HARD TO FORECAST:
MEETING PUBLIC EXPECTATIONS
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METEOROLOGIST JEFF HABY
With the advancements in technology there can be an expectation that more and greater things can be accomplished. This is generally
true. This works in forecasting also. Each 10 years generally experiences an increase in forecast accuracy. The problem though is that
these expectations can be taken to the extreme. This is called unrealistic expectations. An example of an unrealistic expectation is
a question like, “for our outdoor event in 5 days from now, will it be raining?”. This is such an easy question to ask and seems
reasonable. However, the advancements in meteorological technology have not allowed a certain answer to this question to be formulated.
A reason why future predictions of weather can not be answered with a simple yes or no is because the science of prediction deals with
probability and not certainty. The probability forecast is a permanent fixture of weather forecasting. It is true that more accurate
forecasts can be obtained with more data and better analysis techniques but a goal of having certain predictions is a limit that
can not be obtained.
As technology improves, expectations tend to increase right along with it. For example, 5 day forecasts are more accurate today than
20 years ago due to better analysis and data techniques. The increased accuracy may not be noticed by the public though since there
will be an expectation for even more improved forecasts. Increasing expectation examples include forecasts with better temperature
accuracy at longer time frames, a more precise time that rain will fall in the short term forecast, and not only better 10 day forecasts
but the addition of a 15 day forecast. Forecasting improvements tend to be taken for granted as they happen and then an expectation for
additional improvement is requested. This can cause great frustration in weather forecasters. The public thinks in terms of certainty
while forecasters have to think in terms of probability. One way to explain this to the public is to use examples of sporting events,
news events and political events. For example, it is not certain which team will win the Super Bowl, the value of the stock market in
5 days from now, and who the next president of the United States will be. The weather is no different than a probability that occurs
with future news, the stock market, sporting events, and elections but somehow the weather is often viewed differently as if we will
somehow be possible to predict weather with certainty. All predictions have to have probability introduced into the forecast to have
a thorough comprehension of what may happen.
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