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

. A flexible and highly extensible data assimilation testing suite, namedDATeS, is described in this paper. DATeS aims to offer a unified testingenvironment that allows researchers to compare different data assimilationmethodologies and understand their performance in various settings. The coreof DATeS is implemented in Python and takes advantage of its object-orientedcapabilities. The main components of the package (the numerical models, thedata assimilation algorithms, the linear algebra solvers, and the timediscretization routines) are independent of each other, which offers greatflexibility to configure data assimilation applications. DATeS can interfaceeasily with large third-party numerical models written in Fortran or in C,and with a plethora of external solvers.

DATeS: a highly extensible data assimilation testing suite v1.0