Not long ago, Rush Limbaugh once again confirmed his idiocy to the world when he referred to National Hurricane Center meteorologists as “weather dolts.” I wanted to scream until red in the face at his comment, but being a Ph.D. candidate in meteorology meant that people would assume a bias. Plus, every time Rush Limbaugh’s name is mentioned, a cute chinchilla gets kicked in the shin.1
With apt timing, the ever awesome Nate Silver came to the rescue:
Why are weather forecasters succeeding when other predictors fail? It’s because long ago they came to accept the imperfections in their knowledge. That helped them understand that even the most sophisticated computers, combing through seemingly limitless data, are painfully ill equipped to predict something as dynamic as weather all by themselves. So as fields like economics began relying more on Big Data, meteorologists recognized that data on its own isn’t enough.
It’s a long piece, but Silver does a great job of conveying the realities and uncertainties associated with weather forecasting.
I study methods to model turbulence in the lowest portion of the atmosphere, so forecasting isn’t something I directly deal with. However, I personally know many who do forecast and they are good - damn good. So, I urge to you to read Silver’s article and make Rodney Dangerfield happy by giving forecasters a little respect.
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Two chinchillas were thereby harmed by the writing of this post. My apologies. ↩︎