Snow is extremely important to a wide range of natural processes in Alaska. Snow cover helps regulate the earth’s temperature and stores water on the landscape. As it melts, snow hydrates the soil and replenishes the freshwater supplies of streams and lakes, providing water for vegetation, wildlife, and human activities such as agriculture and electricity generation. Understanding present and future snow conditions under climate change is critical for managing Alaska’s natural resources, yet many scientists, land managers, and policymakers lack this information at useful scales. Hence, the goal of this project was to produce an advanced snow modeling system for part of the Arctic that predicts a variety of factors across space and time, including estimates of snowfall, snow depth, and changes in snow season length. The model was developed with collaborative input from ecologists, biologists, and geophysical scientists to determine which outputs would be most useful. These datasets are presently being used by the Arctic Landscape Conservation Cooperative for continued climate, hydrologic, and ecosystem research.