In this talk, we will discuss some initial steps that will lead to pan-Arctic hydrological simulations. We first introduce the Kuparuk River Basin (KRB) of Alaska (the focal point of our research) and describe the Catchment-based Land Surface Model (CLSM). Then we investigate some of the forcing datasets available to us to force the CLSM in this Arctic watershed. A comparison between the observational and reanalysis (ERA15) datasets shows that the ERA15 meteorological conditions are generally consistent with observations. Some notable differences do emerge, however, such as the well-documented cold temperature bias in the ERA15. We then demonstrate how different forcing datasets lead to significant variations in the modeled water budgets of the KRB.

In the second half of the talk, we describe a methodology for the inclusion of subgrid-scale spatial variation of snowcover within the CLSM. The inclusion of varying snow depths into two bins (shallow and deep snowpacks) within the model is sufficient to produce a dramatic improvement in the timing and magnitude of the simulated spring melt. By carefully selecting a forcing dataset and including some additional physical processes within our modeling framework, we will be able to conduct longterm diagnostic studies with precise day-to-day variations in the hydrology of the pan-Arctic.