Hourly and daily models of active layer evolution in arctic soils

For models to predict arctic ecosystems' responses to climate change, it is important to first predict soil thermal responses. However, soil heat-budget models are generally too finely scaled and detailed to couple with large-scale biogeochemical models. Appropriate data sets to derive simple models capable of predicting active soil layer behavior on a time scale appropriate to biogeochemical models do not exist. One solution is to scale a highly detailed, physical heat model. The fine-scale predictions of this model can be aggregated to generate coarse-scale data, which can be used to derive an appropriately scaled model. We develop an hourly, spatially detailed model of soil temperature based on well-understood physical and biological processes and driven by detailed data. Under a range of environmental conditions, the hourly model predicts active layer behavior. From these predictions we construct a daily model that requires far fewer data about the climatic, environmental, and physical conditions to predict the volume of thawed soil over longer time scales.