English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

This paper deals with the question of whether uncertainty regarding modelstructure, especially in climate modeling, exhibits a kind of "chaos." Do smallchanges in model structure, in other words, lead to large variations inensemble predictions? More specifically, does model error destroy forecastskill faster than the ordinary or "classical" chaos inherent in the real-worldattractor? In some cases, the answer to this question seems to be "yes." Buthow common is this state of affairs? And are there precise mathematical resultsthat can help us answer this question? We examine some efforts in theliterature to answer this last question in the affirmative and find them to beunconvincing.

An Antidote for Hawkmoths: On the prevalence of structural chaos in non-linear modeling