March Warmth As A Guide To Summer Temperatures

During each transition season of spring and fall, people incorrectly attempt to predict the next season's warmth or cold by using the current season's temperatures as a guide. The conversations go something like this:

"This warm March means we're in for a super hot summer" or "This cold and rainy fall means we're in for tons of snow this winter." or some other combination like this.

Does this line of thinking work?

I checked the top 10 warmest March years for 8 cities (Cleveland, Cincinnati, Detroit, Indianapolis, Cincinnati, Pittsburgh, Milwaukee and Buffalo) and ranked them. I found the top 10 warmest years that occurred the most frequently for all of the cities and plotted a summer (June through August) composite (blend) temperature map of these years weighting the more frequent--top 6--warm years higher.

Summer blend - Most Frequent Top 10 Warm March Years - Top 6 Weighted Higher

I next plotted the blend of only the top 6 most frequent years of occurrence that were previously weighted. Notice the warmth become more widespread in this blend.

Neither one of these composites above are blast furnace summers by any stretch.

The problem is that both of these composites mask the individual year extremes. Look at each of the top 5 most frequent years of occurrence?  Each summer varies a great deal. A more detailed look at March 2012 (hottest on record in northern Ohio HERE) 

When we create our summer outlook each year, we perform an in-depth analysis of specific current conditions and combine it with computer projections of these conditions into the future. We combine this with some statistical analysis (similar to the above maps) to come up with a consensus outlook. Its more complicated than saying "its warm or cool now therefore it will be warm or cool next month/next season".

Bottom line, seasonal outlooks are very complex.  Don't be fooled by monthly warmth especially in early spring. It doesn't necessarily mean that an equally warmer than normal summer is ahead.

More on the summer outlook later in April.

Tale of Two Different Aprils

Cedar Point in late April

It's hard to believe but temperatures for the first 3 weeks of April were well above normal. I've mentioned this fact to many people and they don't believe me.  Of course since then, the average temperatures have been anything but warm. The recency effect, as I've written, has certainly played a part in most people's perceptions of the April temperatures as a whole. Here are the numbers and handy pictures:

The first 20 days of April were above normal for not only Ohio but much of the US.

It was the 4th warmest first 20 days of April in Cleveland since 1871! The only years warmer were 1945, 1955 and 2010.

 Then the bottom fell out since then...

The temperatures across not only Cleveland but the Great Lakes, Ohio Valley and portions of the Deep South were well below normal. The period from April 21 through April 28 was the 7th coldest on record. The last year which featured a colder late April was 1940!

Luckily, the forecast for the beginning of May is showing a nice warm up. Expect temperatures in May to average above normal.

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.