I was in the grocery store earlier today – you know, getting the bread and milk – and I overheard the same type of conversation that I always hear after it snows: “It must be nice to be a weatherman where you can be wrong all the time and still have a job.”
In all fairness, snowfall is really hard to predict. And here’s why.
For one, nobody really pays attention to total snowfall. It’s what sticks on the ground that we measure and base our criticism on. There are times when it could snow 3″ but only 1″ accumulates, and we then think the weatherman was wrong.
Surface temperature plays a big role. If the surface temperature is below freezing, the snow will most likely stick. If the surface temperature is 33-36 degrees, it will mainly melt – unless it snows really fast. Then it’s possible the melting won’t keep up with the snowfall. So, here, the meteorologists are forced to (in additional to predicting snowfall amount) to predict the surface temperature and how fast the snow will fall.
But it’s not just the temperature of the surface the plays a role, the ground temperature is a factor in the melting also.
Deciding if the precipitation is going to be rain or snow can be rather difficult for the weatherman. You may assume that just because it’s 10 degrees outside, the precipitation would obviously be snow. But that’s not the case. Here, you have to look at the temperature of the bottom 10,000′ of the atmosphere. Meteorologists tend to look at the distance between two pressure levels (called the thickness) to decide on precipitation type. Usually the best indicator is what they call the thickness. You can think of it as the average temperature of the layer between two pressure levels. If the thickness is below 1300 meters, then snow is possible.
Weather is also constantly changing. A lot can happen (change) in a day’s time. Some of this has do to inherent limitations. Models are run using current atmospheric conditions, gathered by sampling efforts like weather balloons launched from NWS offices to see what’s happening in the atmosphere at a certain time. But those sampling efforts don’t cover the whole planet, and the Earth’s atmosphere is a large, interacting system — what’s happening on the West Coast today will affect the East Coast a few days later, for example.
If we could sample the entire globe perfectly, we’d have a perfect forecast. But meteorologists can’t do that, so they’re left with the imperfect simulations they can get.
Snow to rain ratio. This is a huge factor that many people are not aware of. Generally speaking, about 10″ of snow equals 1″ of rain. So there’s a lot more room for error with snow. If the weatherman predicts 1″ of rain for tomorrow, and it rains 0.6″, you’re probably not going to be criticizing them at the grocery store, or even be aware of the slight inaccuracy. But it’s no different than the weatherman predicting 10″ of snow and we only get 6″. You’re going to notice that, and you may question the local meteorologist’s ability to predict weather. Or, maybe even more noticeably, if they predict 5″ of snow and it only snows 1″. You went to the store and bought all that bread and milk in preparation of being snowed in for a day or 2, and then it hardly snows and you’re irritated by the false prediction. You might say something like, “I bet the meteorologists are working together with the grocery stores just to scare us.” But it’s no different than predicting half an inch of rain and only get 1/10 of an inch – something you may not even notice.
With all of this in mind, I think that our local weathermen and weatherwomen do a great job of forecasting the weather for us here in Central Indiana. The fact that they know it’s going to snow – let alone how much it’s going to snow – a week in advance is pretty impressive to me.