Improving the Snow-to-Liquid Ratio and Snowfall Forecasts in the Western United States

Accurate and spatially detailed estimation of snow-to-liquid ratio (SLR) is a critical component of snowfall forecasting as it is used to convert the quantitative precipitation forecast (QPF) to snowfall amount. In the continental western United States, snow climates vary significantly from the coast to the interior, necessitating the development of regionally specific SLR algorithms capable of accounting for large SLR variability during individual storms (i.e., from 4:1 to 40:1 or more in rare cases). Given regional variations in the SLR climatology, snowfall forecasts based on overly simplistic SLR estimates or climatologies may yield large errors.

In this study, we investigate relationships between SLR and atmospheric conditions using high-quality manual snowfall observations collected by snow-safety personnel and other groups at several high-elevation sites in the continental western United States. These relationships are then applied to high-resolution and downscaled ensemble forecast system output to produce high-resolution probabilistic SLR and snowfall forecasts.

In addition to developing these regional relationships, point-specific relationships may be developed for nearly any site with a snowfall and liquid equivalent record of sufficient length and quality. We anticipate these statistical techniques for determining SLR will be a valuable addition to an operational forecaster’s toolbox and enhance the quality of snowfall forecasts especially in regions of complex terrain in the western United States and beyond.