I'd like to share a few updates that we've made to products on weather.utah.edu since last winter.
The Little Cottonwood forecast guidance derived from the HRRR (https://www.inscc.utah.edu/~steenburgh/ml/hrrrlccforecast.html) and GFS (https://www.inscc.utah.edu/~steenburgh/ml/gfslccforecast.html) has been updated with retrained machine learning algorithms that include last season in the training dataset. An example from the GFS is below.
We also added a temperature forecast for the Collins (9662 ft) observing site, which is a bit more representative of mid-mountain conditions than Mt. Baldy, which is still included as it is useful for ridge-top temperatures.
The new snow-to-liquid ratio (SLR) algorithm is based on a technique known as a random forest trained with observations from Alta-Collins. It is more accurate and should produce a somewhat wider range of SLRs (up to about 25:1 if conditions are right) than the technique we used last year. We thank Alta Ski Patrol and Alta Ski Area for continuing to provide access to weather observations and snow measurements so that we can produce products like this.
We also updated the SLR algorithm used in our experimental HRRR snowfall products, and example of which is below.