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 Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

The role of multiplicative and additive covariance inflation on ensembledynamics under the presence of model errors is examined. We show thatmultiplicative inflation significantly impacts the alignment of ensembleanomalies onto the backward Lyapunov vectors. Whereas the ensemble is expectedto collapse onto the subspace corresponding to the unstable portions of theLyapunov spectrum, the use of multiplicative inflation contributes to retainanomalies beyond that span. Given that model error implies that analysis erroris not fully confined on the local unstable subspace, this uncovered feature ofmultiplicative inflation is of paramount importance for an optimal filtering.We propose hybrid schemes whereby additive perturbations complementmultiplicative inflation by suitably increasing the dimension of the subspacespanned by the ensemble. The use of hybrid schemes improves analysis RMSE onthe Lorenz-96 model compared to the use of multiplicative inflation alone,emphasizing the role of model dynamics when designing additive inflationschemes.

Dynamical effects of inflation in ensemble-based data assimilation under the presence of model error