Weather is a complex system. The dynamics of air, temperature, and humidity interact in nonlinear ways that result in unpredictable behavior. Weather has sensitivity to initial conditions, meaning that small deviations in the inputs can result in widely different outcomes over moderate time lengths. In the 1950s and 1960s, a meteorologist named Edward Lorenz discovered that his models of weather were very sensitive to initial conditions. Changing the input data by a tiny amount resulted in a change from sun to rain a week later in his simulation. It was surprising at the time that such small changes could cause such large uncertainty in forecasts. Sensitivity to initial conditions is one of the reasons that weather forecasts are only accurate for a week or two in the future. The input data isn’t accurate enough to do much better.
This led to the idea of the butterfly effect. A butterfly flaps its wings, creating a small change in initial conditions. Over time, these changes could grow to eventually cause a tornado on the other side of the planet. Let’s hope that all butterflies aren’t as devious as the one depicted here.