Abstract:
Extremal dependence or independence may occur among the components of univariate or
bivariate random vectors. Assessing which asymptotic regime occurs and also its extent are crucial
tasks when such vectors are used as statistical models for risk assessment in the field of Climatology
under climate change conditions. Motivated by the poor resolution of current global climate models
in North Atlantic Small Islands, the extremal dependence between a North Atlantic Oscillation index
(NAOI) and rainfall was considered at multi-year dominance of negative and positive NAOI, i.e.,
−NAOI and +NAOI dominance subperiods, respectively. The datasets used (from 1948–2017) were
daily NAOI, and three daily weighted regionalised rainfall series computed based on factor analysis
and the Voronoi polygons method from 40 rain gauges in the small island of Madeira (∼740 km2
),
Portugal. The extremogram technique was applied for measuring the extremal dependence within
the NAOI univariate series. The cross-extremogram determined the dependence between the upper
tail of the weighted regionalised rainfalls, and the upper and lower tails of daily NAOI. Throughout
the 70-year period, the results suggest systematic evidence of statistical dependence over Madeira
between exceptionally −NAOI records and extreme rainfalls, which is stronger in the −NAOI
dominance subperiods. The extremal dependence for +NAOI records is only significant in recent
years, however, with a still unclear +NAOI dominance.
