Mindset Behind My Snowfall Forecasts

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, inaction and ultimately apathy when the next snow or weather event or importance happens. This is basic psychology that's been well documented over the years. We need to find a delicate balance between voicing uncertainty and sticking to a forecast.

Cognitive Biases: How Do These Affect Your Decision Making?

Click on the image to maximize it.

Behaviorial Meteorology: Psychology Behind Our Cold Weather Perceptions

Last year I wrote an article on how our perceptions of the weather are shaped by events that have
occurred most recently. This winter's cold weather is a prime example: The last two winters have
been milder in comparison so we are preconditioned to believe that this winter would not only be
worse (which it is) but one of the worse in years and comparable to the harsh winter of the 1970s and
early 1980s. Both are false.
 
Why do we perceive this winter to be one of the worst ever? Its a classic example of the RECENCY
EFFECT: This is the tendency to think that more recent trends and patterns we observe (which are
more recent in our minds like our recent mild winters) are a very good representation of the
entire period in question. Since the winters of yesteryear are distant memories, we tend to weight
them less than our memories of recent winters. We believe our memories and observations--
recent mild winters--are excellent predictors of what the near future will bring.

How often has someone said to you this past fall "We are due for a bad winter".  Or how about
this: "This winter has to be one of the coldest ever" or "This colder trend recently surely means
that the rest of the spring and summer will be cold?  That is the RECENCY EFFECT at work.
Those frequently uttered sentences above are totally driven by our perceptions.  Our perceptions
make us feel good because they fit our hard-wired biases.  Most of the time, we grossly
underestimate the significance of our biases. The truth is that this winter is ranked...45th coldest! 
The winter pattern rarely has a connection to spring or summer. Hard to believe but its true.

This type of information might run counter to our perceived notions ultimately becoming a source of
frustration and internal conflict.  We have a built in motivation to reduce conflicting ideas by altering the existing conditions in our mind to create consistency. Pick any topic: weather, economics, politics, investing...anything. We all do it. 

In the case of understanding our winter weather or any weather during any season), we do this by 1)  Believing weather information which best fits our preconceived notions 2)  We alter its importance in our mind and/or dismiss the hard, cold facts and data all together or 3) We just plain criticize it. Sometimes, it’s a blend of all three. This inclination to favor information that reinforces our comfort level is called a "Confirmation Bias".  Incidentally, this happens all of the time inside Facebook comment threads.

Watch what happens when the first cold stretch develops in spring. Everyone will be shouting that
"they knew this would happen because of our cold winter." That's classic CONFIRMATION BIAS.
The problem is that as we create "consistency" through favoring our own view of the information,
we create a new false interpretation of the weather which we believe to be true. Rather than
looking objectively at the reasons for the change scientifically (science scares people), most
people tend to use an overly simplified and often inaccurate scientific explanation of the weather
to ultimately confirm their predispositions.

The response "We are due for a bad winter" has virtually no scientific merit.  For events that require object analysis, our own human nature deceives us.  In this case, our biases "cloud"--no pun intended--our judgment of the weather.  By recognizing our own weather biases, we can actively attempt to dampen the effects. As much as it might hurt, trust the data.