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greater than chance. The accuracy of the
almanac’s predictions is further confused by
the vague language used. While they explain
how to read the almanac on their website, it

is observed that language like “greater than
usual” and “less than usual” allows the almanac
to claim accuracy when they are just stating

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the usual averages and leaning on the law
of averages. For example, the term “greater
than usual snow’ is used in the almanacs.
How much greater? Another criticism is
that historic averages can’t help when the
weather is abnormal. It is mentioned that
meteorology used to be all about looking at
historic averages, so the almanac does share
that method with historic meteorology—
but the almanac cannot predict day-to-day
changes with their method.

Meteorologists emphasize that any
weather prediction past a week is unreliable,
and that even day-to-day forecasts are, at
this point in science, seen as impossible
to master. Because there are a mind-
boggling number of variables in predicting
weather, forecasts are all about the amount
of power behind the huge calculations
needing completion. With the help of
supercomputers, meteorologists are able
to input these millions of variables without
needing the manpower of thousands upon
thousands of people to complete these
equations. The availability of accurate and
constantly updated weather data is what
has pushed meteorology forward, so the
almanacs making accurate far-reaching
predictions without considering any of this
revolutionary data seems unlikely.

It is said that if every molecule in the
system were monitored, we would be able
to predict the exact weather, but as that is
impossible (at this point in human history
anyway), all weather readings are guaranteed
to be inexact educated guesses. This where
the “Butterfly Effect” comes into place—a
theory first postulated by meteorologist
Edward Lorenz in the 1960s. The theory
basically explains that with a system as

complex and as filled with variables as the
weather, small changes in one aspect have
the power to create big changes in the final
forecast of the weather. His theory was also
known as “chaos theory.”

 

Instances where forecasters have been
drastically off the mark after being so confident
understandably contribute to the negative
impression many have of meteorologists—and
perhaps is why more than a million people
look to the two popular farmer almanacs for
alternative weather forecasts. For an example
of the failings of forecasters, a 19-year-old
boy named Jacob Meisel made his own app
that predicted the floods due to Superstorm
Sandy much more accurately than the local
weather program. A study in Kansas City
found that when local forecasters predicted
a 100 percent chance of rain, it only actually
rained roughly 33 percent of the time. These
examples certainly don’t build up the image of
the weatherman. It is understandable where
the confusion and contempt comes from, but
there have been many successes in metrology.
Hurricane and flood prediction is one huge
advancement to consider. Another factor to
consider is that information used to predict
the weather isn’t available to every network
and station. Less populated areas have less
technology to predict the weather.

Knowing that meteorology is still a new
and developing science with little accuracy
is essential when trying not to drown in the
plethora of weather reports coming at you. We
can't completely discount the credibility of the
almanacs without reviewing their methods—
but if they bar the public from reviewing
their methods, the secrecy is certainly reason
for suspicion. It is no question that their
methods are out of place in the field of science.
Meteorology, while a changing and improving
science, is still very fetal in its methods and
theories. Strides in weather forecasting are
on the horizon, but until then, we'll have to
appreciate the technology we have now and
learn to live in the uncertainty of weather. And
without the uncertainty of weather, where
would small talk be?

A study in Kansas City found that when local forecasters predicted a 100 percent
chance of rain, it only actually rained roughly 33 percent of the time.