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 Tools annual

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 monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

A computational technique is proposed for studying patterns of interannual variability of climate seasonal means that arise from intraseasonal variability. The method, using monthly means of climate data, is more computationally efficient than other current methods that use daily means to estimate the spatial covariability of the intraseasonal component. Removing this component, it is possible to estimate the long-range potentially predictable patterns of climate variability. The method is applied to a study of the Southern Hemisphere winter circulation and compared with a method using daily data to show that the results are very similar.

A method for studying the influence of intra-seasonal variability on the inter-annual variability of climate fields