Snow is currently short of scant in the Wasatch with 6" being reported by the Collins automated sensor and spotty coverage on high-north aspects.
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| Alta Ski Area cam image from 8:40 AM MDT 31 Oct 2025. Source: Alta Ski Area. |
While there's no skiing, it does look like a splendid Halloween and weekend for late fall, so enjoy.
Given that we are playing the waiting game for snow, I thought I would share a few thoughts on using long-range forecast guidance.
The National Weather Service Global Forecast System (GFS) produces forecasts at ~13 km grid spacing out to 16 days. The European Center for Medium Range Weather Forecasting similarly produces a "control" forecast at ~9 km grid spacing out to 15 days with their Integrated Forecast System. For simplicity I will call this the ECMWF control, although you may know it as the Euro, EC, ECMWF, or HRES. Plots from these modeling systems are readily available on
weather.utah.edu and other sites. However, when you are looking many days out, there is little point in relying on forecasts from the GFS or ECMWF "control" when a large ensemble is available. Here's why.
In the case of models run by the ECMWF, the ECMWF control is simply the so-called "unperturbed control member" of their 51 member ECMWF medium-range Ensemble Prediction System or ENS. This means that the initial conditions for the ECMWF control represent the "best guess" as to what the atmosphere looks like when the model run is started. The other 50 members are run with the exact same model, but with perturbed initial conditions. Differences in the forecasts arise from these slightly different initial conditions, as well as the perturbations that are added to the model physics to account for uncertainties in how we simulate physical processes such the generation of clouds and precipitation. The latter is referred to as "stochastic" (or random) physics. We don't know for example exactly what the characteristics of cloud droplets are in a cloud, so we use stochastic physics to try and account for the range of possibilities. Together, the differing initial conditions and stochastic physics lead to differing forecasts, with the spread growing with time.
It turns out that the ECMWF control slightly outperforms the other members of the ENS at short lead times. However, at longer lead times, the advantage becomes small and in a statistical sense it has very little advantage over the other ensemble members. So, when you are looking 5+ days into the future, there's little point in relying on the ECMWF control. Each member of the ENS is equally likely, just as when you roll a die, any of the six faces is equally likely to end up on top. The ENS die just has a lot more faces.
The National Weather Service Global Ensemble Modeling System or GEFS has 31 members. The GFS is NOT a GEFS member. The GFS and GEFS use the same modeling system, but the GFS is run at higher resolution (~13 km) than the GEFS members (~25 km), including the GEFS control run. Despite this resolution advantage, the gap between the GFS and the individual GEFS members closes with lead time.
The Utah Snow Ensemble attempts to squeeze as much as we can from the 51 ENS members and 31 GEFS members through the use of downscaling and other techniques. We are trying to take advantage of all of those runs to provide information as to the likelihood of precipitation and snowfall amounts at high resolution. Rather than relying on the GFS or ECMWF control, I think of all members of the ensemble as equally likely. Additionally, over many events, the GEFS or ENS mean is going to outperform the individual forecasts from the GFS or ECMWF control. There's strength in numbers.
Let's use last night's forecast as an example. The GFS is bringing in a pretty healthy system for next Thursday. Below is the forecast valid 1500 UTC (0800 MDT) Thursday 6 November.
If we pull out the forecast for Alta-Collins, the GFS puts out about 1.3" of water through 1200 UTC (0500 MDT) Friday 7 November. Bank on it?
Well if we look at the Utah Snow Ensemble, a different picture emerges. The GFS is actually an outlier compared to all of the forecasts produced by the GEFS and ENS (note that the Utah Snow Ensemble goes to 10 days instead of 7 like the GFS forecast above). Through 1200 UTC 7 November, only 4 out of 31 GEFS forecasts produce > 1" of water equivalent. The wettest ENS member is around 0.6".
The GFS could verify, but it's a lower probability outcome than inferred from the full GEFS and ENS ensembles.
We provide tables for Alta-Collins precipitation and snowfall at
https://weather.utah.edu/text/ensgefsdslccforecast.html. It takes a bit of time to get used to these, but I'll focus solely on the total water equivalent precipitation table below (right click and open in another window to enlarge). I've highlighted in red the total accumulated precipitation through 6 AM MDT Friday 7 November (we have a bug for dealing with daylight time so that's going to be 5 AM local time). The rows include the minimum from the ensemble on the top and maximum on the bottom. P10 indicates the so called tenth percentile. 10% of the forecasts are at or below this value. P50 is the fiftieth percentile or median. Half of the forecasts are below this value and half are above. In this case P50 is 0.17", so half the ensemble members are at or below 0.17". Much lower than the GFS.
The GFS's 1.3" sits somewhere between the P75 value and the P90 value. Those are the seventyfifth and ninetieth percentiles. Let's guesstimate it to be at about P85, which means 85% of the ensemble members are below the GFS amount and 15% are above.
So, the GFS could verify, but a look at all of the forecasts suggests that's a lower probability outcome. The full Utah Ensemble suggests the "over under" through Friday morning is not the GFS's 1.3" but more like 0.16" (the P50 value).
The discussion above assumes the Utah Snow Ensemble is unbiased. In other words, on average, it produces about the same amount of precipitation at Colins as is observed and that it's probabilities, evaluated over many events, reflect real world probabilities (i.e, when the Utah Snow Ensemble says there's a 10% chance of 1" or more of precipitation it actually happens 10% of the time). I don't actually know if this is the case. The GEFS and ENS underpredict precipitation at most mountain sites. Our downscaling helps with this, but undoubtably biases remain, vary by site, and in some cases could be high rather than low biases. I haven't had time to look into this, so I'm going to leave this for your, the student, to investigate.