8 Quick Common Misconceptions About Forecasters and Meteorologists

Imagine you’re planning a camping trip with your family. Everyone wants to do it this weekend, but just to make sure there won’t be any surprises, you check with your local forecaster. A quick Google search, a brief visit to his or her website, and you’re all clear for Saturday. Great! You let everyone know and that’s that.

On Friday night, you double check the weather forecast. On Saturday morning, you triple check the weather forecast. Again, the forecaster says today will be bright and beautiful with very, very little chance of rain.

“Honey, let’s go!” Everyone gets in the car and off y’all go. You reach the campsite, but then it starts to rain cats and dogs.

“Why! Why!” You shout out to the heavens. “F*** you, local weather forecaster!”

Well, my friend, the answer to your question is quite simple. Your misery is based on a number of misconceptions.

  1. First, understand that meteorologists are scientists who observe and measure weather patterns.
  2. Next realize that forecasters simply broadcast the forecasts of meteorologists.
  3. There are currently 13 land-based weather station networks, 2,000 Automated Surface Observing Systems (ASOS) stations, 26,000+ weather stations that are part of the Meteorological Assimilation Data Ingest System (MADIS), and over 250,000 personal weather stations (i.e., owned by people like you and me).
  4. All of this data (at least most of it) gets transmitted to various centers around the country. Meteorologists, then, assimilate and extrapolate every piece of meteorological data they can get their grubby hands on. Of course, it’s impossible for just one human being to do anything with this data, so “experts” sometimes rely on supercomputers to help them process it.
  5. Afterward, meteorologists or supercomputers (or a combination of both) generate predictions based on what they know and have been trained to do.
  6. These predictions are then made available to local forecasters. Local forecasters now have a choice: They can either broadcast predictions word-for-word or (if he or she was trained on how to interpret particular kinds of weather models) devise his or her own interpretations about what the weather will be like over the course of several days.
  7. Ironically, even with the minds of over 10,000 atmospheric scientists (including meteorologists), countless local weather forecasters, tens of supercomputers, and nearly half a million weather stations sending in data every day, METEOROLOGY WILL NEVER BE AN EXACT SCIENCE. Regardless of what you might hear on television or read in the newspaper, no one will ever be able to accurately predict with 100 percent certainty the tide of our complex weather system.
  8. In fact, just to highlight the misleading inherent bias in weather forecasting, the public is plagued with something insidious called wet bias. According to Wikipedia,

 

The term wet bias refers to the phenomenon whereby some weather forecasters (usually deliberately) report a higher probability of precipitation (in particular, of rain) than the probability they believe (and the probability borne out by empirical evidence), in order to increase the usefulness and actionability of their forecast.

The Weather Channel has been empirically shown, and has also admitted, to having a wet bias in the case of low probability of precipitation (for instance, a 5% probability may be reported as a 20% probability) but not at high probabilities of precipitation (so a 60% probability will be reported as a 60% probability).

Some local TV stations have been shown as having significantly greater wet bias, often reporting a 100% probability of precipitation in cases where it rains only 70% of the time.

They do this simply because if the probability of precipitation is low, spectators may interpret the forecast as meaning there’s no chance of rain and then be really upset if it does rain. In other words, a weather forecaster

…compensates for the people that have greater loss aversion than they think they do, and therefore miscalculate their cost-loss ratio when it is low, by deliberately inflating probabilities. … The Weather Channel [admits], “If the forecast was objective, if it has zero bias in precipitation, we are in trouble.”

The same can be said for hot bias, dry bias, allergy bias, and so on. Point is the next time you’re planning something important, don’t rely on your local weather forecaster. Take whatever he or she says with a grain of salt. The best thing you can do is come up with several contingency plans just in case the expected becomes the unexpected.

 

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