Deterministic Nonperiodic Flow (nonfiction): Difference between revisions

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* [[Crimes against mathematical constants]]
* [[Crimes against mathematical constants]]
* [[Did you step on a butterfly in Texas during a tornado while watching Jurassic Park in Brazil under the influence of JJ-180?]]
* [[Gnomon algorithm]]
* [[Gnomon algorithm]]
* [[Gnomon Chronicles]]
* [[Gnomon Chronicles]]
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* [https://journals.ametsoc.org/doi/pdf/10.1175/1520-0469%281963%29020%3C0130%3ADNF%3E2.0.CO%3B2 Deterministic Period Flow]
* [https://journals.ametsoc.org/doi/pdf/10.1175/1520-0469%281963%29020%3C0130%3ADNF%3E2.0.CO%3B2 Deterministic Period Flow]


== Attribution ==


[[Category:Nonfiction (nonfiction)]]
[[Category:Nonfiction (nonfiction)]]
[[Category:Chaos theory (nonfiction)]]
[[Category:Chaos theory (nonfiction)]]

Latest revision as of 12:28, 2 November 2020

Chart from "Deterministic Nonperiodic Flow" by Edward Lorenz.

"Deterministic Nonperiodic Flow" is a 1963 paper by mathematician and meteorologist Edward Lorenz published in Journal of the Atmospheric Sciences. The paper was influential in the early development of chaos theory.

Lorenz states in the paper:

Two states differing by imperceptible amounts may eventually evolve into two considerably different states ... If, then, there is any error whatever in observing the present state—and in any real system such errors seem inevitable—an acceptable prediction of an instantaneous state in the distant future may well be impossible....In view of the inevitable inaccuracy and incompleteness of weather observations, precise very-long-range forecasting would seem to be nonexistent."

His description of the butterfly effect, the idea that small changes can have large consequences, followed in 1969.

Lorenz's insights on deterministic chaos resonated widely starting in the 1970s and 80s, when it spurred new fields of study in virtually every branch of science, from biology to geology to physics. In meteorology, it led to the conclusion that it may be fundamentally impossible to predict weather beyond two or three weeks with a reasonable degree of accuracy. However, the recognition of chaos has led to improvements in weather forecasting, as now forecasters recognize that measurements are imperfect and thus run many simulations starting from slightly different conditions, called ensemble forecasting.

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