Abstract
Abstract. The Arctic is warming rapidly, especially in winter, which is causing large-scale reductions in snow cover. Snow is one of the main controls on soil thermodynamics, and changes in its thickness and extent affect both permafrost thaw and soil biogeochemistry. Since soil respiration during the cold season potentially offsets carbon uptake during the growing season, it is essential to achieve a realistic simulation of the effect of snow cover on soil conditions to more accurately project the direction of arctic carbon–climate feedbacks under continued winter warming. The Lund–Potsdam–Jena General Ecosystem Simulator (LPJ-GUESS) dynamic vegetation model has used – up until now – a single layer snow scheme, which underestimated the insulation effect of snow, leading to a cold bias in soil temperature. To address this shortcoming, we developed and integrated a dynamic, multi-layer snow scheme in LPJ-GUESS. The new snow scheme performs well in simulating the insulation of snow at hundreds of locations across Russia compared to observations. We show that improving this single physical factor enhanced simulations of permafrost extent compared to an advanced permafrost product, where the overestimation of permafrost cover decreased from 10 % to 5 % using the new snow scheme. Besides soil thermodynamics, the new snow scheme resulted in a doubled winter respiration and an overall higher vegetation carbon content. This study highlights the importance of a correct representation of snow in ecosystem models to project biogeochemical processes that govern climate feedbacks. The new dynamic snow scheme is an essential improvement in the simulation of cold season processes, which reduces the uncertainty of model projections. These developments contribute to a more realistic simulation of arctic carbon–climate feedbacks.
Highlights
The Arctic is undergoing rapid warming, with some of the most pronounced changes occurring during the winter (Box et al, 2019; Natali et al, 2019)
Snow insulation is recognized as the primary control over soil thermodynamics (Lawrence and Slater, 2010), and soil temperature is closely connected to physical and biogeochemical processes (Peng et al, 2016)
These detailed snowpack observations from Zackenberg helped to determine whether the Dynamic scheme can simulate internal snowpack dynamics, snow depth, and snow density
Summary
The Arctic is undergoing rapid warming, with some of the most pronounced changes occurring during the winter (Box et al, 2019; Natali et al, 2019). Observations show that snow cover changes have played a major role in a warming trend of permafrost soils of approximately 0.3 ◦C per decade (Biskaborn et al, 2019; AMAP, 2017) This warming may lead to increased microbial activity, decomposition rates and bioavailability of previously frozen soil carbon. Since permafrost soils contain approximately 1600 Pg carbon, accounting for half of the global soil carbon storage (Hugelius et al, 2014), there is ample potential for these changes to lead to the release of the greenhouse gases CO2 and methane This has the potential to accelerate global warming (Schuur et al, 2015), which underlines the need for a better understanding of drivers and potential feedbacks to better predict the rate and magnitude of future carbon exchange
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