Figure 2. a) Slopes of
the regional trends at different durations for observed and modelled AM;
significant trends (α-level=0.05) are marked; stochastic uncertainty
associated with the modelled AM (90% C.I. of the MonteCarlo simulation)
is also reported. b) Slopes of the regional trends for the
model parameters: scale parameter (λ), shape parameter (κ), and yearly
number of storms (n); significant trends (α-level=0.05) are marked.c) Differential impact on the modelled trends of combinations
of changes and no-changes in the model parameters; series labels report
the parameters which are allowed to change. d) Slopes of the
regional trends for some estimated return levels (2, 10, 25, 50 yr);
significant trends (α-level=0.05) are marked; note that the 2 yr return
levels correspond to the modelled AM.
3.4 Changes in the proportion of convective-like events
The parametrization of our model allows us to formulate hypotheses about
the physical processes underlying the detected changes. In particular,
the observed changes could be explained by an increased number of
intense convective events, which would mainly contribute to the short
duration annual maxima. We analyze possible changes in the number of
storms occurring in different seasons, and in the seasonal number of
convective-like and other types of storms (Figure 3 ). The
positive trend in the yearly number of storms reported above is fully
explained by the increases in the number of storms in autumn (SON,Figure 3 a) and in winter (DJF). However, examining changes in
the types composition shows no distinct increase in convective-like
storms during these seasons (Figure 3 b, c).
Conversely, although no trend emerges in the number of storms in summer
(JJA), the number of summer convective-like storms in this season
increased significantly, while the number of other storms shows no trend
(Figure 3 b, c). This implies a significant increase in the
proportion of summer convective-like events. Since convective-like
storms are generally associated with heavy intensities at short
durations, this change in composition could explain the observed
increase in tail heaviness at short durations, and thus the observed
trends on short-duration AM. This is confirmed when the parameters of
the ordinary events distribution are examined considering spring-summer
(MAMJJA) and autumn-winter (SONDJF) separately (Figure S2). These
results suggest that the significant positive trends found for
short-duration extremes are mostly related to changes in summer storms,
and that these can be related to changes in the intensity distributions
(increasing tail-heaviness) induced by an increasing proportion of heavy
convective-like storms in the summer.