Scientists from the University of Utah, US, have developed an easier way for meteorologists to predict snowfall amounts and density.
Based on a study of 457 winter storms during eight years at 9,644 feet in the Wasatch Range at Utah’s Alta Ski Area, the researchers determined that forecasters could predict snowfall density - known as snow-to-liquid ratio (SLR) - most accurately using only two variables: temperatures and wind speeds at mountain crest level.
“We’ve developed a formula that predicts the water content of snow as a function of temperature and wind speed,” said the study’s senior author, Jim Steenburgh, professor and chair of atmospheric sciences at the University of Utah.
“This is about improving snowfall amount forecasts - how much snow is going to fall,” said Steenburgh. “As a nice side benefit for the ski community, this will tell you whether you’re going to get powder or concrete when it snows. We are working on incorporating this into the UtahSkiWeather.com website run by the university,” he added.
The new method “is also helpful to avalanche forecasters,” said the study’s first author, Trevor Alcott, a doctoral student in atmospheric sciences. “We’re forecasting snow density, which is related to the stability of freshly fallen snow,” he added.
“Forecasters really like it because it gives us a more realistic depiction of how snow density will vary across the Wasatch Range and with elevation,” he said. “Instead of anticipating a singular density of snow or fluffiness of the snow over the Wasatch, Trevor’s and Jim’s tool has allowed us to have different snowfall densities in our forecasts for different areas based on forecasts of (crest-level) temperature and wind,” he added.
“We’ve always had some insight into the difference between a real powder day versus a really wet snowfall event,” said Randy Graham, the science operations officer.
“What this tool has enabled us to do is to better differentiate how dense the snow is going to be over an area with really complex terrain,” he added.
