"Of course I couldn't possibly be talking about you."
I'm resurrecting a blog title from an old TCHE article in light of recent snowfall forecasts (for the 12-21/12-22 period), most of which originated on Facebook and Twitter. I hesitate to call these "forecasts," as they were simply regurgitated images of model output posted at face value, without any meteorological interrogation. As an example, here is a popular image that was viral on social media sites by late Monday afternoon:
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| 156 hr. "Total Snowfall" forecast from the ECMWF model initialized 1200 UTC December 16, 2013 |
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| Actual snowfall verification from the 12-21/22-13 cyclone |
As you can see, the heaviest axis of observed snow fell roughly 200 miles further northwest than the model forecast and also totaled nearly 10 in. less in terms of magnitude.
So, what went wrong?
Meteorologically, nothing!
While this was obviously a poor numerical weather model forecast, error only arises when a human interprets this solution as reality. This is not necessarily a ploy to get people to stop posting such images (although that would certainly be nice!), rather I would like to see interrogation of the meteorological fields and discussions of features that would support or refute the forecast in question. This is obviously not feasible on Twitter, yet I keep seeing such images posted. Every snowfall. Every severe weather outbreak. Pictures of various model fields with hype abound. Where are the discussions of vorticity, thermal advection, and frontogenesis; or analysis of variables such as pressure, temperature, and specific humidity that are actually simulated by the governing equations driving the "sexy" model fields?
They're around, just not on social media sites. In fact, I closely followed the Area Forecast Discussions leading up to this event from WFO KLOT (Chicago) and KDVN (Davenport), and I must say they were quite impressive (you can find such discussions here). Both offices discussed uncertainty in the model fields and provided physical meteorological reasoning behind their forecasts. While these forecasts were far more accurate (in the true sense of the word), they were not the first forecasts for the event. Similar to what many are seeing in main-stream journalism, there seems to be a rush to get the word out first, regardless of fact-checking or care for accuracy/precision. It seems that simply being the first to announce a snowstorm a week in advance is more important than getting the forecast correct!
As the event drew closer, images kept popping up of "snowfall" plots slowly shifting the axis of heaviest snow further northwest with each run. I put "snowfall" in quotation marks, as this is not actually a post-processed model output field for the ECMWF, rather a simple 10:1 ice:liquid ratio multiplication, which can itself be a source of significant error depending on the vertical thermal profile. These slow shifts to the northwest were not surprising to me, especially after analyzing low-level potential vorticity fields.
The point here is to suggest better communication practices for meteorologists when dealing with folks who may have little/no meteorological training. Posting an image of 240 hr. snowfall as your forecast may draw you more followers, but where's the verification? You're lucky most people have a short memory! These posts are doing disservice to meteorologists everywhere and helping to perpetuate "the weatherman is always wrong" stereotype. Forecasting is an imperfect science that should be expressed with probabilistic forecasts and associated uncertainty.
Let's strive to be better weather journalists.
