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.

了解未来暴风雪的变化方式对于估计对水资源和依赖其的地球以及社会经济系统的影响至关重要。在这里，我们使用暴风雪作为标记来评估气候变化的中尺度指纹，从而描述了在高人为排放途径下北美中部和东部冬季天气事件发生的潜在变化，特征和变异性。暴风雪使用动态缩小的模拟的高分辨率雪水当量输出进行分段和跟踪，与全球气候模型不同，暴雪可以解析重要的中尺度特征，例如带状积雪。在伪全球变暖模拟中，发现暴风雪的频率和大小显着减少，包括那些产生最大降雪量的事件。寒冬的早期和晚期在暴风雪和雪水当量累积中显示出特别强劲的比例下降。