Thursday, April 26, 2018

Probabilistic vs Deterministic Messaging

This past Winter, our office (TFX) participated in the NWS' prob snow experiment. For those who might not be familiar with what that is or what it involved, it was a way to experiment with utilizing snowfall probability information within operations and decision-support activities. Perhaps in another post I'll ponder the good and the bad about the experiment, itself. But, for now, I wanted to take it a different direction.

Related to that experiment, a question was probabilistic or deterministic information better when it comes to messaging? At its core, this question is part of a larger and ongoing debate related to the effective communication of weather hazards. That debate is a fascinating and challenging one, but is probably too long for one post. For now, I'll just address the one piece of the puzzle that focuses on probabilistic vs deterministic messaging.

When it comes to snowfall amounts, what do we often see? Ranges. And, we seem to gravitate toward certain ranges at that. 1-3", 3-6", 6-12". If you are one of those rebel types, you might even use 2-5" or 3-7". Oh the humanity...

The interesting (note I said interesting and not necessarily bad) part about the end-user's use of ranges is the seemingly automatic focus on the high number. Knowing the worst-case scenario isn't a bad thing in of itself, but how it's used can be. Just before a winter storm a couple months ago, a friend of mine texted me and said, 'Hey! I heard we are supposed to get 7" of snow'. The winter product from our office said something to the effect of 2-4" with isolated amounts up to 7", if I remember correctly. My friend read that as we are getting 7" of snow. I doubt he was alone in that assessment.

I often give ranges when messaging upcoming snowfall events and I am not here to argue against that. My end-game is to think through the different possibilities. Recently, I decided to give the ole probability method a try. Prior to a winter event, a caller asked how much snow we expected for her area. With experimentation on the brain, I boldly informed her that there was an 80% chance of exceeding 4" at her house. To which she replied, 'So, do you think we might get a foot?'.

The sample size on my little experiment is incredibly small. But, how much would you be willing to wager against her response representing a large part of the population? One thing that stuck out to me in her response was the 12" amount. After talking with her more, I got the sense that 12" is when she starts having problems in her world. It's the point when her daily plans change. I believe that is why her mind immediately jumped to a foot. For her, my arbitrary percentage-greater-than-x-amount didn't help. Now, had I given her the probability of exceeding 12", well that could have been a different story. Would she have been able to interpret it effectively? I don't know.

When it comes to the general public, the thresholds for when action is taken is all over the place. That lady's threshold was 12". A recent transplant from the South would probably have a different response. So where does that leave us as Meteorologists? In a very challenging position. We have a responsibility to message hazardous weather, but to a group of people who don't even share a common breaking point.

On the flip side, we have individuals or groups (DOT, emergency managers, etc) that often DO have specific thresholds that we can know. I watched an enlightening presentation recently that looked at the potential effectiveness of probability information for decision-makers like the DOT. I get the sense that probability messaging works great for them. Honestly, I believe it could work great for the general public as well. The challenge is our inability to know each and every person's breaking point.

One part of the prob snow experiment that I really liked was that it gave probability information for several breaking points (2", 4", 6", 8", 12", 16"). We may not be able to know all thresholds, but we can certainly try to cover as many as possible in our messaging, within reason. But, that's just snow. What about rain, hail size, tornadoes, tornado strength, etc? Do we say "this storm will produce up to golf ball size hail" or "there is an 80% chance of exceeding quarter size hail?". I'm not sure a warning product is the place to put a lot of probability wording, if nothing else but for the sake of time/understanding. Imagine The Weather Channel scrolling the probability of multiple thresholds, or hearing those probabilities being read over Weather Radio broadcasts/statements?

My answer to the question of probabilistic or deterministic? The verdict is still out, but I imagine it involves some sort of a mix that relates to the known users, the product, and the event. I don't know if there will come a time when all of our messages are completely understood, used correctly, and heeded, but working through and experimenting with this piece of the puzzle is beneficial to the larger discussion regarding effective communication. In the spirit of probabilistic messaging, I will inform you that there is a 100% chance that I will blog more about effective communication down the road...

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