Reply on AC2

Abstract

Lakes in the Arctic are important reservoirs of heat with much lower albedo in summer and larger absorption of solar radiation than surrounding tundra vegetation. In the winter, lakes that do not freeze to their bed have a mean annual bed temperature > 0 °C in an otherwise frozen landscape. Under climate warming scenarios, we expect Arctic lakes to accelerate thawing underlying permafrost due to warming waters in the summer and in the winter. Previous studies of Arctic lakes 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. We applied the LAKE 2.0 model to simulate water temperatures in three Arctic lakes in Northern Alaska over several years and tested the sensitivity of the model to several perturbations of input meteorological variables (precipitation, shortwave radiation, and air temperature). The LAKE model is a one-dimensional model that explicitly solves vertical profiles of water state variables on a grid. We used a combination of meteorological data from local and remote weather stations, as well as data derived from remote sensing, to drive the model. We validated modelled water temperatures with data of observed lake temperatures at several depths. Our validation of the LAKE model completes a necessary step toward modelling changes in Arctic lake ice regimes, lake heat balance, and thermal interactions with permafrost. The sensitivity analysis shows us that the LAKE model is not highly sensitive to the weather data perturbations used in this study. Our results show that snow depth and lake ice strongly affect water temperatures during the frozen season which dominates the annual thermal regime. These findings suggest that reductions in lake ice thickness and duration could lead to more heat storage by lakes and enhanced permafrost degradation.