Imagine this: You are planning your day, dressing your kids, or worried about the weather and you turn on your radio to get a forecast. And the forecast is in German! Even if the forecast is 100% accurate, a "perfect" forecast, does it help you choose the right clothes or precautions? For a few million American citizens this - forecasts in a non-native language - is a reality.
Now imagine this: You have a piece of information or advice that will save your friend's life. All she needs to do is listen to you and wait 30 minutes before she runs an errand. What if you can't get in touch with her? What if she ignores you? What if someone else gives her conflicting advice? What would it be like to watch her drive right into peril to run an errand that wasn't worth her life?
This scenario - the failure of life-saving information to influence good decisions - is something forecasters deal with far too often.
For the past week, I've had the opportunity to attend a workshop that asks these kind of questions to the weather community. You know, stuff like, "Is an accurate forecast that nobody heeds really a good forecast?", and "Why do people drive into running water?" and "What influences decision-making under pressure?" and "If young, single men are overwhelmingly more likely to take risky behavior (like driving into a flooded roadway), why do our educational materials often feature a woman holding a baby?"
Why? (photo set courtesy of US Geological Survey)
The name of the workshop is WAS*IS, short for "Weather and Society * Integrated Studies". It's design will help produce more effective forecasts and weather products, but not necessarily by improving the accuracy or precision of them. WAS*IS is more focused on how they are used and interpreted.
Asking these questions may seem like common sense to you and me. But here's the reality: in the culture of science, painting outside the boundaries of your discipline rarely earns you career advances. So, young scientists are often left with a choice: Do I keep working within the confines of data and numbers, or do I take a risky plunge into making meaning out of all this? I made this plunge a few years ago, and while it was personally rewarding beyond expectations, more than a few of my colleagues have asked me why I would do something so silly.
And that's where WAS*IS comes in. It's half-filled with young meteorologists (and a few of us not so young!), who represent the future of the discipline. But it's also half-filled with professionals that study human behavior, learning and values. Yesterday, I sat between a historian and a sociologist. We spoke about what it means to do good work. Is it an accurate forecast, or a life saved? What has worked elsewhere? Why do we do things the way we do? By beginning these conversations, I'm optimistic that we can do so much more than produce more accurate forecasts. We can produce more meaningful forecasts.
So, what do you think? What's your input? How would you improve the forecast-and-warning system we have now? Have you ever been "caught" in a situation when you didn't know a warning was out there?
