Understanding how snowstorms may change in the future is critical for estimating impacts on water resources and the Earth and socioeconomic systems that depend on them. Here we use snowstorms as a marker to assess the mesoscale fingerprint of climate change, providing a description of potential changes in winter weather event occurrence, character and variability in central and eastern North America under a high anthropogenic emissions pathway. Snowstorms are segmented and tracked using high-resolution, snow water equivalent output from dynamically downscaled simulations which, unlike global climate models, can resolve important mesoscale features such as banded snow. Significant decreases are found in the frequency and size of snowstorms in a pseudo-global warming simulation, including those events that produce the most extreme snowfall accumulations. Early and late boreal winter months show particularly robust proportional decreases in snowstorms and snow water equivalent accumulations.