People who live in areas where it snows may be aware at just how terrible snow forecasts tend to be. That's because snow is especially difficult to predict.
Photo by revec.
Weather is notoriously hard to predict as it is, and even the terminology can be a bit baffling to understand. In the case of snow, forecasters are tasked not only with predicting when it will snow and for how long, but also how much of that snow will accumulate on the ground. All these factors make it hard to get snow totals right.
Let's start at the beginning then. The BBC points out one of the big reasons behind whether it will snow or rain can be hard to predict in certain regions:
Snow is more likely in higher areas as the temperature is cooler, meaning rain may fall as snow in mountainous areas giving the dusting of snow on peaks which is commonly seen at this time of year.
Equally, snow is less likely to fall in urban areas because of the warmer surroundings. In central London it will rain sometimes, while a relatively short way away just outside the M25 there is heavy snow.
"It only takes a tenth of a degree for it to be either rain or snow..."
The difference between what becomes rain and snow can be small, and atmospheric moisture and surface temperature all play a part in what happens.
We're generally pretty good at predicting if precipitation will fall, but what form it will come in and where is often a little trickier. The vertical structure of temperatures in the atmosphere make is so precipitation can eventually hit the ground as snow, sleet, freezing rain or just regular old rain. There's a lot of variability there, and that skews how much snow falls, where it falls, and how much accumulates.
That all gets even more confusing when you factor in regional climate zones that can wreck havoc on predictions. The Washington Post uses Washington, DC, as an example here:
To make forecasting even more difficult, Washington is between two regional climate zones: the Atlantic Ocean and Gulf Stream to the east, and the Blue Ridge and Appalachian mountains to the west. This creates a special transition zone, with warm air on one side and cold air on the other.
The elevation change between the low-lying areas east of Washington and the high elevations to the west also plays a critical role in snowfall forecasts. It is more likely to snow in higher elevations simply because it is colder. Sometimes, just this slight deviation in temperature can make or break a forecast.
A lot of major US cities are surrounded by oddball regional climate zones that make it difficult to predict weather, like Denver's Rocky Mountains or Seattle's Puget Sound.
Using the example of the March storm in the US Northeast, the "inaccuracy" all came down to where the storm landed. Speaking with the Wall Street Journal, meteorologist Patrick Burke points out that snow accumulation is already a tricky beast because temperatures have to be exact, and any variation can cause drastic shifts in accumulation totals.
The line of a storm can change throughout the day, so a forecast at 6AM isn't the same as one at 11PM. In the case of the US Northeast storm, the storm drifted a bit north and west, causing it to hit harder 80km north of New York City. Which is to say, the storm still dumped a lot of snow, the meteorologists just missed their mark a little.
Generally, we can't expect pinpoint accuracy with snow. A storm might miss a major city but dump loads in the mountains nearby, or the warmer air from a nearby climate zone might quickly turn that snow into rainy-slush. Lots of factors can change what happens, but it's still always probably best to the prepare for the worst.
I'd also like to toss in one personal theory about why we talk so much about snow forecasts: You can go out and measure snow accumulation with a ruler. That means that suddenly everyone is an expert on snowfall. Most of us aren't collecting rainfall, or measuring exactly how much of the Sun is visible on a given day, so we don't really have a bearing on how accurate these things tend to be.