Using an idealized experiment where atmospheric carbon dioxide doubles from its 1990 value over 70 years, a new Geophysical Fluid Dynamics Laboratory (GFDL) high-resolution climate model, CM2.5, predicts an increase in snowfall for the Earth’s polar regions and highest mountains, but an overall drop in snowfall for the globe. A recent study currently in press and available online in the Journal of Climate, led by Cooperative Institute for Climate Science – Princeton (CICS-P) Scientist Sarah Kapnick and coauthored with Thomas Delworth, a senior physical scientist at GFDL and Princeton lecturer; found that CM2.5 better captures various snow variables when compared to previous models.
CM2.5 is unique in that its resolution allows it to capture complex mountain ranges. This makes a difference in places like the western U.S. where a single plateau in coarse models is transformed into several distinct mountain ranges in CM2.5 (e.g. California Sierras, Cascades, and Rockies). This is important for having snow fall in the correct regions and collect as snowpack (seasonal snow on the ground).
Over the United States, the future climate experiment exhibits significant reductions in average annual snowfall. Figure 1 represents the geographic distribution of snowfall change in response to CO2 doubling. The vast majority of the U.S. experiences snowfall loss, with the greatest percentages occurring in the south, along the eastern coast, and the Pacific Northwest. This will lead to fundamental changes in the availability of water from spring and summer snowmelt. The continental interior experiences fewer reductions. While this study focuses on mean annual snow variables, future work will focus on exploring changes in extreme snowfall events, such as the frequency and strength of blizzards, and changes in seasonality. This work relates to the National Oceanic and Atmospheric’s (NOAA) Climate Goal: Understand Climate Variability and Change to Enhance Society’s Ability to Plan and Respond.
Contact Information: Sarah Kapnick at (609) 452-6548 or email@example.com