Seasonal Temperatures – the Math Doesn’t Add Up

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As a professional meteorologist, I have mixed feelings about how the general population hears the weather forecast. And, as a former on-air television and radio meteorologist, I also have mixed feelings about how best to present the weather to the general population.

First, let me say that I don’t mean to insult, but an effective presentation that’s delivered to a broad and largely unknown audience (like those of radio and television) has to be (or should be) presented with the lowest common denominator in mind. You know darn well that if you’re a meteorologist talking to a roomful of meteorologists (or astronauts talking to space people, or lawyers talking to legal people and so on), the words you choose and the concepts or ideas you express will be different than if you’re talking to the local PTA after dinner. It has to be or you’ll lose most of your audience before the third slide. I’m reminded of highway speed limits—they’re not designed for a Ferrari on a warm, sunny day with a professional driver. No, they’re designed for the overloaded SUV, at night, in the rain with a typical American driver at the wheel—the lowest common denominator.

Math isn't easy

Which leaves the on-air meteorologist, arguably the most educated person in science and math at the station, in a bit of a quandary. Meteorology and the movement of the atmosphere are driven by complex mathematical equations, none of which are easy to explain in the 3-, 4- or sometimes 6-minutes segments devoted to the weather on TV (when I did radio, my spots were hard-limited to 30 seconds). So they have to be skipped (ignored) in favor of something more easy to digest. Tell me what you think of this, “And this large dip in the jet stream will bring unsettled weather to Texas and the Southeast.” With the right audience, a meteorologist could turn that single sentence into 30 minutes, easy. However, the television meteorologist isn’t left with many other options.

This came to light the other night when my lovely wife and I were wrapping up the evening watching the late news. The TV meteorologist gave tomorrow’s high and low and compared it to seasonal averages. My wife said, “Wow, we’re nowhere close to where we should be for this time of year.” She’s not quite right about that, although I only said, “Yup. Pretty cold, alright.”

Seasonal temperature norms are only mathematical averages of daily temperatures that have already occurred. With that in mind, if the high one day is 70 and the high the other day is 50, then the norm of the two is 60—yet 60 wasn’t the high on the first day or the second day. In fact, it’s way off what was experienced on either day. These differences become less dramatic when considering years and years of data and less apparent still when the actual temperatures have little variation. However, temperatures on the Gulf Coast in January and February can swing broadly between post-frontal highs in the 30s and return-flow temperatures from the Gulf in the 70s only a few days later. This is a just a local example from my backyard, but any place can have swings from one extreme to the other when the mathematical average is far from representative of what actually occurred. For example, if Houston experiences a January with a week in the 30s, then a week in the 60s, then a week in the 70s then a week back in the 30s, the rough math brings the norm into the upper 40s, yet it’s quite possible there wasn’t a single day with a January high in the upper 40s. What’s normal here is change and often the change is dramatic.

When you watch the TV forecast (or listen to the radio forecast), what do you hear? When the meteorologist says “the average high temperature is 63,” do you long for a week in the low 60s? Or do you remember the plunging and rising thermometer and think, “Yeah, right! When’s the last time we saw a high near 63?” Or perhaps you’re one of the few who would say, “I don’t care about the average temperature, just tell me what it’s going to be tomorrow.”

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