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

Modeling extremes of climate variables in the framework of climate change isa particularly difficult task, since it implies taking into accountspatio-temporal nonstationarities. In this paper, we propose a new method forestimating extreme precipitation at the points where we have not observationsusing information from marginal distributions and dependence structure. Toreach this goal we combine two statistical approaches of extreme values theoryallowing on the one hand to control temporal and spatial non-stationarities viaa tail trend function with a spatio-temporal structure in the marginaldistributions and by modeling on the other hand the dependence structure by alatent spatial process using generalized `-Pareto processes. This newmethodology for trend analysis of extreme events is applied to rainfall datafrom Burkina Faso. We show that extreme precipitation is spatially andtemporally correlated for distances of approximately 200 km. Locally, extremerainfall has more of an upward than downward trend.

Modeling space-time trends and dependence in extreme precipitations of Burkina Faso by the approach of the Peaks-Over-Threshold