Why are Winter Forecasts so Difficult?

The minute someone mentions snow in the forecast everyone goes crazy. Comments range from being excited to yeah right, these guys are never right. Forecasts can go awry from snow to just rain, or from snow to ice, or from ice to rain, etc. Forecasting these transitional zones is more of an artform and luck than pure skill. The reason is simply that we don’t have the ability to measure the atmosphere everywhere we need to so that the computer models get an accurate representation of initial conditions.
Use the above chart for example to give you an idea on how many different factors one must take into account to predict the type of wintry precipitation. Any one of these is off, and the forecast changes dramatically. Balloon soundings are launched from various NWS offices across the US, but they are typically hundreds of miles away from each other. A lot of weather happens between these points that isn’t captured. So the model is blind in this style of a course grid. It has to infer that things are similar between point A and point B, when in reality they may be very different.

One of the notorious issues we have here in Oklahoma is the warm nose layer. This layer typically resides around 800 to 850 mb. It is a region of warm air that is often underestimated by the models. One of their known weaknesses. If too much warm air is present or moves in unannounced, then the precipitation that falls melts to pure liquid. That’s bad news for snow lovers, but could be great news for ice lovers, assuming the temperature near ground level is below 32 degrees. The tricky part from there is how cold it is at the surface. Typically it needs to be between 27 to 29 to cause roadways to freeze up since the colder values overtake the warm ground temps from radiating upwards as well as any solar radiation. Take away the solar element, ie nightfall, and it’s even easier to freeze.
So during the next winter event, just keep in mind that many times this warm layer messes things up, even at the last minute. Models will never be able to resolve these issues until our course grid turns into a fine grid in tracking atmospheric variables.