Improving Permafrost Soil Representation in a Dynamic Global Vegetation Model Enhances Predictions of Boreal Forest Carbon Dynamics and Vegetation Structure

Abstract. Boreal forests constitute a major component of the global terrestrial carbon sink, yet how climate-driven permafrost degradation alters their ecosystem carbon dynamics remains poorly constrained. Despite their importance, the persistence of this carbon sink remains highly uncertain, partly due to limitations in Earth system model projections of future carbon dynamics in permafrost-affected regions. Here, we improve the soil module of the LPJ-GUESS model by implementing a deep soil profile (3 m) with refined vertical discretization (30 layers) and explicit ice-impedance effects. The enhanced model (LPJ-GUESS-Cryo) is then used to simulate carbon and hydrothermal dynamics in the climate-sensitive boreal forests of Northeast China. Model evaluation shows that LPJ-GUESS-Cryo substantially improves the simulation of soil hydrothermal dynamics relative to the default configuration. The correlation coefficient for deep soil temperature (1 m) increases from 0.818 to 0.894, while the systematic overestimation of soil water content is effectively corrected, with the bias at 1 m reduced from 0.321 to -0.006. These process-level improvements lead to a more realistic simulation of vegetation composition. The dominance of needleleaf forests is corrected from near-complete saturation to 24.1 %, consistent with observed vegetation patterns. Consequently, biases in carbon estimates are reduced, with simulated net primary productivity decreasing from 583.5 to 560.1 g C m^-2 yr^-1 and aboveground biomass from 112.9 to 99.0 t ha^-1, resulting in better agreement with estimates from satellite-based observations. Model sensitivity analysis indicates that vegetation composition is highly sensitive to changes in soil hydrothermal conditions relative to the control simulation. Pronounced shifts in vegetation composition occur when soil temperature increases exceed 0.6 °C and soil water deficits exceed 0.6 m³ m^-3 compared to the default model configuration. Overall, this study highlights that accurately representing permafrost processes in dynamic global vegetation models is critical for reducing uncertainties in high-latitude climate-carbon feedbacks.