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Abstract Accelerated warming of the Arctic can affect the global climate system by thawing permafrost and exposing organic carbon in soils to decompose and release greenhouse gases into the atmosphere. We used a process-based biosphere model (DVM-DOS-TEM) designed to simulate biophysical and biogeochemical interactions between the soil, vegetation, and atmosphere. We varied soil and environmental parameters to assess the impact on cryohydrological and biogeochemical outputs in the model. We analyzed the responses of ecosystem carbon balances to permafrost thaw by running site-level simulations at two long-term tundra ecological monitoring sites in Alaska: Eight Mile Lake (EML) and Imnavait Creek Watershed (IMN), which are characterized by similar tussock tundra vegetation but differing soil drainage conditions and climate. Model outputs showed agreement with field observations at both sites for soil physical properties and ecosystem CO₂fluxes. Model simulations of Net Ecosystem Exchange (NEE) showed an overestimation during the frozen season (higher CO₂emissions) at EML with a mean NEE of 26.98 ± 4.83 gC/m²/month compared to observational mean of 22.01 ± 5.67 gC/m²/month, and during the fall months at IMN, with a modeled mean of 19.21 ± 7.49 gC/m²/month compared to observation mean of 11.9 ± 4.45 gC/m²/month. Our results underscore the importance of representing the impact of soil drainage conditions on the thawing of permafrost soils, particularly poorly drained soils, which will drive the magnitude of carbon released at sites across the high-latitude tundra. These findings can help improve predictions of net carbon releases from thawing permafrost, ultimately contributing to a better understanding of the impact of Arctic warming on the global climate system. 

Abstract. Lakes in the Arctic are important reservoirs of heat withmuch lower albedo in summer and greater absorption of solar radiation thansurrounding tundra vegetation. In the winter, lakes that do not freeze totheir bed have a mean annual bed temperature >0 ∘C inan otherwise frozen landscape. Under climate warming scenarios, we expectArctic lakes to accelerate thawing of underlying permafrost due to warmingwater temperatures in the summer and winter. Previous studies of Arcticlakes have focused on ice cover and thickness, the ice decay process,catchment hydrology, lake water balance, and eddy covariance measurements,but little work has been done in the Arctic to model lake heat balance. Weapplied the LAKE 2.0 model to simulate water temperatures in three Arcticlakes in northern Alaska over several years and tested the sensitivity ofthe model to several perturbations of input meteorological variables(precipitation, shortwave radiation, and air temperature) and several modelparameters (water vertical resolution, sediment vertical resolution, depthof soil column, and temporal resolution). The LAKE 2.0 model is aone-dimensional model that explicitly solves vertical profiles of waterstate variables on a grid. We used a combination of meteorological data fromlocal and remote weather stations, as well as data derived from remotesensing, to drive the model. We validated modeled water temperatures withdata of observed lake water temperatures at several depths over severalyears for each lake. Our validation of the LAKE 2.0 model is a necessarystep toward modeling changes in Arctic lake ice regimes, lake heat balance,and thermal interactions with permafrost. The sensitivity analysis shows usthat lake water temperature is not highly sensitive to small changes in airtemperature or precipitation, while changes in shortwave radiation and largechanges in precipitation produced larger effects. Snow depth and lake icestrongly affect water temperatures during the frozen season, which dominatesthe annual thermal regime of Arctic lakes. These findings suggest thatreductions in lake ice thickness and duration could lead to more heatstorage by lakes and enhanced permafrost degradation.