1. Uncertainty isn't actionable. A statement like, "There's an 85% chance of snow with accumulation of 1–24" with peak probabilities of 28% and 17% at 2" and 18", respectively" is nonsense to most people. And moreover, it doesn't mean anything to me. Are we going to get snow that will affect my morning commute? Are we going to get so much snow that I need to take emergency action? A probability distribution doesn't answer those questions, even if that's the best that exists.
2. Weather is news. The cable news channels were dominated by snow predictions yesterday, and the Weather Channel exists as an "entertainment" venue, not a source of scientific information. If it doesn't fit into a soundbite, the public can't absorb it. And "Weather is hard to predict" doesn't garner viewership.
3. Prepare for the worst. While small changes in the environment can lead to large variability in snow accumulation, the fact of the matter is that there was a not-unlikely chance (according to the models) that NYC, Boston, and other cities could have seen crippling snowfall. They were able to prepare for that eventuality. That it didn't come to pass is almost a non-issue. Can you imagine the outcry—not to mention the impact—if the situation was reversed (i.e., surprise 3' of snow)? Fairfax County Public Schools outside of DC got slammed in the media for not closing a few weeks back.
The real question is: at what point of probability do you prepare for a potential outcome, and are you prepared to back that up (either way)? Do we prepare for record snowfall on 80% likelihood? 50%? 10%? (And as a broader point of discussion, this same calculation applies to other areas: TSA spend vs. terrorism; flood insurance cost vs. coverage; etc.)