This post is to help to jump to the defense of meteorologists long range forecasts. Generally forecasts for a current day can be assumed to be close to 100% correct, however they can lose that percentage as the hours and days increase. As I have written in previous posts our atmosphere is like a large ocean and the swirls and currents can change. Our Mets do the best they can with the data they have at any given moment to predict what is going to happen at any given location. Most of this data comes from computer models and can be only guesses at best as they move past a couple days.
The Butterfly Effect refers to instances where small variations in initial conditions in a system can result in significant changes later down the line.
The Butterfly Effect was originally ‘discovered’ in simulations of weather prediction. Researchers found that minute changes in the initial pre-conditions would yield extremely different results as the simulation progressed. However, the Butterfly Effect can be seen in simple systems as well as complex systems – the height and position from where a bouncy ball is dropped will have a significant impact on its pattern of movement thereafter.
In a mathematical context, the butterfly effect is an important idea in chaos theory and it is commonly phrased as a ‘sensitive dependence on initial conditions.’ Chaotic events are those in which outcomes can’t be calculated despite the fact that incremental steps can be predicted and measured.
The Butterfly Effect is named after the most common example, which is the formation of a severe hurricane being dependent on whether a single butterfly had fluttered its wings days or weeks earlier. It was named by American mathematician Edward Norton Lorenz, known as the father of chaos theory.
In the early 1960s Lorenz discovered that the weather exhibits a nonlinear phenomenon known as sensitive dependence on initial conditions. He constructed a weather model showing that almost any two nearby starting points, indicating the current weather, will quickly diverge trajectories and will quite frequently end up in different “lobes,” which correspond to calm or stormy weather. He explained this phenomenon, which makes long-range weather forecasting impossible, to the public as the “butterfly effect”: in China a butterfly flaps its wings, leading to unpredictable changes in U.S. weather a few days later.
As bizarre as it may sound, if I say that a butterfly flapped its wing in Brazil, and a tornado took place in Chicago, that’s what the theory states. Note that the butterfly in Brazil did not directly cause the tornado. A flap is simply a change in the present state, which gives rise to further events. Once that chain is complete, which the butterfly started, a tornado takes place in Chicago. In short, perturbations created by them give birth to a major happening.
So, before you take out your frustrations on inaccurate futurecasts in the weather by your local Met keep in mind that a butterfly or even a flock of barn swallows downstream can cause changes in the weather pattern meaning small changes in a weather pattern can have major effects downstream.
Our cooler than normal temps will continue on through most of the rest of the month according to the CPC and things should start to dry out (hopefully). We could see some heavy rain and rumbles of thunder today…
Seven Day Forecast
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