But wait, there's one subtle feature here that can make or break this monster snow forecast and that is the forecast snow ratio and compaction. First, snow ratio is incredibly complex to measure, or to even have consensus as to how to measure. Before the snow even hits the ground, there are a multitude of factors within and below the cloud that can affect the density of snow flakes. Crystal shapes can change quickly from relatively compact plates to the more classic dendrites just by changing the supersaturation of the cloud ever so slightly. Some research indicates that supersaturation increases when the vertical velocity increases. But supersaturation can also depend on how fast the liquid and gaseous water is being scavenged out by the crystals themselves. That's a feedback loop that can gunk up our initial guess. Then when a crystal falls into warmer saturated air, it can accrete other crystals, grow new ones right from water vapor, or directly intercept liquid cloud droplets. The rate at which these processes happen again depend on the vertical velocity, liquid and vapor content in the cloud and the number of ice crystals competing in the same space for available water. The end result of all these processes is a flake of snow with a certain density. This is a process that cannot be directly observed by operational forecasters.
However, we attempt to make some assumptions about the density of the falling snow flakes as a function various simpler processes and then see what happens to the forecast snow to liquid ratio (a simplistic estimate of falling snow density). The most simple estimate is to just apply a climatological average snow ratio. One is available here created by Dr. Martin Baxter. Let's assume a 12:1 ratio and we get a timeline of snow accumulation (called a plume diagram) for an ensemble member near the mean snow fall. The time now increases right to left and the appropriate axis is labeled in inches in the far right. The blue line below shows the 12:1 ratio and the accumulation peaks just over 20", a respectable snow storm.
But there are other techniques. A maximum temp in profile technique assumes the snow ratio increases as the maximum temperature in a vertical column decreases. The thinking here is that the density of falling snow decreases as the maximum temperature in the warm layer aloft decreases. There may be some merit to that if that warm layer is saturated since the maximum liquid cloud water content available for riming decreases as temperature decreases. Notice here the forecasted snow ratio for max temp in profile slowly increases as the air cools aloft.
Meanwhile there is the Zone omega technique (colloquially called the Cobb 05 technique) where snow density decreases if the strongest ascent occurs in the dendrite production zone (-12 to -18 C). I talked about this a couple years ago before our drought when we had a much colder snow storm. This is a horribly difficult method to verify and this method is completely statistical. The Woodward forecast below also shows the extreme volatility of the snow ratio. The snow fall winds up being pretty high (25-30") because this technique allows for snow ratios exceeding 40:1 if the vertical motion spikes in the dendrite production zone. Many times this technique overestimates the ratios (underestimates falling snow density) based on the experience of forecasters.
Due to the errors, an alternate version of the technique cuts the snow ratios for each temperature down by almost a factor of two. Now the snow fall is around 23", or similar to that of the first two techniques.
What we discussed so far only represents our best attempt at predicting the density of falling snow. What happens after the snow hits the ground before we go to measure it is a completely different matter. Snow begins to compact immediately after the flakes hit the ground and accumulate. Every one of the graphics above initiates a compaction routine based on an time-dependent exponential decay function. That's why the forecast snow accumulations decrease with time. If we removed that function, the purple line shows the snow depth forecast and now you can see values in excess of 35".
However, the exponential decay function is static, and therefore presents an unrealistic display of the processes that affect snow compaction. Perhaps the only realistic component of this is that the compaction continues with time and thus presents an idea of how much snow depth loss (density increase) occurs before someone measures the snow. But the rate of compaction can change according to the wind. The stronger the wind, the more blowing and drifting of snow causes crystal breakup and compaction. A strong wind like what Woodward is expecting today could cause drifts compact enough to support someone walking on them. If so, that kind of density is going to be associated with very small snow ratios, maybe 3 to 4:1! But let's assume a flat, representative surface for measuring snow. If that's the case then there's a nifty neural net (called the Roebber technique) located here that allows you to enter in the QPF (in liquid equivalent) and the expected wind speed. It will estimate the snow ratio for you. I entered in 2" of QPF and a 25 kt wind, certainly reasonable numbers for today. The output snow ratio falls to 9:1. That would yield less than 20". The Roebber technique also accounts for temperature related compaction. Certainly some of that occurred since Woodward was well above freezing yesterday.
All of this of course depends on an accurate QPF. Fortunately Woodward is in an area where the SREF had a high probability of > 2" of QPF and therefore a high confidence of forecasting if this snow will be recordbreaking or not. For those less fortunate areas where the QPF uncertainty is greater, the errors in snow ratio may not matter so much.
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