Editing Predictability (section)

==In weather and climate==
{{See also|Potential predictability|Butterfly effect#In weather}}
As [[climate change]] and other weather phenomenon become more common, the predictability of climate systems becomes more important. The [[IPCC]] notes that our ability to predict future detailed climate interactions is difficult, however, long term climate forecasts are possible.<ref>{{cite web|title=Predictability of the Climate System|url=https://www.ipcc.ch/ipccreports/tar/wg1/265.htm|website=Working Group I: The Scientific Basis|publisher=IPCC|access-date=26 September 2017}}</ref><ref>{{Cite book |last=Solomon |first=S., D. Qin, M. Manning, Z. Chen, M. Marquis, K. Averyt, M. Tignor, and H. L. Miller Jr., Eds |title=Climate Change 2007: The Physical Science Basis. |publisher=Cambridge University Press |year=2007 |location=Cambridge, United Kingdom and New York, NY, USA |pages=996}}</ref>

=== The dual nature with distinct predictability ===
Over 50 years since Lorenz's 1963 study and a follow-up presentation in 1972, the statement “weather is chaotic” has been well accepted.<ref name=":0" /><ref name=":1" /> Such a view turns our attention from regularity associated with Laplace's view of determinism to irregularity associated with chaos. In contrast to single-type chaotic solutions, recent studies using a generalized Lorenz model<ref>{{Cite journal |last=Shen |first=Bo-Wen |date=2019-03-01 |title=Aggregated Negative Feedback in a Generalized Lorenz Model |journal=International Journal of Bifurcation and Chaos |volume=29 |issue=3 |pages=1950037–1950091 |doi=10.1142/S0218127419500378 |bibcode=2019IJBC...2950037S |s2cid=132494234 |issn=0218-1274|doi-access=free }}</ref> have focused on the coexistence of chaotic and regular solutions that appear within the same model using the same modeling configurations but different initial conditions.<ref>{{Cite journal |last1=Yorke |first1=James A. |last2=Yorke |first2=Ellen D. |date=1979-09-01 |title=Metastable chaos: The transition to sustained chaotic behavior in the Lorenz model |url=https://doi.org/10.1007/BF01011469 |journal=Journal of Statistical Physics |language=en |volume=21 |issue=3 |pages=263–277 |doi=10.1007/BF01011469 |bibcode=1979JSP....21..263Y |s2cid=12172750 |issn=1572-9613|url-access=subscription }}</ref><ref>{{Cite book |last1=Shen |first1=Bo-Wen |last2=Pielke Sr. |first2=R. A. |last3=Zeng |first3=X. |last4=Baik |first4=J.-J. |last5=Faghih-Naini |first5=S. |last6=Cui |first6=J. |last7=Atlas |first7=R. |last8=Reyes |first8=T. A. L. |title=13th Chaotic Modeling and Simulation International Conference |chapter=Is Weather Chaotic? Coexisting Chaotic and Non-chaotic Attractors within Lorenz Models |date=2021 |editor-last=Skiadas |editor-first=Christos H. |editor2-last=Dimotikalis |editor2-first=Yiannis |chapter-url=https://link.springer.com/chapter/10.1007/978-3-030-70795-8_57 |series=Springer Proceedings in Complexity |language=en |location=Cham |publisher=Springer International Publishing |pages=805–825 |doi=10.1007/978-3-030-70795-8_57 |isbn=978-3-030-70795-8|s2cid=245197840 }}</ref> The results, with attractor coexistence, suggest that the entirety of weather possesses a dual nature of chaos and order with distinct predictability.<ref>{{Cite journal |last1=Shen |first1=Bo-Wen |last2=Pielke |first2=Roger A. |last3=Zeng |first3=Xubin |last4=Baik |first4=Jong-Jin |last5=Faghih-Naini |first5=Sara |last6=Cui |first6=Jialin |last7=Atlas |first7=Robert |date=2021-01-01 |title=Is Weather Chaotic?: Coexistence of Chaos and Order within a Generalized Lorenz Model |journal=Bulletin of the American Meteorological Society |language=EN |volume=102 |issue=1 |pages=E148–E158 |doi=10.1175/BAMS-D-19-0165.1 |bibcode=2021BAMS..102E.148S |s2cid=208369617 |issn=0003-0007|doi-access=free }}[[File:CC-BY icon.svg|50px]]  Text was derived from this source, which is available under a [https://creativecommons.org/licenses/by/4.0/ Creative Commons Attribution 4.0 International License].</ref>

Using a slowly varying, periodic heating parameter within a generalized Lorenz model, Shen and his co-authors suggested a revised view: “The atmosphere possesses chaos and order; it includes, as examples, emerging organized systems (such as tornadoes) and time varying forcing from recurrent seasons”.<ref>{{Cite journal |last1=Shen |first1=Bo-Wen |last2=Pielke |first2=Roger |last3=Zeng |first3=Xubin |last4=Cui |first4=Jialin |last5=Faghih-Naini |first5=Sara |last6=Paxson |first6=Wei |last7=Kesarkar |first7=Amit |last8=Zeng |first8=Xiping |last9=Atlas |first9=Robert |date=2022-11-12 |title=The Dual Nature of Chaos and Order in the Atmosphere |journal=Atmosphere |language=en |volume=13 |issue=11 |pages=1892 |bibcode=2022Atmos..13.1892S |doi=10.3390/atmos13111892 |issn=2073-4433 |doi-access=free}}</ref>

===Spring predictability barrier===
The spring predictability barrier refers to a period of time early in the year when making summer weather predictions about the [[El Niño–Southern Oscillation]] is difficult. It is unknown why it is difficult, although many theories have been proposed. There is some thought that the cause is due to the [[ENSO]] transition where conditions are more rapidly shifting.<ref>{{cite web|last1=L'Heureux|first1=Michelle|title=The Spring Predictability Barrier: we'd rather be on Spring Break|url=https://www.climate.gov/news-features/blogs/enso/spring-predictability-barrier-we’d-rather-be-spring-break|website=Climate.gov|publisher=NOAA|access-date=26 September 2017}}</ref>