Difficulty of prediction in many fields of science

Some fields of science have great difficulty in accurate prediction and forecasting. In some fields the complexity of data makes it difficult (pandemics, demography, population dynamics, climate prediction, prediction of natural disasters and, in general, meteorology). Prediction difficulties are due to different causes:

The above explanations are compatible with determinism, and a more radical possibility that would prevent effective prediction is that a phenomenon was effectively random or its behavior with current knowledge could not be distinguished from genuinely random behavior.

Predictability and determinism

The determinism of a certain physical theory, such as Newtonian mechanics, is frequently confused with effective predictability in the medium or long term.

The temporal evolution is evident in which macroscopic physical systems can be described by differential equations and, therefore, from a formal point of view they are deterministic, since the initial conditions determine the entire future of the temporal evolution. However, this theoretical possibility is not feasible in practice, because some systems have high "sensitivity to initial conditions", which means that small errors in the measurement used to determine the initial conditions lead to exponential divergences over time.

Chaotic systems (for example, weather systems) are of this type, which is why, although they are deterministic, they do not allow effective long-term prediction. Currently, the computer models used in weather prediction are highly reliable four days in advance and, although simulations are made for ten days or more, it is known that in that interval they are not very approximate. Therefore long-term climate prediction is only reliable for general behavior, but not for accurate weather prediction. In the case of atmospheric weather, its chaotic character was suggested by Edward Lorenz in 1963. Topological methods applied to hydrodynamics have made it possible to establish required limits for the precision of the initial data to make reliable forecasts. Currently, numerical simulations at 3 or 4 days are reliable, but with more than 10 days they are very imprecise.

Difficulty of prediction in many fields of science

Some fields of science have great difficulty in accurate prediction and forecasting. In some fields the complexity of data makes it difficult (pandemics, demography, population dynamics, climate prediction, prediction of natural disasters and, in general, meteorology). Prediction difficulties are due to different causes:

The above explanations are compatible with determinism, and a more radical possibility that would prevent effective prediction is that a phenomenon was effectively random or its behavior with current knowledge could not be distinguished from genuinely random behavior.

Predictability and determinism

The determinism of a certain physical theory, such as Newtonian mechanics, is frequently confused with effective predictability in the medium or long term.

The temporal evolution is evident in which macroscopic physical systems can be described by differential equations and, therefore, from a formal point of view they are deterministic, since the initial conditions determine the entire future of the temporal evolution. However, this theoretical possibility is not feasible in practice, because some systems have high "sensitivity to initial conditions", which means that small errors in the measurement used to determine the initial conditions lead to exponential divergences over time.

Chaotic systems (for example, weather systems) are of this type, which is why, although they are deterministic, they do not allow effective long-term prediction. Currently, the computer models used in weather prediction are highly reliable four days in advance and, although simulations are made for ten days or more, it is known that in that interval they are not very approximate. Therefore long-term climate prediction is only reliable for general behavior, but not for accurate weather prediction. In the case of atmospheric weather, its chaotic character was suggested by Edward Lorenz in 1963. Topological methods applied to hydrodynamics have made it possible to establish required limits for the precision of the initial data to make reliable forecasts. Currently, numerical simulations at 3 or 4 days are reliable, but with more than 10 days they are very imprecise.