significantly affects model outcomes due to nonlinear processes in heterogenous land surfaces. This suggests that resolution needs to be accounted in simulations of land surface models in the Arctic.