|Sandusky, Ohio snow on February 25, 2016. Photo courtesy: Bryan Edwards (Twitter)|
Snowfall forecasts are very difficult animals both in the meteorology that's used to create them and the public's perception of the numbers you display.
Tuesday morning, I posted a general low resolution hand drawn preliminary forecast for Thursday's snowfall.
|Preliminary Thursday Snow Forecast Issued Tuesday Morning|
Yet, many people on social media interpreted this preliminary forecast too literally. Several on Twitter freaked out when they saw Lorain close to the 3-5" range contour. I told them it probably didn't matter since its--A RANGE! Sure, Lorain was closer to the potentially heavier snowfall but the overall difference using the range for Lorain was small, probably an inch or two. Yet many on social media see it differently.
Yesterday morning (Wednesday), I adjusted the area of heavier snow further west but KEPT THE RANGES THE SAME. Once again, people on social media interpreted this as a huge alteration in the snowfall forecast to which I replied, "Use the ranges NOT absolute numbers". In reality, the overall forecast within the confines of our ranges remained the pretty much the same aside from shifting the heavier amounts west a bit. Yet the perception by the some was that Lorain went from five inches to one inch.
Most meteorologists on television, the public sector (National Weather Service) and in private industry use snowfall ranges in their forecasts. This works best because it takes into account the variance in movement and intensity of the many individual bands of snowfall within snowfall systems. The problem for the meteorologist is that most people want A SPECIFIC SNOWFALL NUMBER for their backyard. Yet many people see a snowfall forecast during the morning newscast and believe that this holds for the entire day. Nothing is further from the truth. These forecasts are not one-and-done. They evolve throughout the day as the event unfolds. Forecasts change as the conditions change. People see individual snowfall amounts on their phone apps and believe these over human derived forecasts. They want absolute specifics yet more often than not, one snowfall amount number for any location will not work.
For example, here was my official snowfall forecast issued Thursday morning at 4am for the entire day using ranges:
One specific (WRF 4km) high resolution computer model early in the morning cranked out these amounts for Thursday's snowfall. While these were in line with our official snowfall forecast above, people fixated on some of the individual numbers and were confused.
How do we combat this confusion on social and broadcast media? Good question.
My soft policy is that I rarely post computer model snowfall output unless we are inside 24 hours before a snowfall event. If my intention is to highlight the general outlook for the week ahead, I will post snowfall accumulations without numbers. A quality controlled "hand drawn" map is another option. My ultimate goal is to present information that describes the weather without creating confusion.
Situations like this reminds me of the psychology behind the weather forecast. Most people want exactness in there forecasts. Remember that we are all hard wired to simplify uncertainty. So when a snowfall forecast range is posted on a map, people immediately find a number within that range that best fits. I'd like to say that I make a forecast with a cold, rational eye but I don't. I take into account how people with react to EACH WORD knowing that many people with perceive selective elements to fit their location. I learned that real quick after my first major lake effect event twenty years ago.
If I could make a poster with bullet points for meteorologists, it would list these five at the top
* Public perception is very powerful
* We need to be better communicators of information
* Choice of words is of the utmost importance in conveying severity of the weather
* Risk is personal (public). Mass media is for the masses. Yet people want personal forecasts. Huge conundrum.
* Too much emphasis on uncertainty breeds confusion and inaction. We need to find a delicate balance between voicing uncertainty and sticking to a forecast.