Quasiperiodicity is the property of a system that displays irregular periodicity. Periodic behavior is defined as recurring at regular intervals, such as "every 24 hours".[1] Quasiperiodic behavior is a pattern of recurrence with a component of unpredictability that does not lend itself to precise measurement.[2] It is different from the mathematical concept of an almost periodic function, which has increasing regularity over multiple periods.

Climatology

Climate oscillations that appear to follow a regular pattern but which do not have a fixed period are called quasiperiodic.[3][4]

Within a dynamical system such as the ocean-atmosphere oscillations may occur regularly, when they are forced by a regular external forcing: for example, the familiar winter-summer cycle is forced by variations in sunlight from the (very close to perfectly) periodic motion of the Earth around the Sun. Or, like the recent ice age cycles, they may be less regular but still locked by external forcing. However, when the system contains the potential for an oscillation, but there is no strong external forcing it to be phase-locked to it, the "period" is likely to be irregular.

The canonical example of quasiperiodicity in climatology is El Niño–Southern Oscillation (ENSO).[5] ENSO is highly consequential for wheat cultivation in Australia.[5] Models to predict and thereby assist adaptation to ENSO have a large potential benefit to Australian wheat farmers.[5] In the modern era, it has a "period" somewhere between four and twelve years and a peak spectral density around five years.

See also

References

  1. ↑ Periodicity – Definition and More from the Free Merriam-Webster Dictionary
  2. ↑ Quasiperiodic – Definition and More from the Free Merriam-Webster Dictionary
  3. ↑ Not Found – UNISDR
  4. ↑ The meteorological glossary: 2d ed. 1930. Meteorological Office, Great Britain. "Certain phenomena which recur more or less regularly but without the exactness of truly periodic phenomena are termed quasi-periodic."
  5. 1 2 3 Potgieter, Andries; Zhao, Yan; Tejada, Pablo; Chenu, Karine; Zhang, Yifan; Porker, Kenton; Biddulph, Ben; Dang, Yash; Neale, Tim; Roosta, Fred; Chapman, Scott (2021). "Evolution and application of digital technologies to predict crop type and crop phenology in agriculture". in silico Plants. Oxford University Press (OUP) (The Annals of Botany Company (AoB)). 3 (1). doi:10.1093/insilicoplants/diab017. hdl:11343/280690. ISSN 2517-5025. This review cites this study: Zheng, Bangyou; Chapman, Scott; Chenu, Karine (2018). "The Value of Tactical Adaptation to El Niño–Southern Oscillation for East Australian Wheat". Climate. 6 (3): 77. Bibcode:2018Clim....6...77Z. doi:10.3390/cli6030077. CK ORCID 0000-0001-7273-2057.


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