Winter snowpack provides critical water resources for human populations and ecosystems throughout western North America. Increasing temperature and changing precipitation patterns are expected to alter the extent, amount, and persistence of snow in this region.
Observations of snowpack and related hydroclimate variables are limited and sparse. This project will capitalize on recent advances in water balance and snow modeling as well as the development of comprehensive North American tree-ring datasets to produce spatially specific, annually resolved, and management relevant reconstructions of snow, streamflow, and warm season temperature. The project researchers will focus specifically on spatiotemporal reconstructions of western North American snowpack over the last millennium, in order to provide a long-term perspective on water resources and climate variability in the region. They will use networks of temperature-, moisture-, and snow-limited tree-ring chronologies in combination with water balance modeling to develop spatially explicit reconstructions of snowpack and related hydroclimate variables. They will evaluate these reconstructions for their connection to large-scale climate forcing and modes of ocean-atmosphere variability, provide full characterization of the range of natural variability, and place recent observations in a long-term context. The team will work directly with stakeholders and water managers to formulate priority research questions for the water management community and datasets tailored for direct application or comparison against climate-model based future scenarios generated for climate impact assessments.
