Have you ever seen it snow when the temperature is above freezing?

Well, we just saw that happen Sunday evening along the Front Range of Colorado, and new research from the University of Colorado shows that Colorado gets some of the warmest temperature snow on the planet.

“We’re getting snowfall at temperatures easily approaching 40 degrees Fahrenheit,” said Keith Jennings, a graduate researcher in CU Boulder’s Institute of Arctic and Alpine Research (INSTAAR) and the lead author of the study.

Jennings and his team created a map of the Northern Hemisphere showing how location and humidity can affect precipitation, illustrating wide variability in how and why different areas receive snow or rain.

“One of the big surprises was that zero degrees Celsius or 32 Fahrenheit was not a very good predictor at all of the rain-snow transition temperature, and actually that transition almost always occurs at a much warmer temperature: 1 degree Celsius, as high as almost 4 degrees Celsius depending on where you are,” said Ben Livneh, an assistant professor in CU Boulder’s Department of Civil, Environmental and Architectural Engineering and a co-author of the study.

For snow to form naturally in a cloud, the temperature must be 32 degrees Fahrenheit or lower, but the atmospheric conditions can vary greatly as that snow falls to the ground. The key for that snowflake remaining a snowflake is very low relative humidity.

“You’re giving the snowflake more of an opportunity to cool itself as it falls through the atmosphere, like on a warm day you’re body sweats to cool itself, and it’s more efficient if you’re in a drier place like Colorado,” Jennings said.

It's a process called evaporative cooling. Ski area's use this knowledge to create snow early in the season when the air temperature is above freezing, but the relative humidity is still very low.

"We've sort of synthesized the state of the science in a way that extends what the ski areas have kind of known for a long time, and we've kind of brought it to the scientific community," said Livneh.

He said it also works the other way around. That very moist air can physically melt flakes even if the air temperature is favorable for snow.

“Those flakes will interact with the atmosphere around them a lot more intensively, and will therefore melt, and become rain," Livneh said, who is also a fellow with the Cooperative Institute for Research in Environmental Sciences (CIRES).

This team of researchers, which also included Noah Molotch, Director of the Center for Water Earth Science & Technology (CWEST), and graduate researcher Taylor Winchell, used nearly 18 million precipitation, temperature, and humidity observations spanning over 100 countries and four continents across the Northern Hemisphere.

The dataset was created by the Environmental Centers for Prediction (NCEP) and is hosted by the National Center for Atmospheric Research (NCAR).

"That really takes you into the realm of big data, where you're using advanced techniques to analyze it, and quality control it," Jennings said.

These researchers said they hope to improve land surface models with their work. Those are the key components for the computer forecast models used by other researchers, hydrologists, and water managers, to run computer simulations of climate forecasts, and general atmospheric circulations.

They say many of those models will often use a baseline of 32 degrees Fahrenheit to distinguish between when rain will become snow. This group is already working with administrators to get their data implemented into those models.

"You can just change a line or two of code to incorporate the humidity information that is already being used to force the model, and then you can have this more advanced, more accurate way of discriminating between the different precipitation phase types," said Jennings.

This research could also be important as we try to figure out what is going to happen to our water resources in a warming future. Something these scientists look at often.

“One of the most concerning parts of global warming, is the areas that we are most uncertain of, so the areas that have the least amount of predictive capacity, are the same areas that are actually quite important to water resources, like the intermountain west, and the Sierra Nevada in the United States,” said Jennings.

Here is a link to the full research paper published today in the journal Nature Communications.