Understanding the difference between potential and hype

I think I personally hit a bit of a breaking point today. Around 6:00am this morning, we received an inquiry regarding the potential winter weather events next week.  This is nothing terribly unusual — our email inbox is normally filled with these and we do our best to try and answer them and keep people informed. The title of the email read “Information Regarding Blizzard Feb 8” and the contents essentially asked us for our snowfall forecast for the upcoming “Blizzard” which the mailer was under the assumption was going to arrive next week. In the email was a model image, produced by Weatherbell Analytics, which showed the snowfall totals from a ECMWF Ensemble Control run at 200+ hours. It was then that I realized we had a big problem on our hands.

This is nobody’s fault. Not the mailer, nor the company which produced the map. It isn’t our fault, your fault, or any meteorologists. In fact — nobody is to blame. But it is a problem, because the image went viral on social media and many in the general public took it as fact. And so, as meteorologists, it is our job to source back this issue and try to figure out how to avoid it happening again. Similar things have occurred during storms in the past, as recently as a month ago, and the end result is never pretty.

This snowfall total map, which went viral yesterday, is a snowfall forecast from an ensemble member of the ECMWF model.

This snowfall total map, which went viral yesterday, is a snowfall forecast from an ensemble member of the ECMWF model.

In the meteorological community, the root of the issue lies in the simple fact that people want to share information as quickly as possible to reach as many people as they can. Some have no ill intentions and want to share the information for the greater good. Others specifically tailor their posts to try and share model images that garner attention and hype. Regardless of this, the images are making it to the internet.

Think of it this way: Weatherbell produces these model images for meteorologists, forecasters and hobbyists. There are 50 other sources or more from which you can gain this information as well. In today’s technological age, these images make their way into the hands of thousands — and not everybody, like meteorologists, can understand exactly the significance of them.

And the issue, therefore, lies within the understanding gap between the public and meteorologists.

Here’s something which my freshman year meteorology professor made very clear was essential to working in the field: Forecast models are for guidance only.

This seems like a simple piece of advice at first, but it has come up time and time again in my experience forecasting over the last 5+ years. It is essential to remember that forecast models are computers, which are simulating the fluid atmospheric process. There are many different forecast models, all with a different set of equations, resolution, biases, and more. As meteorologists, our job is to understand the actual evolution and progression of the pattern and discern between which models have the correct idea and which don’t. As you can imagine, beyond about 84 hours, it can become a total mess. So when we see these images, of a random model’s snowfall forecast at 200+ hours, making the rounds — we cringe.

Here’s the thing though: It isn’t the general public’s job to understand this. So this leaves us meteorologists with two jobs. First, we shouldn’t  share information that won’t do the public any good. There is a fine line between creating fair warning and causing confusion and hype. We need to continue to discern between what is relevant and what isn’t. Second: We need to educate, to the best of our ability, the public on what these forecast models mean and what the images are telling us. This will help bridge the gap in understanding between meteorologists and the general public, eventually causing less hype and confusion.

In the medium and long range, anywhere beyond 84 hours in advance essentially, meteorology is much more about pattern recognition than it is about individual forecast models. The model image pictured above was one solution amongst an innumerable amount. To speak to its variability, that very same forecast model now shows absolutely nothing for the same valid time frame. Meteorologists, for instance, use ensemble guidance at this range to help cut down on the wild variability. Essentially, most models have an ensemble of satellite models of their own, and when you blend together the mean of them, meteorologists can gain a better understanding of what may be going down — and which way things are trending over time.

So here’s my advice: Use your trusted sources. Understand that more than ever, this information is becoming freely available and also understand that people will be posting these things for reasons other than just to warn you. Know that forecast models beyond 5-7 days are subject to extreme variability and are unreliable — they simply are not designed to be used for individual forecasts *especially* snowfall totals. Most importantly, try to discern between what meteorologists flag as potential based on recognition and understanding of the pattern evolution, and what others may unknowingly spread as hype.

Meteorology is a very complicated field. This is something that probably has become increasingly evident to many people over the past few years, regardless of prior opinions. It truly is a unique and difficult science. That being said, the general public has come to a much better understanding of how things work as far as the innards of a forecast — and we can still improve that understanding. With meteorologists and the public working together, we can at the very least significantly cut down on the amount of misunderstandings we have in the future over model graphics of similar nature.



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