Model simulations of arctic biogeochemistry and permafrost extent are highly sensitive to the implemented snow scheme in LPJ-GUESS

Abstract. The Arctic is warming rapidly, especially in winter, which causing large-scale reductions snow cover. Snow one of the main controls on soil thermodynamics, and changes its thickness extent affect both permafrost thaw biogeochemistry. Since respiration during cold season potentially offsets carbon uptake growing season, it essential to achieve a realistic simulation effect cover conditions more accurately project direction arctic carbon–climate feedbacks under continued winter warming. Lund–Potsdam–Jena General Ecosystem Simulator (LPJ-GUESS) dynamic vegetation model has used – up until now single layer scheme, underestimated insulation snow, leading bias temperature. To address this shortcoming, we developed integrated dynamic, multi-layer scheme LPJ-GUESS. new performs well simulating at hundreds locations across Russia compared observations. We show that improving physical factor enhanced simulations an advanced product, where overestimation decreased from 10 % 5 using scheme. Besides resulted doubled overall higher content. This study highlights importance correct representation ecosystem models biogeochemical processes govern climate feedbacks. improvement processes, reduces uncertainty projections. These developments contribute