S32 The Changes of North America Mean and Extreme Snowfall Observed Since 1950 and Their Future Projection Under a 1.5ºC Global Warming Scenario

Sunday, 7 January 2018
Exhibit Hall 5 (ACC) (Austin, Texas)
Benjamin O. Johnson, Texas A&M Univ., College Station, TX; and Y. Xu

Extreme snowfall events can devastate local economies. The goal of this research is to quantify the trend in mean and extreme snowfall over North America using a gridded dataset of historical snowfall (1950-2009; Kluver et al., 2016) aggregated from long-term ground station records. We find that mean snowfall, although decreasing in much of the Southern States due to regional warming, has surprisingly increased slightly over the Northern Plains and Southwest Plains, downwind of the Great Lakes by as much as 10% per decade, and even more significantly over much of Northern Canada and Alaska. Through various statistical methods such as Generalized Extreme Values theory, we find consistent trends exist for extreme daily snowfall events in many regions, yet noticeable differences in others such as the Northeast US, which shows an increase in heavy snowfall event (e.g. maximum daily snowfall in a year), despite a slight decrease in mean snowfall. Annual mean time series of snowfall metrics were correlated to various climate variables, such as local temperature and the Multi-variable ENSO Index (MEI). It was found that local winter temperatures, and the associated increase in atmospheric moisture-holding potential, can explain the long-term increase in snowfall over high-latitude regions and high-altitude mountains, where climatological temperatures are sufficiently cold. We also found that shorter-term variability, such as ENSO, plays a significant role in mean and extreme snowfall over continental US, with El Nino years leading to greater total snowfall in much the Southern States, and a higher frequency for snowstorms in the Northeast US, corresponding to cooler and moister than normal conditions during El Nino years. The analysis is further expanded using historical and future simulation of daily snowfall data from a climate model to understand changes in observed atmospheric conditions, and to improve the projection of mean and extreme snowfall changes in a warmer world.
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