But, if you live in the midwest, you know--we've heard this before. Predictions of over half a foot of snow that don't materialize or completely missing a huge snowfall until it's too late. Now, taking a look at model forecasts aloft over the next few days, it doesn't look very impressive. Here's what this morning's GFS run shows at 500 mb on Friday evening:
|Fig 1 -- 36 hour GFS forecast of 500 mb geopotential heights and winds for 00Z, Sat. Dec. 4, 2010. From the HOOT website.|
In another blog post I talked about using critical thickness values to help determine where snow would fall. Here's a view of the GFS forecast for most of the major critical thickness lines for Friday evening:
|Fig 2 -- 36 hour GFS forecast of critical thickness lines for various heights (exact parameters not shown) for 00Z, Sat. Dec. 4, 2010.|
|Fig 3 -- 36 hour GFS forecast of surface temperature (shaded), sea-level pressure (contoured) and winds for 00Z, Sat. Dec. 4, 2010. From the HOOT website.|
Now that's just one model. We're close enough to this event that we can look at medium-range models as well. Let's look at the NAM forecast for this same time. Here's the 500 mb chart:
|Fig 4 -- 36 hour forecast of 500 mb geopotential height and winds for 00Z, Sat. Dec 4, 2010. From the HOOT website.|
We could look at more model graphics for both of these models and try to reconcile them with each other. But we know that both models have their flaws and we could agonize for hours trying to answer a simple question--is it going to snow or not? What if we could somehow look at lots of models with their slightly different solutions all at the same time to see if we can make any general conclusions about where the models do agree? But wait--we can do this! Through the use of model ensembles.
The basic idea is this. We know that the GFS, NAM or any other model is flawed in many ways. There's also errors in the data we used to initialize the model in the first place. But generally, the models do capture the general flow of things quite well. So what if we ran the same model several different times, using slightly different initial conditions each time, and then seeing how many of those model runs agreed on some particular parameter? People are doing this in research groups across the country. For example, NCEP runs a GFS ensemble at the same time as the operational GFS model (the one we always look at). They run 20 GFS models all with slightly different initial conditions. As a result, we can get plots like this:
|Fig 5 -- GFS ensemble 500 mb geopotential height enemble mean and normalized ensemble spread for a 36 hour forecast valid 00Z, Sat. Dec. 2, 2010. From the NCEP EMC website.|
However, we can do this sort of analysis for any parameter we want. So what question were we asking? Are we going to get snow from Friday into Saturday in the upper midwest?
|Fig 6 -- GFS ensemble probability of precipitation exceeding 0.1, 0.25, 0.5 and 1.0 inch in a 24-hour period between 12Z Dec 3, 2010 and 12Z, Dec 4, 2010. From the ensemble initialized at 00Z, Dec 2, 2010. From the NCEP EMC website.|
We can see in the image above that for much of that swath from Minnesota through northern Illinois, there is at least a 70% (if not higher) probability of at least 0.1 inches of liquid equivalent precipitation from Friday morning through Saturday morning. There's even a good-sized area of greater than 60% chance of at least 0.25 inches of liquid equivalent precipitation in that are as well. So even though the GFS doesn't have that great of a hold on this system, the majority of the models show that precipitation will fall in that area.
There are other ensembles we can look at too. For instance, the Storm Prediction Center runs what's called the SREF -- Short Range Ensemble Forecast system. It's basically an ensemble of WRF models that are analyzed in the same way as the GFS ensemble. So what do they say about precipitation?
|Fig 7 -- SREF probability of 24-hour liquid equivalent precipitation greater than 0.1 inch ending at 12Z, Sat. Nov 4, 2010.|
|Fig 8 -- SREF probability of 24-hour liquid equivalent precipitation greater than 0.25 inch ending at 12Z, Sat. Nov 4, 2010.|
|Fig 9 -- SREF probability of 24-hour liquid equivalent precipitation greater than 0.5 inch ending at 12Z, Sat. Nov 4, 2010.|
So what does this all mean? Even though we looked at two different model environments (GFS and WRF) (the NAM model is actually a WRF model now, so it enhances our comparison even further...) that had low confidence and differences in the upper air patterns and surface low placement and all that, surprisingly they all agree to a decently high probability that much of that geographical swath will see a good amount of liquid equivalent precipitation. Not bad for pulling something conclusive out of inconclusive models...
Still...how much snow does this mean? I am going to write a blog post soon where I look at different methods of calculating snow amounts from liquid equivalences. For now, a general rule of thumb often used is the 10:1 snow ration--10 inches of snow for every 1 inch of liquid water equivalent. Applying that to what we saw above, our 0.25-0.5 inch range of liquid equivalent would translate to 2.5-5 inches of snow.
I didn't really stop here (beyond the quick check of critical thickness) to look at if this precipitation would all fall as snow--remember, there was that concern that the critical thickness lines could come north if the jet stream stayed further north. Based on my quick look through the models (more than I showed here), they actually all seem to be keeping the low to the south and keeping that precipitation swath well in the colder air.
So, in conclusion, I see where the NWS snow forecasts are coming from based on the power of model ensembles. Ensembles hold great promise for the future of weather prediction--I'm sure I'll be writing more about them in the time to come.
As many people have pointed out to me over the last hour or so, the SREF page has a whole section of ensemble products devoted to probabilities of winter weather. As such, we can see far more detailed predictions instead of just the liquid equivalent. I used the liquid equivalent because that was available in both the SREF and the GFS ensemble and so I could compare them. But, by popular demand, here are three SREF snowfall predictions:
|Fig 9 -- SREF most probable precipitation type for 12Z, Sat. Dec 4, 2010. 45 hour forecast.|
|Fig 9 -- SREF probability of snowfall for 12Z, Sat. Dec 4, 2010. 45 hour forecast.|
|Fig 9 -- SREF previous 12 hour snow accumulation for 12Z, Sat. Dec 4, 2010. 45 hour forecast.|