In the 1960s, meteorologist Edward Lorenz was running weather simulations on an early computer system when he realized that a small rounding difference led to extremely divergent weather predictions. He later called this idea the butterfly effect to communicate that small changes in initial conditions, like a butterfly flapping its wings in Nepal, could produce wildly different outcomes, like rain in New York.
But better understanding those initial conditions and how the biological world couples with the atmospheric one can provide better predictions about the future of the planet—from where umbrellas may be most needed in a given season to where electricity needs might sap the grid.
Today, computers are much more powerful than when Lorenz was working, and scientists use a special kind of simulation that accounts for physics, chemistry, biology, and water cycles to try to grasp the past and predict the future. These simulations, called Earth system models, or ESMs, attempt to consider the planet as a system made up of components that nudge and shove each other. Scientists first developed physical climate models in the 1960s and 1970s, and became better at integrating atmospheric and ocean models in subsequent years. As both environmental knowledge and computing power increased, they began to sprinkle in the other variables, leading to current-day ESMs.
“It's coupling together usually an atmosphere model, an ocean model, a sea ice model, land model, together to get a full picture of a physical system,” said David Lawrence, a senior scientist at the National Center for Atmospheric Research's Climate and Global Dynamics Laboratory, which he noted was recently changed to the CGD Laboratory to remove the word climate. The models also move beyond the planet’s physical components, including chemistry and biology.